Our arrangement that looks something like this:

Our host OS is Windows running Virtual Box. The guest operating system is Ubuntu running a django server. Before we begin we need to know the IP addresses of the host OS and the guest OS.

**Windows Host IP Address**

Open a command prompt and run the command “ipconfig”. This will list information about every network adapter on the system. Find an adapter that is assigned an IP address. Not this for later, we will call this the host IP address.

**Ubuntu Guest IP Address**

Open a command prompt and run the command “ifconfig”. This command will list all of the network settings for the linux guest operating system. Note the IP, we’ll call it the guest IP address.

**Port Forwarding in Virtual Box**

Virtual Box has the ability to route a port on the host OS to a port on the guest OS. To do this we will need to pick an unused port on the host system. We’ll use 8080. If this port is taken on your machine, pick a different port. On the guest operating system we can configure the Django server to run on any port. We’ll use 8000. We can run the command “python manage.py runserver <guest-ip>:8000”. With these settings in mind we can open the port forwarding settings in Virtual Box. We do this by right clicking the network icon and selecting “Network Settings…”

In the Window that pops up, click on the “Port Forwarding” button. In the dialog that appears, create a new rule. Enter the IP and port information collected earlier. After confirming your settings, Windows firewall may say that Virtual Box was blocked by the firewall. Create an exception to allow appropriate access.

**Testing the Settings**

Start the Django development server. Open a browser on the host OS. Change the address to <host-ip>:8080. The request will be routed by Virtual Box to the guest OS. If you see your Django project then the process worked!

**Resources**

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Consider something as simple as a sea shell. In today’s fast paced modern life it can be easy to miss a sea shell. But if we were to pause from the distractions swirling around us we would see that the world is full of beautiful patterns. We see things like symmetry, stripes, tessellations and other patterns when we just look. Today we will focus on patterns that can be described with the help of an idea called fractals.

**Repeated Structures**

A fractal is self similar, meaning that it has similar patterns at large and small scales. This similarity lends it self naturally to mathematical models. Let’s consider a fractal that is built using geometric rules. We can construct a famous fractal called Sierpinski’s Triangle. The rules for constructing this triangle are simple:

- Start with an equilateral triangle
- Break the triangle into four triangles of equal size
- Color the middle triangle
- Repeat step 2 for the three other triangles in the subdivision

Here is what the first four iterations look like:

**Spiral Fractal**

The Fibonacci sequence is constructed using a few simple rules.

- The first term is 0
- The second term is 1
- The third term is equal to the first term plus the second term (1)
- The nth term is equal to the the sum of the (n-1) and (n-2) terms

The first few Fibonacci numbers are 0, 1, 1, 2, 3, 5, 8, 13…. There are a variety of uses for this sequence but we get something special when we use the numbers to draw boxes. We start with a 1×1 square. Then we add another 1×1 square next to it form a 2×1 rectangle. Next we add a 2×2 square to form a 3×2 rectangle. We continue in this fashion adding new squares to form a new rectangle. When we have added a few terms of the sequence we can go back and connect alternating arcs on each square we added. The result looks something like the image to the image below.

It turns out spirals with similar ratios happen all the time in nature. It forms a type of fractal because as you continue the pattern the macro view looks similar to the micro view. To help you see this spiral in more places, please flip through the slide show that follows. Whether it is galaxies, hurricanes, sea shells, broccoli,ram horns or flower seeds, this pattern repeats over and over again.

**Branching Fractal**

Consider a tree that grows and splits into two branches. Each branch in turn splits into two more pieces. If we keep going for a few iterations we will get something that looks like this:

We can add variation to the tree like structures we create by altering the angles and number of each branch. A key break through for exploring fractals came from a theoretical biologist named Aristid Lindenmayer. Lindenmayer created a system that used simple letters to describe the state of a plant’s leaves and branches. That system can be combined with simple rules that change the representation of the system over time. We used simple rules earlier while we explored the Fibonacci set. Our rule was that each value was based on the previous two values.

Since the letters describe the tree, we actually draw the result. Now drawing each branch would be very tedious, but luckily computers are great at doing repetitive math operations. A computer program can be constructed to draw out the equivalent “plant”. For example, they may draw a branch, and then turn 35 degrees and then begin drawing again. These three elements of a simple grammar, simple rules and a drawing program allow for a vast array of fractal creations to be explored. With these techniques it is possible to draw mountains, trees and other natural formations quickly using an algorithm or calculation instead of an elaborate 3D model that captures each facet and face.

**Conclusion**

If we look just a little we will find a wealth of patterns in every aspect of the natural world. We can use simple, repetitive rules to model systems that would otherwise be impossible to model. Fractals present opportunities for both beauty and curiosity. As we begin to understand fractals more and more with computers, we may find that the cure for cancer or a similar world changing discovery to be just a simulation away using fractals.

“Bottomless wonders spring from simple rules… without end”Benoit Mandlebrot

**Handouts**

**Fibonacci Sequence and Fractal Spirals**, Fractal Foundation, http://fractalfoundation.org/fractivities/FibonacciWorksheetAdvanced.pdf**Fractal Triangles**, Fractal Foundation, http://fractalfoundation.org/fractivities/TriangleWorksheet.pdf

**References**

**Patterns in Nature**, Wikipedia, https://en.wikipedia.org/wiki/Patterns_in_nature**Visualize It: Sierpinski Triangle**, Khan Academy program by Charles Cozad, https://www.khanacademy.org/computer-programming/visualize-it-sierpinski-triangle/3208360053**Fibonacci Numbers**, The On-line Encyclopedia of Number Sequences, http://oeis.org/A000045**Fibonacci Number**, Wolfram Math World, http://mathworld.wolfram.com/FibonacciNumber.html**Lindenmayer System**, Wikipedia, https://en.wikipedia.org/wiki/L-system**L-Systems Turtle Graphics Renderer – HTML5 Canvas – by Kevin Roast**, http://www.kevs3d.co.uk/dev/lsystems/

**Videos**

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The three key ideas were

**A slice of pizza is a fraction**- Pizza is a favorite of many children. (and adults!)
- LEGOs also make a great visual for understanding fractions.

**A circle has 360 degrees**- We can extend our pizza analogy by considering a pizza with 360 slices.
- Sports like skate boarding, snow boarding, ice skating and gymnastics in corporate rotations or spinning.
- Kids like to move. Games like duck, duck, GOOSE! can help children understand rotations and movement around a circle.

