Category: Statistics

Calculate Your Net Worth Instructions
How do you calculate net worth? Calculating your net worth requires you to take an inventory of what you own, as well as your outstanding debt. And when we say own, we include assets that you may still be paying for, such as a car or a house.
For example, if you have a mortgage on a house with a market value of $200,000 and the balance on your loan is $150,000, you can add $50,000 to your net worth.
Basically, the formula is: ASSETS – LIABILITIES = NET WORTH
Download the Net Worth Spreadsheet below to calculate your net worth. The items listed may or may not apply to you. Delete, add, and substitute to personalize it to your needs.
Create a Budget Instructions
Everyone needs a budget, whether you’re married with kids or a student embarking on an educational journey. While making and sticking to a budget may seem like a daunting task, the process can actually be easier than you think. There are a number of ways to save a few bucks every month.
An effective budget needs to be put down on paper or via a spreadsheet from a student budget template. On this budget, make a list of all your forms of incomes (including your job, loans, parents, etc.), followed by all your expenses (such as rent, books, food, etc.).
Make sure to differentiate between your needs versus your wants. The final number that you calculate should not be a negative number. If it is, you need to make some adjustments to make sure your take-home pay covers all your expenses.
Download the Budget Spreadsheet below to create a monthly budget. The items listed may or may not apply to you. Delete, add, and substitute to personalize it to your needs. Do NOT include a “miscellaneous” category – everything needs to be accounted for. Download and fill out the attached Microsoft Excel spreadsheets to complete this assignment. When you are finished, you will upload the completed Microsoft Excel spreadsheets.

there are 3 parts to this assignment, i have attached the instructions for each part, as well as an example for each of the parts, so please look at them fro refence as to how to work sshould be done. For the data that needs to be analyzed, I have screenrecored a video showing it, and all of the labels, so please refence that. I also included an image of the codebook mentioned, so when it is needed, that should be used! I also said that 3 sources are required, but if more are needed, as are shown in the examples, please do include them! Let me know if any required information is missing or if there is anything that needs further clarification!

there are 3 parts to this assignment, i have attached the instructions for each part, as well as an example for each of the parts, so please look at them fro refence as to how to work sshould be done. For the data that needs to be analyzed, I have screenrecored a video showing it, and all of the labels, so please refence that. I also included an image of the codebook mentioned, so when it is needed, that should be used! I also said that 3 sources are required, but if more are needed, as are shown in the examples, please do include them! Let me know if ther are any questions!

Need to calculate and answer the following short questions, using the table attached.
1-    How many players have values that are above the mean in this dataset?
2-    How players have values that are below the mean?
3-    Calculate the z-score for Bam Adebayo. Round your answer to three decimal places. (you should also round the mean and standard deviation out three decimal places in your calculation to avoid rounding error). 
4-    Calculate the z-score for Jimmy Butler. Round your answer to three decimal places. (you should also round the mean and standard deviation out three decimal places in your calculation to avoid rounding error). 
5-    Calculate the z-score for Haywood Highsmith. Round your answer to three decimal places. (you should also round the mean and standard deviation out three decimal places in your calculation to avoid rounding error). 
6-    Calculate the z-score for Dru Smith. Round your answer to three decimal places. (you should also round the mean and standard deviation out three decimal places in your calculation to avoid rounding error)
7-    Calculate the z-score for Tyler Herro. Round your answer to three decimal places. (you should also round the mean and standard deviation out three decimal places in your calculation to avoid rounding error). 
8-    Calculate the z-score for Jamal Cain. Round your answer to three decimal places. (you should also round the mean and standard deviation out three decimal places in your calculation to avoid rounding error). 
9-    If you randomly select a professional basketball player, what is the probability that the player’s field goal percentage for the season is between Tyler Herro and Cody Zeller? To answer this question you need to use the table in the appendix of the text to figure out the area between those two scores on the normal curve. Show your work on this. To get full credit, you must demonstrate all calculations, values you used from the appendix, and steps you took to get your answer (that is, your answer must include the z score, the area under the curve that you found in the appendix, and how you came to your final answer).
10- If you randomly select an NBA player from the whole population, what percentage of the time would the player’s field goal percentage for the season be lower than Duncan Robinson? To answer this question you need to use the table in the appendix of the text to figure out the area below this score. Show your work on this. To get full credit, you must demonstrate all calculations, values you used from the appendix, and steps you took to get your answer (that is, your answer must include the z score, the area under the curve that you found in the appendix, and how you came to your final answer).
11- You and your friend are engaging in a classic sports argument: which famous athlete is better at their respective sport? In other words, we’re going to explore the question: in the year 2023, was Jimmy Butler better at basketball than Travis Kelce (Tight End for Kansas City) was at football? Because we’re comparing to totally different sports with different statistics, in order to answer this question, we need to look at standardized scores (z-scores). For Travis Kelce, we’ll look at Yards Per Catch (or Yards Per Reception), which shows the average number of yards a receiver gains every time they catch the football (how far do they take the ball each time they catch it?). It’s a simple but effective metric for evaluating the effectiveness and productivity of a Tight End. In the 2023 season, Travis Kelcy had an average of 10.6 yards per catch. The total NFL average for tight ends that year was 9.77 with a standard deviation of 2.49. 
Using this information tell me, who was better at their respective sport: Jimmy Butler or Travis Kelce?
In your answer include the following information: 
a.     The z scores for Kelce’s yards per catch and Jimmy Butler’s field goal percentage?
b.     A comparison of the two z scores and an explanation of your conclusion, based on those z-scores.  What is your final conclusion: who is better, relative to others in their respective sports? Why?
c.     Is this a fair comparison? Why or why not? 

