# Assignment #03: Time Management with Excel

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### Technical Module I

Demonstrator:

Dereatha Cross | dac4303@ksu.edu

## Assignment #03: Time Management with Excel

### Introduction

Success in any endeavor depends upon time management. One of the optional exercises covers such concepts applying them to Microsoft Excel.

Planners rely on statistical information and the ability to communicate such data. A planner’s success in such endeavor depends on their ability to convert data into information usually in the form of a probabilistic model. This model must be able to explain the data observed and must account for the variation encountered.

Listening to data requires us to enter into a conversation with the data. Most of us find our first encounters with data to be very one-sided, just like dealing with a very shy person. There are several methods we can learn about the “shy” person simply through data modeling.

It may or may not be that you have had statistics. However, it may be useful to learn how to represent statistical data. This

assignment gives you the freedom to choose the appropriate exercise for your skill level. If you are not sure, start at level 2. If you find the exercise too difficult move down a level. If it is too easy move up a level.

Finally, there are those rare planners who are the “Jedi masters” of Excel. So, yes, there is an exercise for you too.

A lot of concepts will be provided here which may seem above your current academic level. Recall part of Techmod is to gather resources for later use. So even if you do not quite understand what is going on with each concept yet, try the exercises to make the interesting graphs, and save the resources for later when you might really need it.

### Student Learning Outcomes

 Demonstrate understanding of file management.

 Demonstrate understanding of tables, formulas, conditional formatting, and conditional statements  Demonstrate resourcefulness

### Task 1: Choose one of the exercises (A, B, C, D, or E)

A. Introduction to Microsoft Excel (For beginners) B. Stem-and-Leaf Displays (Level 1)

C. Boxplot/Box and Whisker(Level 2) D. Histograms (Level 1)

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### Part 1: Concept

One of the most difficult concepts to learn in college is time management. We will use Excel to learn Time Management and Time management to help us learn Excel. This presentation demonstration is for beginners in Excel. It will be given at the APDesign West building.

### Part 2: Setup the file management system

1. Create a project called “FileManagementStrategy” 2. Open Microsoft Excel

### Part 3: Follow along in class (this means you will likely need to come to class)

1. This demonstration will likely take two weeks to complete.

2. Keep in mind the following:

a. For every cr/hr enrolled you need to spend 3 hours outside of class time studying for that course. b. You need 6 to 8 hours of sleep every night

c. You need two to three meals a day

d. You need to perform personal hygiene tasks daily

e. You need to exercise 30 minutes to an hour daily (sleeping in the grass outside does not count) f. Other activities should be included ranging from religious, socializing, and/or work.

3. Take-aways

a. Excel is used for analyzing data

b. Excel can be used to help inform you if your time management strategy is realistic.

### Part 4: Study Results

1. Is your time management proposal realistic?

### Part 5: Submission

Submit Sunday night at 10 p.m. for feedback

### Part 1: Concept

The stem-and-leaf display provides a basis for evaluating the “shape” of the data set with minimal loss of the original information. The basic idea is to let the data suggest natural groupings, which then may be exploited to produce a plot that displays the data’s shape. This process loses only the time order of the data.

Before doing a stem-and-leaf plot the data must be organized in ascending order.

### Part 2: Setup the file management system

3. Create a project called “StemAndLeafDisplay” 4. Open Microsoft Excel

5. Navigate to the following link:

a. How to create Stem-And-Leaf Display

b. Using double “” means your datatype will be a “string”. There are other data types such as Booleans, characters, floating-point numbers, and alpha-numeric strings. To learn more:

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Page 3 Some applications will have data types specific to that application. For example GIS has a datatype called a “blob”. This is an important concept to learn because when doing mathematical operations the computer often wants all data in the equation to be of the same data type. This is applicable in Microsoft Excel.

c. Concatenation can be used to help stitch together data such that it appears much like how it appeared in the Leaf side of the video demonstration. Notice it is counting how many “leaves” there are on the stem 5. There is only one numbers in the 50 to 59 range. That number is a 2 so you see only one leaf but notice how 7 has 8 numbers from 70 to 79 range. SO you see 8 leaves. These leaves numerical values are 2, 4, 4, 6, 6, 6, 8, and 8. Notice in Excel how they have a space in between. This was done when “ # “ was specified in the formula. Notice the space before and after. Then the code used the & symbol before the next duplicate code is pasted. This allows you to have “ # “” # “ right next to each other. This is called concatenation. To learn more:

https://en.wikipedia.org/wiki/Concatenation

This can be useful in helping you present your data in a specific format without having to do it manually each time.

d. Automating a repetitious task is extremely useful and time conserving. Notice rept function is used: Rept(____,_____). The first blank is the number after the first digit you are looking for. So the first run will look for a 50 and will input a 0 in the cell if it finds a 50. It would stop at 50 if not for countif. Notice the second blank contains the function countif(_____,_____). The first blank is the range to look in. In the example the first blank is the range between specific cell values 52 to 96. The second blank is the number we are searching for. The first iteration is a 50. C5*0+1 equals 50 in the first iteration.

e. Using “\$“ symbol will make sure when you copy a formula each variable in your formula will not shift cells. So in our example notice the range was from cell A1 to A20. Notice how we copied the formula from D5 to D10. We don’t want A1 to A20 selection to shift down as we copy and paste the formula down the page. By adding the \$ we ensure A1 to A20’s selection will stay put.

f. Finally brackets in excel work the same as they do in arithmetic on a calculator. The computer does the operations in the inner most bracket set before it does the outer most ones.

g. Specifying a range of numbers using “:”. The : symbol may be useful when needing to specify a range of numbers. You can also click and drag to select the range of numbers.