**Rules determine order**- Many math operations involve understanding and applying rules to reach an outcome. Whether it is multiplying large numbers, adding fractions or using the order of operations in algebra, rule and sequence play an important role.
- A simple way to understand and apply a rule is to line up by different criteria such as height, birthday and last name

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Computers touch nearly every area of life in today’s modern world. Calculations carried out on computers have helped cure diseases, ensure our buildings can withstand amazing forces and entertain us with complex computer animations. Of the numerous ways math relates to computers, we will look specifically at three areas of number systems, robotics and computer animation.

One of the first math skills we master is how to count. Then we learn to manipulate those numbers using various mathematical operations. At the core of a computer is the ability to represent numbers and perform math operations. When we represent numbers we use the digits the 10 symbols 0, 1, 2, 3, 4, 5, 6, 7, 8, 9. We then use a set of rules or an algorithm to express values larger the defined symbols we have. We simply start over at the beginning of the symbols and add a new symbol to the left.

Think of the number 9. When we want to add one more to this quantity we have run out of single symbols to express the new amount. So instead we call it 10. In this way we can think of numbers like an odometer on an old car. When ever the digits for one digit in the number makes a full revolution, the number in the next highest position moves to the next number. Life proceeds as normal and we just think of these symbols as the numbers them selves.

But for a computer to keep track of numbers, using 10 distinct symbols or states to represent a number is problematic. You see, in a general sense the computer is just an electrical circuit. A computer needs to represent numbers using only electricity. We could take a voltage and divide it into ten different regions and call each of them our numbers. But it turns out this is really hard and it is much easier, cheaper and faster to represent only two states, 1 and 0. But can we still count to all the numbers? Sure we can, now each wheel on our odometer will only have two numbers. So we start counting: 0, 1… what now? Well, we apply the same rules we are familiar with. The right most digit rolls around and a new digit is added to the left. Let’s see what happens when we count to 10 in decimal with our new number system.

- 0000 (0)
- 0001 (1)
- 0010 (2)
- 0011 (3)
- 0100 (4)
- 0101 (5)
- 0110 (6)
- 0111 (7)
- 1000 (8)
- 1001 (9)
- 1010 (10)

Well maybe these two digits will work out after all. No writing all of these zeros and ones can get pretty tiring, pretty quickly. There has got to be a way to write things in a more compact form. We could write the numbers as decimal again but then it takes some extra thinking to move things back to binary. What if we could represent each of the 16 patters for four binary numbers using a unique symbol? What would we call 1010? Computer scientists opted to call the number after 9 A. The numbers after A are B,C,D,E,F. Why? Well mostly just because but also because they were familiar symbols that we are used to seeing in ascending order.

Let’s look at the digits that are available in each number system side by side. All of these just give us a symbol to express a value using a set of rules.

The same basic operations we use in decimal can be extended to other number systems. Binary values also open up the possibility of something called Boolean Algebra. Boolean Algebra uses familiar words like AND, OR, NOT and gives them mathematical meaning. As computing evolved important math operations emerged and these were given new names like XOR (Exclusive OR) and NAND (NOT AND) . Lot’s of simple math operations could be chained together to form more complex things like memory and advanced math operations.

As the calculating power of computers grows, they are able to perform ever more complex calculations. Advances in computers also helped scientists and engineers find ways to represent more and more of the physical world as electrical signals. Special circuitry can represent electrical signals as numbers. Once information is in the form of a number the computer can do it’s lightning fast math operations to manipulate the data.

Besides being really fast at math, computers can also store information and execute different instructions based on the results of different calculations. A person programs the computer behave in different ways based on calculations they specify. The final piece of the equation that more circuitry can translate numbers into electrical signals.

With these pieces of translating events in the real world to numbers, memory, logical branching and transfer of numbers to the physical world, we start getting a fairly complex system. We can even do something like check for obstacles and move a wheel forward if no obstacles are found. Combine a lot of these feedback loops together and you get what we know today as a robot.

When we draw something we draw the shapes and colors we see. If we wanted to draw a scene from a different angle we would draw another picture. How does a computer draw something on the screen? Remember that the computer does not see the world the way we do. It only deals in numbers. So we have to represent the thing to be drawn in numbers. For example, we can use the xyz points on a Cartesian coordinate system.

With points in space we can give further information about which points are connected to one another, colors of regions and other properties like how reflective a surface is. A computer can combine all of this numeric information into a model that it can then use to simulate the behavior of light from different vantage points. This whole process may take millions or billions of calculations to produce the colors that represent a view in space. The computer can save a few calculations and thus time by doing quicker calculations that allow certain calculations to be skipped. For example, we do not need to determine the color for the back side of an object that is not visible.

The advantage of having this information in a model the computer can process is that the computer can repeat the same set of calculations from ANY vantage point in the 3D world. And even though millions and billions of things is a mind boggling amount, modern computers can do millions of calculations each SECOND.

We can go even further and use the computer to simulate physics equations, material behaviors and other complex phenomenon. I dabble in this industry my self, but Tony DeRose from Pixar does good job breaking down specific animation principles using math from Middle School and High School.

At the core of a computer we find math. If you wish to create new things in technology it will likely also involve math in some way. Simple math operations have been stacked up to form complex systems that can interact with the physical world and make choices based on those inputs. Computers also use math to simulate the physical objects and calculate how light and various forces would interact with that system over time. This only scratches the surface of the wide variety of things math and computers make available.

**Binary, Hexadecimal and Octal Number Systems**, TI Basic Developer http://tibasicdev.wikidot.com/binandhex**Hour of Code**, code.org https://code.org/learn**Pixar Animation in A Box**, Khan Academy https://www.khanacademy.org/partner-content/pixar

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Imagine you are getting ready for the big game by preparing your delicious dip recipe. Everyone is excited and the guest list is growing by the hour. Your place, with its delicious dip, is the place everyone wants to be. Your recipe is made to serve 8 but now it needs to feed 24. With some simple math you can scale your recipe to meet the demands of your new popularity. Modifying recipes is just one way math can help in the kitchen. In this week’s article we will explore a variety of other ways math impacts our work in the kitchen and the food we eat.

Let’s get back to this dip you are making for the big game. While your made from scratch onion dip is known throughout your neighborhood, it is actually a recipe from Food Network’s Alton Brown. (See the references if you actually want to know how to make it) In the time you have been reading this your Aunt Myrtle had some plans fall through and wants to come over for the game and try this delicious dip everyone has been talking about. Aunt Myrtle also wants to bring her bridge club with her. She knows it is a lot of people but promises to pay for any extra supplies needed for such a large group. Now your party is up to 40 people.