Answer all questions except question 2,3, and 4.
Please read instructions carefully and answer the questions correctly.
Let me know if any files don’t open.
Thanks.

Here are the details:
Initial Post : For your initial post, you should choose and solve one of the problems from the document posted above. To do so, please try to print out the single page, solve the problem, scan back in and post. You may also just state the number of the problem and solve it in the discussion itself using the math typesetting if you would like. You should try to choose a problem that people haven’t done yet or use a different technique if you solve one that has already been posted. Make sure to post the problem number in the subject line of your post.
Be sure to explain HOW how you solved it. Did you use the calculator? a Table? StatCrunch? Really explain it so others can understand! 🙂
If you’d like, you may post a video of you solving it!
Follow-up Posts: You are required to post AT LEAST 2 follow-up posts. These can be replies to other students, additional solved review problems, videos or website resources that have helped you study, etc. If someone has already replied, please make sure to make your reply unique by offering another suggestion, a different place to look, or comment on someone else’s question.
You are more than welcome to solve more problems!

This is a written discussion board assignment, so please respond to the following prompt in an essay response of around 150 words.
Prompt: For this discussion board post, explain the following three things:
What are degrees of freedom?
Why do we divide SS by df instead of by N when estimate population variance?
What is the difference between a one-sample t-test and a dependent samples t-test