### Part 4: Study Results

1. Two questions one would ask the data is (1) what is the typical value (the “center”) for the dataset? And (2) What is the variability (“Spread”) of the data?

2. More subtle questions are:

a. Does the data follow some pattern? (symmetric, skewed right, skewed left) b. Are there multiple peaks?

c. Are there outliers? d. Any interesting features?

3. We will take the results and draw on it as such: Stems  Leafs  5   2   6   2  6  8   7   2  4  4  6  6  6  8  8   8   2  2  4  6  8   9   2  6

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Page 4 5. Skewed to the right would look like this:

6. Skewed to the left would look like this:

7. Multiple peaks would look somewhat like the following (may have more or less peaks) and typically means contamination from another population.

8. Outliers are data values that clearly are out of sync with the other values in the dataset. One may want to ask if something went wrong in the data collection process or in the transcription process.

9. Regardless of the result the planner should study why such patterns exist. For the purposes of Techmod we simply need to know how to create these plots and have some awareness as to their functions. We will leave further discussion of this topic for your statistics course.

### Part 5: Submission

Zip the project folder named “StemAndLeafDisplay” and submit the compressed file on Sunday night at 10 p.m. for feedback.

### Part 1: Concept

The boxplot provides a quick display of some important features of the data. Unlike the stem-and-leaf display, which retains virtually all of the information in the data set, the boxplot “distills” the data set down to its most important features. As a result, the boxplot does lose some information contained in the dataset.

The boxplot gives the planner a formal tool for discriminating outliers during preliminary data analysis. Since we expect to encounter outliers, we construct the boxplot by using measures of the center and the spread based on the median and the quartiles, which are resistant or insensitive to the presence of outliers. Both the median and the quartiles require the data set to be arranged in ascending order.

Definition of some terms:

Median: This is the middle value of the dataset once it has been arranged in ascending order. The median gives a measure of the “center” of the dataset. So this would be like writing it out and taking a yard stick and measuring the middle.

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Page 5 Sometimes it may fall between two numbers. There are equations which go along with this concept one can learn about in statistics.

Quartiles: With the data arranged in ascending order, the quartiles are those values that divide the dataset into four equal parts. The first or lower quartile often denoted as Q1, the third or upper quartile is denoted as Q3, and the median is the

second quartile Q2.

So let us do this in Excel so we can see what this all exactly means visually.

### Part 2: Setup the file management system

1. Create a project called “Boxplots”. 5. Open Microsoft Excel

2. Navigate to the following link:

a. Notice quartile (_____,_____) function is used. The first blank contains the range. The second blank is where you indicate quartiles. To learn more:

https://en.wikipedia.org/wiki/Quartile b. How to format charts

c. It is pretty common for software companies such as Microsoft to update their products sometimes yearly. When this occurs the help and other tutorial resources may not match up exactly. You may have to look around the interface to locate that same function. That was the case in this tutorial.

### Part 4: Study Results

1. The median and the quartiles are often called resistant statistics because they are relatively insensitive to the presence of outliers. Recall the video chose “no fill” for certain areas.

2. Boxplots are used to identify possible outliers. We compromise our ability to identify outliers if extreme values distort our definition of a possible outlier.

3. Boxplots provide the planner with the following information: a. The center of the dataset.

b. Where most of the data falls

c. The spread of the unquestionably “good” data d. Possible outliers.

4. Regardless of the results the planner should study why such patterns exist. For the purposes of Techmod we simply need to know how to create these plots and have some awareness as to their functions. We will leave further discussion of this topic for your statistics course.

### Part 5: Submission

1. Zip the project folder named “Boxplots” and submit the compressed file on Sunday night at 10 p.m. for feedback

### Part 1: Concept

Histograms simply provide us another way to see the shape of the data. The data is divided up into suitable ranges of intervals, all with the same length. The histogram then plots either the count for the number of observations that fall within each interval (for small datasets) or the relative proportion of observations that fall within each interval (for large data sets). The interval chosen by some software applications may or may not correspond with the stems it chooses for the

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Page 6 that fall in the interval, we lose the individual data values. In general, stem-and-leaf plots should be used for smaller datasets and histograms for larger ones as histograms will rescale the data to a workable scale.

There are many suggestions as to what the interval should be. It really depends on the application you are using and the information you are seeking.

So let us do this in Excel so we can see what this all exactly means visually.

### Part 2: Setup the file management system

1. Create a project called “Histogram”. 2. Open Microsoft Excel.

2. Navigate to the following link:

a. How to use keyboard shortcuts b. How to create and edit a table

### Part 4: Study Results

1. The results are similar to the stem and leaf plot. Refer to that exercise Part 4. Recall you would use this method for large datasets, not small ones.

Part 5: Submission

1. Zip the project folder named “Histogram” and submit the compressed file on Sunday night at 10 p.m. for feedback.

### Part 1: Concept

VBA is one the easiest programming languages to learn. A programming language is the “DNA” of the application except we don’t call it DNA we call it writing the code of the application. Being able to write code for Microsoft Excel allows you more analysis design freedom. To put it simply, you can go beyond the functions in the ribbon tab by simply creating your own. This exercise is recommended for advanced Excel users only. If you are not yet advanced it might be useful to save this for later in case you might be interested in learning this later.

### Part 2: Setup the file management system

1. Create a project called “LearningVBA”. This is where you would save the tutorials. 2. Open Microsoft Excel.

1. The following link is a play list of many videos. Start where you think you need to. Navigate to the following link:

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## References

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