You might say well, I have five times as many guests as I planned, so I can just multiply all of the ingredients by 5. And then you look at the recipe and see that most of the ingredients are expressed as fractions. 1/2 teaspoon of this, 1 and 1/2 cups of that. Fractions can give people trouble well into adulthood so let’s break down what we need to do.

The first thing we need to remember is that any number can be expressed as a fraction. 5 is the same as 5/1.

Second, we can remember some rules for multiplying two fractions. We multiply the numbers on top and that becomes the new top. We multiply the numbers on bottom and it becomes the new bottom.Numbers like 1 and 1/2 we might need to change into a fraction like 3/2 so we can do the same operation on everything.

So 1/2 teaspoon becomes 5/2 teaspoons and 1 and 1/2 cups becomes 15/2 cups. Now these numbers look rather strange. This is because we usually use whole numbers with a remainder when expressing fractions, just like we did with 1 and 1/2 cups earlier. 5/2 teaspoons becomes 2 and 1/2 teaspoons and 15/2 cups becomes 7 and 1/2 cups.

It is the next day after your massive party. Your math skills save the day and let you remain the king of dip. You and your family get a sweet tooth and want to make cookies. You pull out grandma’s old recipe and then you realize the her recipe makes six dozen cookies. That is just way too many cookies for your family of three. So instead of six dozen, three dozen might be more appropriate. (you will have enough to share with your mechanic Marvin and your florist Fern)

Just as we can multiply recipes to make them serve more people, we can also divide them to serve fewer people. As long as the proportion or ratio of each ingredient is the same we can reduce or expand our recipe.

Let’s look at our process again. We’ll express numbers 1 and 1/4 cups sugar as 5/4 cups sugar. We will still multiply, but this time we will multiply by 1/2, which is the same as dividing by 2. We get a new value of 5/8 cups sugar or a little more than half a cup.

After your foray in crazy dip production and sweet baking success, time passes and you just stick to exact recipes to avoid any extra math in your life. Then Thanksgiving lands in your lap. Aunt Myrtle called again. She will be coming over to celebrate Thanksgiving with you and your family. We are not sure why Aunt Myrtle always insists on inviting her self over, but it works out well for our discussion. Aunt Myrtle lives for tradition and she will expect a turkey with all of the fixings. So you go to the store and buy a 13 pound frozen turkey a week before Thanksgiving. You’ve cooked dip and cookies before, how hard can a turkey be?

Lucky for you, you read the label and see the turkey people say the turkey needs to thaw 24 hours in the refrigerator for every 5 pounds. You realize you’ll have to start prepping for this meal three days before you need to cook it!

As the big day arrives you answer the fifth call this week from Aunt Myrtle. Aunt Myrtle’s last call was to remind you that she doesn’t like the generic brand of cranberry sauce and that dinner should be at 3:00 PM for tradition sake. You look back at the turkey directions and realize the cooking time is based on the size of the turkey. The labels says 20 minutes per pound at 350 degrees Fahrenheit. You get out a pencil. 13 pounds times 20, 260 minutes. There are sixty minutes in an hour so it is going to take 4 hours and 20 minutes for the turkey to cook! You work backwards and you figure out you need to get the turkey in the oven by 10:30 on Thanksgiving morning. You do similar calculations and form a plan for when the potatoes, stuffing and green bean casserole need to go in. The meal is a success and Aunt Myrtle approves of your meal offerings, even if you didn’t have enough sense to get a hair cut before she arrived.

You begin to doze on the couch anticipating Aunt Myrtle will soon depart now that dinner has completed. Aunt Myrtle tells you that it is just too dark outside for her to be driving and insists she stay at your house over night. As you prepare the guest room you see that Aunt Myrtle is lugging a suitcase from the trunk of her Cadillac. You start to ponder how convenient it is for her to have an overnight bag with her but decide to let it go.

Later that night your stomach is grumbling so you decide to get another piece of pie. “Who eats dinner at 3:00 PM? 8:30 rolls around and it is like you never ate dinner” you mumble to your self. As you are standing at the fridge enjoying your pie, Aunt Myrtle startles you as you suddenly see her illuminated by the light of the refrigerator. She is just standing there in her full length night gown and curlers. Then she says to you “More pie? My dear, you are really starting to fill in that sweater. Would you like me to make you a new one?” You pause to process what she said. “Did she really just say that?” you think to yourself. But then you wipe the meringue off your chin and put the drumstick down and ponder her words. While she lacks tact, and general control of her gas, she may have a point. So the next day you start an exercise plan to shed those pounds.

You look up on the internet that one pound of fat equals 3500 calories. You also read that safe weight loss is about 1-2 pounds a week. You cooked a 13 pound turkey, how hard could losing a single pound be? You walk each day in the week for thirty minutes. Some more research tells you that someone your size burns 200 calories by walking for 30 minutes. You multiply it out and figure you burned 1400 calories this week. You were on track with your diet but there was the one time you slipped and ate one brownie, well one ROW of brownies for 500 calories. You run the numbers and find that you only burned an extra 900 calories that week. The amount is not even half a pound. You use your improved math skills to make better choices in the coming weeks and make progress on your goals. With all of this new health surge you even find the energy to paint your house a different color. Aunt Myrtle ends up not being able to find your house for a good six months. Six. Blissful. Months.

Even if you don’t have an Aunt Myrtle in your life, you can use math to tackle different problems with cooking and food. You can use math to increase the number of servings, decrease the number of servings, plan cooking tasks and to understand the impacts of diet and exercise. Check out the references and videos below to keep learning.

- Onion Dip From Scratch by Alton Brown http://www.foodnetwork.com/recipes/alton-brown/onion-dip-from-scratch-recipe.html
- Soft and Chewy Chocolate Chip Cookie Recipe http://www.food.com/recipe/soft-and-chewy-chocolate-chip-cookies-48356
*Cooking with Math*on Math Central from the University of Regina http://mathcentral.uregina.ca/beyond/articles/Cooking/Cooking1.html- Real Life Math | Chef http://www.pbslearningmedia.org/resource/mkaet.math.rp.chef/real-life-math-chef/

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In this installment we are examining the various math topics around money. Now money in general is an extremely broad topic that has a vast amount of theory and entire professions dedicated to different aspects of money (accountants, book keepers, loan officers, bank employees, etc.) Our discussion will focus on basics essential for young people to get a foothold and see a few different simple math uses in action. We’ll cover what money is, income and expenses.