Competency
In this project, you will demonstrate your mastery of the following competency:
Apply statistical techniques to address research problems
Perform hypothesis testing to address an authentic problem
Overview
In this project, you will apply inference methods for means to test your hypotheses about the housing sales market for a region of the United States. You will use appropriate sampling and statistical methods.
Scenario
You have been hired by your regional real estate company to determine if your region’s housing prices and housing square footage are significantly different from those of the national market. The regional sales director has three questions that they want to see addressed in the report:
Are housing prices in your regional market lower than the national market average?
Is the square footage for homes in your region different than the average square footage for homes in the national market?
For your region, what is the range of values for the 95% confidence interval of square footage for homes in your market?
You are given a real estate data set that has houses listed for every county in the United States. In addition, you have been given national statistics and graphs that show the national averages for housing prices and square footage. Your job is to analyze the data, complete the statistical analyses, and provide a report to the regional sales director. You will do so by completing the Project Two Template located in the What to Submit area below.
Directions
Introduction
Region: Start by picking one region from the following list of regions:
West South Central, West North Central, East South Central, East North Central, Mid Atlantic
Purpose: What is the purpose of your analysis?
Sample: Define your sample. Take a random sample of 500 house sales for your region.
Describe what is included in your sample (i.e., states, region, years or months).
Questions and type of test: For your selected sample, define two hypothesis questions (see the Scenario above) and the appropriate type of test for each. Address the following for each hypothesis:
Describe the population parameter for the variable you are analyzing.
Describe your hypothesis in your own words.
Identify the hypothesis test you will use (1-Tail or 2-Tail).
Level of confidence: Discuss how you will use estimation and confidence intervals to help you solve the problem
1-Tail Test
Hypothesis: Define your hypothesis.
Define the population parameter.
Write null (Ho) and alternative (Ha) hypotheses. Note: For means, define a hypothesis that is less than the population parameter.
Specify your significance level.
Data analysis: Summarize your sample data using appropriate graphical displays and summary statistics and confirm assumptions have not been violated to complete this hypothesis test.
Provide at least one histogram of your sample data.
In a table, provide summary statistics including sample size, mean, median, and standard deviation. Note: For quartiles 1 and 3, use the quartile function in Excel:
=QUARTILE([data range], [quartile number])
Summarize your sample data, describing the center, spread, and shape in comparison to the national information (under Supporting Materials, see the National Summary Statistics and Graphs House Listing Price by Region PDF). Note: For shape, think about the distribution: skewed or symmetric.
Check the conditions.
Determine if the normal condition has been met.
Determine if there are any other conditions that you should check and whether they have been met. Note: Think about the central limit theorem and sampling methods.
Hypothesis test calculations: Complete hypothesis test calculations.
Calculate the hypothesis statistics.
Determine the appropriate test statistic (t). Note: This calculation is (mean – target)/standard error. In this case, the mean is your regional mean, and the target is the national mean.
Calculate the probability (p value). Note: This calculation is done with the T.DIST function in Excel:
=T.DIST([test statistic], [degree of freedom], True) The degree of freedom is calculated by subtracting 1 from your sample size.
Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
Relate the p value and significance level.
Make the correct decision (reject or fail to reject).
Provide a conclusion in the context of your hypothesis.
2-Tail Test
Hypotheses: Define your hypothesis.
Define the population parameter.
Write null and alternative hypotheses. Note: For means, define a hypothesis that is not equal to the population parameter.
State your significance level.
Data analysis: Summarize your sample data using appropriate graphical displays and summary statistics and confirm assumptions have not been violated to complete this hypothesis test.
Provide at least one histogram of your sample data.
In a table, provide summary statistics including sample size, mean, median, and standard deviation. Note: For quartiles 1 and 3, use the quartile function in Excel:
=QUARTILE([data range], [quartile number])
Summarize your sample data, describing the center, spread, and shape in comparison to the national information. Note: For shape, think about the distribution: skewed or symmetric.
Check the assumptions.
Determine if the normal condition has been met.
Determine if there are any other conditions that should be checked on and whether they have been met. Note: Think about the central limit theorem and sampling methods.
Hypothesis test calculations: Complete hypothesis test calculations.
Calculate the hypothesis statistics.
Determine the appropriate test statistic (t). Note: This calculation is (mean – target)/standard error. In this case, the mean is your regional mean, and the target is the national mean.]
Determine the probability (p value). Note: This calculation is done with the TDIST.2T function in Excel:
=T.DIST.2T([test statistic], [degree of freedom]) The degree of freedom is calculated by subtracting 1 from your sample size.
Interpretation: Interpret your hypothesis test results using the p value method to reject or not reject the null hypothesis.
Compare the p value and significance level.
Make the correct decision (reject or fail to reject).
Provide a conclusion in the context of your hypothesis.
Comparison of the test results: Revisit Question 3 from the Scenario section: For your region, what is the range of values for the 95% confidence interval of square footage for homes?
Calculate and report the 95% confidence interval. Show or describe your method of calculation.
Final Conclusions
Summarize your findings: In one paragraph, summarize your findings in clear and concise plain language.
Discuss: Discuss whether you were surprised by the findings. Why or why not?

Textbook: Tokunaga, H. (2019). Fundamental Statistics for the Social and Behavioral Sciences (2nd ed.). Thousand Oaks, CA: Sage Publications, Inc
Complete and discuss your finding for exercise number 12 and exercise number 18 in your textbook. They are at the end of chapter 4, listed under 4.15 Exercises, on page 111 in the textbook. 
#12 – 50 points
#18 – 50 points

In real-life applications, statistics helps us analyze data to extract information about a population. In this module discussion, you will take on the role of Susan, a high school principal. She is planning on having a large movie night for the high school. She has received a lot of feedback on which movie to show and sees differences in movie preferences by gender and also by grade level.
She knows if the wrong movie is shown, it could reduce event turnout by 50%. She would like to maximize the number of students who attend and would like to select a PG-rated movie based on the overall student population’s movie preferences. Each student is assigned a classroom with other students in their grade. She has a spreadsheet that lists the names of each student, their classroom, and their grade. Susan knows a simple random sample would provide a good representation of the population of students at their high school, but wonders if a different method would be better.
You can review the student demographics here: Module One Discussion Data PDF.
In your initial discussion post, specifically address the following:
Introduce yourself and describe a time when you used data in a personal or professional decision. This could be anything from analyzing sales data on the job to making an informed purchasing decision about a home or car.
Describe to Susan how to take a sample of the student population that would not represent the population well.
Describe to Susan how to take a sample of the student population that would represent the population well.
Finally, describe the relationship of a sample to a population and classify your two samples as random, systematic, cluster, stratified, or convenience.