Before we talk about money we should understand what money or currency is. In a general sense, money or currency is made up. But one can touch it and hold it, how can it be made up? Money is made up in the sense that money is merely a social contract that a group has decided on. A value is assigned that maps goods to currency. Once this value is agreed upon, commerce, or an exchange of goods, proceeds from there. You can have commerce without money by simply trading item for item. This is called bartering.

Bartering is simple to visualize. If one person raises chickens and another person raises pigs, they can trade each other. Say the chicken farmer agrees to trade 5 chickens for 1 pig. They make the exchange and enjoy the bounty of their new trade. This works out well because the pig farmer has pigs and wants chickens while the chicken farmer has chickens and wants pigs. This simple system of trading begins to break down under a few different scenarios.

**Storage**

Pigs have a season. They take a certain amount of time and care before they are ready to sell. After a certain period of time they become extremely large and it takes excessive resources to feed them. Very old pigs may lose their savor and not be as good for consumption. So there is a time frame when it makes sense to sell the pig. But what if the pig farmer does not need chicken at that time? What if no chickens are ready for trade? How does the pig farmer eat chicken when it is not the right time to sell the pigs? The farmers certainly could agree to have a delay in their exchange. An arrangement like: I will give you a pig now for chicken later. They could also make preservation efforts like curing a ham for future sell, etc. But all of these things take time. Money allows the farmers find a buyer during the appropriate season and use currency to purchase things later when they have no goods for sale.

**Fractional Amounts**

Related to the problem of storage is fractional amounts. What if the chicken farmer can only part with three of his chickens right now? Does the pig farmer give him 3/5 of a pig and keep the rest? In this example this division may actually be possible. The chicken farmer could trade for just the most desirable portions of the pig. But what about the other way around? The pig farmer has only one pig to trade and he needs 2 chickens and some and milk. He might still be able to divide up the cuts of meat but what if the dairy and the chicken farm are far apart and transporting the divided product before it spoils is difficult? Now there are certainly ways around this. The pig farmer could hire a helper (but what would he pay the helper in, pigs too?) or agree to meet at a central place, but things get complicated really fast. Currency can solve this problem by allowing the chicken farmer to transform his goods (chickens) into currency over time. Perhaps the farmer can sell three chickens for $3 now and use $2 from a previous chicken exchange to fund his pig purchase. In the same line of thinking the pig farmer can sell his pig for $5 and pick up chickens when he is that area and milk the next day when he travels to the other part of the region.

**No Direct Exchange**

Consider a third party who makes lantern oil. Both the pig and chicken farmers need the oil to light their homes. The chicken farmer has chicken to offer for oil and the pig farmer has pigs to offer for oil. But the oil maker isn’t very fond of meat and prefers to eat fresh vegetables. Now they certainly could find another farmer who grows vegetables but things can get complicated. Say the vegetable farmer prefers chicken over pork. The pig farmer could certainly trade a pig for some chickens, chickens for vegetables and vegetables for lantern oil. But this whole exchange takes time to coordinate and execute. On the other hand, if this area has an agreement on a currency, the pig farmer can sell to an interested buyer for money and buy goods from the lantern oil maker directly. The oil maker can then use the money to buy as many fresh salads as he wants directly from the vegetable farmer.

**Desirable Properties of Money**

If we can all agree that this piece of paper or that piece of metal has some value, then money or currency is formed. Currency solves a problem by being easy to store, easy to break into pieces and easy to exchange among different parties. But, as we will see, this invention can also introduce different problems like stress and debt.

Now that we have this common form of exchange called money, we need some way to acquire this resource to exchange for things we need and want. Acquiring money is called income. In the most general sense, income is the result of exchanging something you have with someone who wants what you have, for money. Some common things we trade are time, energy, knowledge, and resources.

Time, energy and knowledge are common things people do in jobs to make income. A home owner might pay someone with a lot of strength to dig a ditch. An employer might pay someone to deliver fliers to advertise a business while they stay in the office to handle calls. Another person might get paid to help someone who is injured feel better. There are as many jobs as there are kinds of people.

Our farmers discussed earlier were exchanging resources they had developed over time. A computer chip maker might make a computer part and sell it to interested parties. A person who has a home or property may rent the location (allow others to occupy the space) in exchange for money.As with jobs, there are as many types of resources that can be gathered and exchanged for income as there are kinds of people.

Let’s look at a few different calculations we can do with Income

**Wage over Different Time Periods**

In the case of a job, some amount of money is exchanged for some result or time. An employer might say a job is $10 an hour and another is $50,000 a year. Translating these numbers between different time frames like $/hour, $/month and $/year can be important for different contexts. Just as we did with our sports discussion, we can use simple math to move from one set of units to another. Some key things to consider:

- While there are 356 days in the year, a person is unlikely to work each and every one of those days. So we need to consider how many days in a given year will be worked.
- The number of hours a person can work is determined by budgets, labor laws and the bounds of human energy. So while there may be 24 hours in a day, you may only be eligible for pay during 8 of them.
- Gross income is different than net income. We will talk about taxes in the expense section, but in short, in most regions there is some amount of money that never hits your pocket. It is taken out in the form of taxes. Net income is how much you actually have at the end of the day.

Moving from an hourly rate to a gross yearly rate looks like the following:

Similarly we can move from from a gross yearly rate to an hourly rate as follows:

**Profit Margin**

When goods are sold the seller tries to make a profit. That is to say they wish to bring in more money than they spent to make the item. When the seller spends more money than they bring in that is called a loss. If they neither make money nor lose money it is called a wash. Profits are important because they insulate against future loses. A business or individual who is selling things will often want to calculate how much income they are producing compared to how much they are spending. A profit margin is a ratio of profits to total sales

Let’s consider a girl named Suzie. Suzie 7 years old but she has studied all her life on how to make delicious baked goods. She wants to open a small stand to sell her cookie marvel, Suzie’s Scrumptious Sugar Cookies. Suzie is also a smart business women. She sat down and calculated all of her costs, everything from flour, sugar, to how much gas it takes to run the oven and energy to cool the house after a long day of baking. She estimates each cookie to cost $0.75 to make. She decides to sell each cookie for $1. Her first day goes great and she sells all 100 of the cookies she baked. Let’s calculate her profit margin.

- Suzie spent $75 to make the cookies
- Suzie took in $100 in sales
- Suzie’s net result was $25 in profit

25/100 gives us a value of .25 or 25%. Suzie has a very healthy profit margin of 25%. A few weeks of good margins like this and Suzie will have the capitol to add new cookies or expand her operations to other neighborhoods.

**Importance of Choices**

Whatever way one decides to generate income, there are a series of choices that lead up to the options that are available. Some choices include

- Self Improvement Efforts
- Time management
- Resource Management
- Relationships

Each of these choices may lead to more or less income opportunities. For example, the choice to study a difficult subject while others party may open up many profitable career paths not available to others. Making a good investment might lead to additional income opportunities while a bad or poorly thought out investment might remove income opportunities.

These choices and many more will add together. The following graphic helps to illustrate decisions we can make in what we do with our time:

Expenses are simply money that you have to payout. It might be for a good you need but don’t have, it might be for something you can’t do or it might be part of a social agreement you made. We will limit this discussion to two expenses that might be confusing or new.

**Taxes**

A tax is an expense required of a person, usually by some larger entity like a city, state or federal government. Taxes are expressed as a percentage of an amount or a fixed value. It might be a percentage of a person’s income, percentage of a sales price or a bridge toll. Taxes are not always called taxes. Sometimes they are called fees, tariffs, duties, tolls, etc. but they mostly behave in a similar way by requiring an expense by some party. Taxes are generally collected with the stated purpose that the individual benefits from some benefit available to all. For example, a person might pay a gas tax when they fill up their car and that tax might be used to build and repair roads. Taxes make a lot of adults pretty heated and there are a lot of active discussions on this topic each day all across the world. People discuss who should be taxed, what should be done with the money, and what amount to tax. This post is not a political post so we we will just talk about the math.

Let’s revisit our two workers from the income section. One made $20,000 a year and the other made $50,000 a year. The United States currently has a variable tax rate that is determined by a complex set of calculations. We’ll leave those complexities to the accountants and just use their gross income without any modifiers to determine a tax from a tax table. We can use these numbers to determine an effective tax rate

If you are still following along, it is important to note these are only federal taxes and there may be many more types of taxes taken on a pay check before it makes it to the earner. Another thing we can do with this is we can revisit the calculations for hourly wage to figure out how much people really make when taxes are factored in:

**Interest**

When discussing interest, it is important to ponder: What do banks sell? An initial response might be that a bank does not sell anything. They just hold your money right? That would not be an accurate observation. A bank collects depositor’s funds and sells them to other people in the form of loans. To say differently, the bank sells money today for more money tomorrow. The increase the bank collects is called interest. Interest can come in the form of a fixed percentage or a value that changes over time.

Simple interest just applies the percentage to the loan. So if you borrowed $1,000 today and agreed to pay 5% simple interest 1 month from now, you would have to pay back $1,050 once the month passes.

Many loans however, do not have simple interest. Instead the interest compounds over time. What this means is that a given interest calculation includes previous interest values. Consider this thought experiment. You start with $1. The you add 10% to that and call it the new value. The you repeat again and again. The first 10 entries would look like:

Now let’s look at that over 100 cycles, this time with just the graph:

Imagine for a second that the one dollar in the example was a pack of gum that was put on a credit card. Imagine that credit card had a modest interest rate (for credit cards of 10%) and that the credit card was was forgotten for a little over 8 years. Through compounding interest thousands of dollars would be due. Now this scenario is a bit contrived because a credit card would have a limit and the company would expect payment well before the balance reached this amount, but it does show what compounding interest can do over time.

Speaking of minimum payments, credit card companies will often lure unsuspecting card users with a “minimum payment”. What they do not disclose is that the minimum payment will often be just barely above the interest fee. So each month that goes by the balance is only reduced by a small fraction. This can cause some cards to take up to 30 years to payoff!

Credit lines, such as credit cards are not intrinsically evil. They can be a great help when used appropriately. For example, they can help businesses with cash flow problems who have money but do not have it at the times their debtors need to be paid. Credit can also help with large purchases like cars, houses or education that are important but would otherwise be unobtainable. But the compounding interest of credit cards means that it is very easy to get trapped by the weight of debt. Care must be taken where the terms can be met without spiraling costs.

Loans and complex debt scenarios are often tackled best with the assistance of computers. A computer spread sheet or other software can be configured to evaluate thousands of tedious calculations and determine different outcomes. In the resources section a few different examples are provided for exploration.

We can now close our discussion on Money. We learned a little about why currency systems emerged over trading systems. We also learned a little bit about what income is ad a few simple calculations related to hourly wages and profit margins. Finally, we learned about two types of expenses called taxes and interest. In the references below there are more detailed exercises to practice math in these areas.

- http://ca.pbslearningmedia.org/resource/mkqed-math-rp-creditcards/the-math-of-credit-cards/
- http://www.vertex42.com/Calculators/debt-reduction-calculator.html
- http://debtgraph.jacobgable.com/

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**Basic Concepts**

**Units of Measure**- We measure distances in units like feet and meters and time in units like seconds and minutes. This information helps us understand scale and scope of a numerical value.
- For example: I walked 50 meters or I waited for 30 minutes.

**Average**- Also called the arithmetic mean, an average is a simple statistic that gives a general idea of where a set of values are centered.
- For example, the height of the average man in the US is 5’10”. Some people will be taller and some shorter but many adult males will be about 5′ 10″ in the US.

**The World’s Fastest Man**

Usain Bolt of Jamaica has demonstrated amazing athletic ability in the sprint events of track and field. One memorable event featured in the video is a world record 9.58 second performance in the 100 meter dash. You can watch the video and get a sense of how his performance compares to other world class athletes, but it is hard to get a sense of how fast this actually is. Perhaps we could transform the units of meters/second to something more familiar like miles/hour.

To do that we will need to do a process called unit conversions. A few facts will help in our conversion calculation:

- 60 seconds = 1 minute
- 60 minutes = 1 hour
- 3.2 feet = 1 meter
- 1 mile = 5280 feet

Note that we can move the right side to the left or the left side to the right and the value of the fraction will be the same (e.g. a form of one). The calculation to convert the unit looks like so:

We can cancel out units of the same type. We show cancellation by putting a line through the unit. For clarity we made the color for each unit unique. Cancellation looks like so:

After cancellation the computation looks like:

Completing this calculation we can see that Usain bolt covered as much ground in 9.58 seconds as a car traveling at 23.3 miles/hour would cover. This means that in some jurisdictions, Mr. Bolt runs so fast he could get a speeding ticket in a school zone!

**Going the Distance**

A race for Usain Bolt is over before you can finish a commercial. How about distance runners? What type of speed can long distance athletes achieve? For this question we will consider the athletic feats of Bennisa Bekele of Ethiopia. Mr. Bekele is the world record holder in the 10,000 meter race with a time of 26:17.53.

We can do the same type of calculation we did for Mr. Bolt’s race to determine a speed in miles per hour. We’ll go a little faster since we have already covered the calculation in detail.

First, let’s express 26:17.53 in seconds. There are 1560 seconds in 26 minutes. That gives us 1577.53 seconds in 26:17.53

With this number we can see that a distance runner has about a 40% drop in speed but a 100x increase in distance. Even with this information, one may still not be able to appreciate just how fast this world record holder is going. A more common way to think of pacing in the time to complete one mile. For example a student in a exercise class might record a “mile time” that they would improve upon during a year. In terms of units this means we want time/distance, or specifically seconds per mile. This means we want the inverse of the value we calculated.

The calculation changes to:

This means the world record holder has nearly a 4 minute mile pace for the duration of the race. Bennisa Bekele can run a full mile in just about the time it takes to boil an egg.

With some simple math we can transform sports outcomes into familiar units of measurement.

**The Sultan of Swat**

The pace and flow of baseball allow ample opportunities to capture a wide variety of statistics. One of baseball’s most famous players was Babe Ruth. Dubbed the “Great Bambino” and “The Sultan of Swat”, Ruth had a storied career of ups and downs that included many championships and records that are still in place.

Of the many statistics gathered in baseball, a batting average is a common measure of how skilled a batter is at connecting with the ball. A batting average is calculated by dividing the number of hits by the the number of at bats or attempts by a player. The batting average represents the probability or chance that a hitter will connect when they face a pitcher.

Babe Ruth had 8,399 at bats over his 22 year career. Of those at bats, he had 2,873 hits. With these numbers we can calculate his batting average over his entire career as (2,873 hits)/(8,399 at bats). This means Ruth had a batting average of .342. Now if a student came home from school and presented a grade of 34.2%, they would surely be scolded by their parents. But in the game of baseball, where it is pitcher vs. batter and there are a myriad of choices playing out each moment, connecting 34.2% of the time is pretty remarkable. This can be approximated to say that Ruth got a hit every three times he made an attempt.

**The Cyclone**

Another great player in baseball history was Cy Young. Cy was short for “Cyclone, which was a nick name given to Young during his first try out as a professional baseball player. The speed of his fastball had damaged the grandstands to the point that it looked like a cyclone had occurred. The Cyclone name stuck and Cy Young went on to have a long career as a pitcher. Cy Young established many records, some of which still exist today. Cy Young’s name was given to an award that recognizes pitching excellence in Major League Baseball.

While hitters are measured by how many times they can connect with a pitch, pitchers are measured by how few runs they allow. This statistic is called an earned run average or ERA. Like a score in golf, a player aims to have a low ERA. A lower ERA means fewer runs are scored while a pitcher plays. The ERA as a statistic is calculated by taking the proportion of runs allowed to innings pitched multiplied by nine. This scaling to a full game of nine innings makes it possible to compare pitchers who may pitch a variable amount of innings over each game in a season.

Over the 22 years that Cy Young played, he pitched 7,356 innings. In those innings a total of 2,147 runs were earned. The value of 2,147/7,356 can be scaled by 9 to give a career ERA of 2.63. While there have been pitchers with lower career ERAs, no one can match the number of inning pitched by Young.

Using simple math we can get an idea of the long term performance of these legends and appreciate their accomplishments.

**Counting Games**

Counting is learned at such an early age that we may not even think of it when we think of “math”. But counting plays a key role in score keeping for a variety of sports. Games with variable scoring events introduce a element of strategy to optimize efforts for the best reward. While this can be an important or even interesting part of a game like basketball or football, score optimization can also have startling outcomes when it is applied to tournament play.

Many sports have tournament style play where advancement depends on the outcome of a number or games played within a small group. For example, the world cup has pool play that determines how the rest of the tournament unfolds. Tournament organizers must however be careful with how they structure tournament scoring. It is possible to create a scenario where the best long term outcome is to LOSE in the short term. This may sound confusing, isn’t the point of playing a game to WIN? How would losing offer any kind of advantage?

This very scenario played out in great prominence during the London 2012 Olympics in the sport of Badminton. Several team had already secured positions in the next round and winners would face higher ranked players sooner in the knockout rounds. Since teams wanted to be more likely to advance to a medal round, they attempted to lose on purpose to secure an easier match up. The full details are included in the references. The ethics of losing on purpose is sure to be a topic that will be debated for years to come.

Even a simple math principle like counting plays a key role in selecting a strategy for a given game.

**Conclusion**

Ultimately, success in sports is determined by time spent in the weight room and on the field playing. We can however use math to appreciate and understand sports in greater depth.

**References**

**Babe Ruth Career Statistics**http://www.baseball-almanac.com/players/player.php?p=ruthba01**Cy Young Player Career Statistics**http://www.baseball-almanac.com/players/player.php?p=youngcy01**CNN Coverage on Badminton Controversy**http://www.cnn.com/2012/08/01/sport/olympics-badminton-scandal/**Yahoo Sports Article on Badminton Controversy**http://sports.yahoo.com/news/olympics–badminton-tournament-marred-by-teams-trying-to-purposefully-lose-a-match.html

**Videos**

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Casinos represent a mind boggling concentration of resources. It is not uncommon for casinos to be vast structures with hundreds of employees, restaurants, shopping , hotels, lavish finishes, advanced technology and extensive areas for gambling activities. All of these things are concentrated in the most unlikely of places, in a desert landscape where the blazing sun is plentiful and water is sparse. Under normal circumstances populations grow around areas high in resources like places where food can grow easily or that have access to large bodies of water. The casino hubs though, especially those in arid places like Nevada, grew because the business of gambling is extremely lucrative. The business is so lucrative that these companies can even build modern day castles in the desert.

**The House Always Wins**

The first thing to consider when looking at the math of gambling is the idea that the house always wins. The house, or the establishment that hosts the gambling activities, does not win every bet. There are times where individuals win both small and large sums of money. What we mean by the house always wins is that in the long term, over many, many betting transactions, the house is mathematically destined to win. For each winner there are many more losers. If the house always wins in the long run, you might ask: How often does the house win and by how much?

We’ll use a few concepts from an area of math called probability to gain an idea on how to answer that question. We’ll just scratch the surface, but it will give you an idea on how to learn more.

**Basic Concepts**

**Randomness**- Things happen without an order or predictable pattern

**Experiment**- An experiment is when we do a random act to get an outcome. So we might roll a dice to see which number appears.

**Event**- The result of an experiment. In the dice rolling example we might roll a three.

**Sample Space**- All of the possible outcomes or events. A cube shaped dice has six possible outcomes.

**Probability**- The chance something will happen. Usually expressed as a fraction. The probability of all events in a sample space adds up to 1. I have a one in six chance that a three will be rolled on a dice

**Independent Events**- Events are independent if they do not influence one another. Each time I roll a dice it does not matter what has been rolled before.

**Dependent Events**- Events are dependent if they influence one another. If I draw a card and do not replace it in the deck, then I can’t draw that card again. Specifically, if I had 10 cards and removed one, the next time I drew a card there would only be nine cards to choose from.

**One Dice**

Let’s think about one dice. How many ways are there to roll the dice? A cube has 6 sides so there are six ways to roll one dice.

**Two Dice**

What about if we roll two dice? Well there are 6 ways to roll the first dice and six ways to roll the second. The first conceptual challenge here is how do we count the events in the sample space? It is always easier to use real numbers so let’s consider that we roll 1 on the first dice. How many ways can the second dice be rolled? (6) We can repeat the thought experiment by rolling a 2 first, then a three first etc. We get something that looks like 6+6+6+6+6+6 or 6*6. We can also visualize this by organizing the outcomes in a table.

We can go further and look at how many times each sum appears in the table. We can use this information to determine the probability for each sum. For example a sum of two can be formed exactly one way (by rolling two ones) in all 36 combinations. Therefore the probability of the dice adding up to 2 is 1/36. The full distribution looks like this:

**Craps**

Craps is a gambling game where participants place bets on the results of rolling two dice. The rules of the game are as follows:

- The player (known as the shooter) rolls a pair of fair dice
- If the sum is 7 or 11 on the first throw, the shooter wins; this event is called a natural.
- If the sum is 2, 3, or 12 on the first throw, the shooter loses; this event is called craps.
- If the sum is 4, 5, 6, 8, 9, or 10 on the first throw, this number becomes the shooter’s point. The shooter continues rolling the dice until either she rolls the point again (in which case she wins) or rolls a 7 (in which case she loses).

There are a wide variety of bets that relate to these activities. The purpose of this article is not to encourage gambling or explain the intricacies of the activity so we’ll only scratch the surface of this game. In fact the goal of this article is to help you understand how much a gambler can stand to lose in the long run.

Consider the case of winning on the first throw. There are 6 ways to roll a seven and two ways to roll an eleven. This means there are eight ways out of 36 to have a winning outcome. We can pair this information with two related bets on this outcome

The seven bet pays out 4:1. So if a dollar is bet, the player nets $4 otherwise he loses his dollar. The gambler will win one in six tries in the long run or 16.7% of the time. So if the gambler places 1,000 one dollar bets he will win back $668 (167 * $4). However he will lose $833 (833 * $1) This means over the long run he walks out $165 poorer.

The eleven bet pays out 15:1. So if a dollar is bet, the player nets $15 otherwise he loses his dollar. Similar to the 7 bet calculation , the player has a 5.6% chance of an 11 bet succeeding. If he places 1,000 one dollar bets, he will win back $840 (56 * $15) and lose $944 (944 * $1). The means over the long run he walks out $104 poorer.

In both of the previous cases the house was the long term winner. Even though the player may feel like they are winning at some points in time, over many betting cycles the house amasses a large influx of cash. The house’s winnings are always net positive in the long run and the player’s are always net negative.

We can use the simulator in the references below to gather the long term results of all craps bet types for our 1,000 one dollar bet scenario. Any way you go you will walk out poorer over the long run.

Further analysis can be done on other games of chance. The outcomes are similar with the house winning in all scenarios over the long run. Some games like Black Jack provide the house a smaller edge allowing for skilled players to reap rewards. One can even observe the flow of the game and use probability to make large bets when the hands left in the deck are in the player’s favor. This is a method called card counting. This can be multiplied by having multiple players gathering information on the deck. However this practice, known as team play, is prohibited and casinos will quickly escort out or take action against players found doing it.

Just such a scenario went down when a group of MIT students devised a plan to do team play against single deck Black Jack and reap huge winnings. Their exploits are detailed in the book “Bringing Down the House”. Casinos quickly caught on to their tactics and black listed them from playing. Outside of the US the young students faced threats of physical violence when they tried to employ their tactics.

While one could argue that individuals who counted solo without the help of a team were just being good players and mastering the game, the casinos were not in the business of losing money. They quickly adjusted their games of chance to include multiple decks. This nullified the counting advantages that single decks offered. Building castles in the desert is an expensive venture and the house is going to do everything in their power to ensure that they keep winning in the long run.

So the next time you see a grand structure where there would normally not be one, think a little about why resources are concentrating there. Math is a tool that can help you solve this riddle.

**Handouts**

- All Possible Outcomes of Rolling Two Dice
- Probability Distribution of Rolling Two Dice

**References**

**Probability, Mathematical Statistics, Stochastic Processes**,**Chapter 12: Games of Chance**, University of Alabama Huntsville, http://www.math.uah.edu/stat/games/**Math of the Game of Craps***Bringing Down the House: The Inside Story of Six M.I.T. Students Who Took Vegas for Millions*http://www.amazon.com/Bringing-Down-House-Students-Millions/dp/B001AQY05Y

**Videos**

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Have you ever had software work on your machine and not work on a different machine? Missing dependencies is a common cause of software that works in one environment and not in another. Modern software is most often a tapestry of libraries and frameworks that must be present on a machine to function properly. Even the simple “Hello World” programs that are used so frequently to introduce programming languages require additional libraries to run outside of a development environment.

**Windows Environments: Dependency Walker**

Dependency Walker (depends.exe) is a tool that has been around for many generations of Microsoft windows. This tool is your basic tool for diagnosing Windows dependency problems in the field.

**Unix Like Environments: ldd**

ldd is a shell tool used to list dynamic dependencies (shared object files). This is your basic tool for diagnosing dependency problems in unix like environments.

**Resolving Dependency Errors**

**Why is the dependency required?**

Sometimes project templates for ISEs can incorporate common dependencies that you may not need for your specific application. Always determine why a dependency is needed. You should be able to account for every library and framework your application requires. This knowledge may also extend to the dependencies of your dependencies and so forth. While this process of tracing dependencies can be tedious, it can teach you a lot about the frameworks you use and the operating systems you distribute on. In simple terms, don’t carry any more dependencies than necessary. Each dependency is a potential vector for bugs and vulnerabilities.

**Is your application built correctly?**

Some operating systems (i.e. Windows) distinguish between debug and release libraries. There will often be restrictions on distributing debug libraries. Debug libraries are often associate with the developer’s machine only. The QT framework on windows is a perfect example of this. Applications linked for debug link to QT libraries with ‘d’ prefix (qt5cored, qt5guid, qt5networkd, etc.) This is case where something working on a developer machine and not on another machine is expected behavior.

**Can static linking help your problem?**

Some languages, such as C++, allow dependencies to be completely pulled into an executable at compile time. This means that the operating system does not need to resolve the dependency at run time because everything is already in the executable. The downside of static linking is that executable sizes increase and dependency updates require an entirely new application to be published. This had helped me in the past to incorporate Boost program options into an application. Static linking is not only language dependent, but also conditional on your licensing situation. Static linking to certain GPL works can cause the linking application to become a derivative of the GPL work and force the linking application to comply with the GPL terms. Consult appropriate legal and technical council for more information on this advanced topic.

**Can you detect when the dependency is not met?**

One common approach to dependency resolution is to check that prerequisites are met before allowing the application to be used. Visual Studio is a prime example of this approach. Visual Studio requires a number of companion technologies to be installed before the application can be installed. This does not prevent future problems because a user can uninstall still remove a prerequisite at a later time but it does set a nice baseline for what the publisher expected the system state to be.

**Would setting minimum system requirements help?**

Sometimes large sets of dependent files are distributed as a single update. An example of this would be service packs for Microsoft operating systems or names versions on Mac OSX (Yosemite, Snow Leopard, Mountain Lion, etc.) Requiring a specific update set can be an easy way to ensure dependencies are met. For example, when a minimum version of the .NET frame work is required.

**Are you future proof?**

Libraries change. Sometimes the way your software is written can cause unnecessary coupling between your application and the specific version of a library. My work supporting applications on Ubuntu has highlighted this idea. At some point in the life the software specific library versions get referenced. When transitions occur between 10.04 ->12.04, 12.04 -> 13.04 and 12.04->14.04 the default distribution for a library is based lined at a newer version. The older version are simply not present in the canonical package repositories. Sometimes members of the community post back borts for commonly used libraries but there is no guarantee this will be the case.

**How Should the dependency be resolved?**

Should you distribute the dynamic library or shared object file with your application? Should you rely on a different installer or updater to put the files there? How you answer these questions depends on the technology being used. Software is generally licensed, not sold. Software licensing dictates the terms that the software can be used and distributed. License restrictions may forbid the component from being installed by a third party. Others may all distribution as long as attribution is made. Some operating systems forbid or discourage the distribution of key system components. For example, it would be inappropriate to distribute a component that is normally updated through Windows Update. In some instances it may be appropriate to rely on a different installer to add and remove a component. The OpenSSL libraries are a good example of this. Every piece of software on the planet has bugs, including mission critical security software. Once you take ownership of distributing a library you are also on the hook for distributing all future security updates. If you don’t do this your software can either be disabled by system administrators or used as an attack vector against flawed software.

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Do you ever wish you had a time machine? Maybe you would like to see ancient history first hand or re-live an important decision in your life? While we can’t travel through time and space, we can achieve a close second in our technical work using source control. Source control is kind of like a time machine for your plain text files.

A simple form of source control could work like the following:

- Do some work in an electronic document
- Save the file off with with a unique name at a given point
- Repeat steps 1 and 2 until the work is complete

This model works well for a small project with a single author. But this approach becomes problematic when different circumstances emerge such as

- Multiple authors are contributing work
- Two or more parallel works need to be merged into one work
- There are lots of files that need to be tracked
- Additional meta data is needed such as author, time and change notes

When one or more of these conditions emerge it becomes appropriate to utilize source control software. As is true with many universal problems in the software industry, the problem of tracking revisions has been solved with many different tools over time. As a frame of reference I have directly or indirectly dealt with seven different source control systems over the course of 14 years. A thorough comparison of source control systems can be found here: http://en.wikipedia.org/wiki/Comparison_of_revision_control_software As with other articles in this series we will focus more on the factors to determine the right tool and less on any one solution.

**Factors to Consider When Picking a Source Control Tool**

**What file types are being stored?**

Most often source control systems focus on the task of versioning plain text (i.e. code and code like artifacts). They frequently do this using a difference concept where the changes from one version the next are captured. This also means that while some solutions are great at tracking plain text changes, they can also be terrible at tracking “binary” files such as images and office documents. If you are working with binary files, source control systems might not be a good choice

**What is your environment?**

One of the reasons why there are so many source control solutions is because there are so many ways to make software. Your environment might include one or more operating systems, official and unofficial IDEs of the team, and graphical vs. terminal workflows. For example, if you are using a Visual Studio based work flow in a Windows environment, Team Foundation Server may be a natural fit because it is seamlessly integrated with specific versions of Visual Studio. On the other hand if you have have a mix of Windows, Mac and Linux hackers you might want to consider a Git solution paired with visual clients like gitk.

**What are your resources?**

Some of the popular source control solutions have a price tag associated with them. Even “free” software can have a cost when paired with cloud services with a prime example being private repositories on GitHub. Different solutions may also require varying levels of infrastructure. Do you have a person who knows how to setup a server securely or setup a database? This infrastructure also needs maintenance over time to ensure availability, performance, and security.

**What does the team prefer?**

Developer productivity is an essential element in delivering a quality product. Productivity and morale will suffer a developer has to learn a complicated system or constantly fight a tool chain. Developers and other content creators should have a major say in the tools they are required to use. It is true that most developers like learning new things, but introducing too many new tools or technologies cripples a teams ability to craft new solutions. Keep the number of completely new tools and technology to one or two if you want to have any hope of making your schedule projections.

**Common Workflows to Master**

Regardless of which tool is selected as the right answer, team members will need to master a few common work scenarios. These skills are essential and should not be schlepped off to peers. Address avoidance of these tasks immediately because they could be:

- An indicator that more hands on training is required
- An indicator that the wrong source control solution was selected
- An indicator that corrective action and coaching is needed at an individual level

**Universal Source Control Tasks**

- Add a file or files to source control
- Remove a file or files from source control
- Obtain the newest version of a file or files
- Obtain a specific version of a file or files
- View revision history for a file or files
- Fork or branch from a given version
- Join or merge two versions
- Roll back to a specific version
- Create a new version and share it with others
- View the changes between two versions
- Mark or otherwise annotate specific versions

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