STATS ONLY

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The first part:

The following are the cases from this module. You have completed each of these replications by now. Please upload your work in the EXCEL file.

There is one additional step, though, that you may need to complete. You may or may not have thought about the professional polish for the benefit of others using your data. Professional polish for effective analysis involves organizing and labeling the data so that a user of your information will quickly understand where the key data are and what messages the data are conveying.

VISUALIZATION AND MEASURES OF CENTRAL TENDENCY 1. Histograms

2. Use the cell function “=average” and “=median” to generate the mean and median score for Mr. Predictable and Mr. Unpredictable.

2. Generate a descriptive statistics table from the Data Analysis (DATA / DATA ANALYSIS). Ensure that the values from the descriptive statistics table agree with those from the cell function calculations developed in step 1.

MEASURING THE VARIABILITY IN THE DATA 1. Use the bowling data. Calculate the variance and standard deviation using the EXCEL cell functions (VAR Function and STDEV function)

2. Ensure that the variance and standard deviation calculated in item 1 agree with the variance and standard deviation provided by the from the Descriptive Statistics tool in the EXCEL DATA TOOLPAK.

DIVIDING DATA FOR ANALYSIS 1. Develop quartiles and deciles for the S&P 500 Market Values

NORMALIZING DATA FOR DECISION MAKING

See the data in the “Coat Sales” tab in the EXCEL student data file. North Trace sells winter coats. You are the Sales Manager with responsibility for two markets: The Upper Midwest headquartered in Chicago and the Southwest headquartered in Los Angeles. You are evaluating your most talented sales persons. Their sales are shown in the EXCEL spreadsheet. Required: 1. Make the empirical case for the top five sales persons in your employ. 2. One sales person is going to be moved out of sales and into the warehouse shipping operations. You do not want this to be one of the talented sales persons. Each of your sales persons is equally able to perform the shipping operations function. Who should be transferred?

A CLOSER LOOK AT THE NORMAL DISTRIBUTION (BELL CURVE)

See the bell curve that represents the bowling scores of Mr. Consistency and Mr. Unpredictable 1. Identify the mean 2. Discuss one standard deviation away from the mean 3. Discuss two standard deviations away from the mean 4. What does it mean to be in the right tail of the distribution? 5. What does it mean to be in the left tail of the distribution? 6. What is the cumulative probability?

RELATIONSHIP BETWEEN TWO VARIABLES

See the “Two Variables (GPA and ACT +)” tab in the data file 1. Create a scatter diagram for GPAs and ACT Scores 2. Create a scatter diagram for GPAs and Absences 3. Does there appear to be a relationship between the two variables? If so, which variable is at least somewhat dependent upon the value of the other variable?

SEE THE TWO VARIABLES (GPA AND ACT +) TAB: 1. Calculate the Correlation Coefficient for two variable sample • ACT Score and GPA • Absences and GPA

The second part

Hypothesis Testing ASSIGNMENT (small sample size)

The CPA Review course providers conducted an experiment. They selected a sample of 24 UMSL Master of Accounting students with very close ACT scores, very close GMAT scores, and very close GPAs. Twelve randomly selected students used the self-study CPA Review course materials (the control group) and twelve randomly selected students used the same materials but also used the in-class instructor experience two nights per week (the treatment group).

At what confidence level can the CPA Review provider claim the in-class experience has incremental value?

(See scores in EXCEL file tab “CPA Exam Scores”)

Hypothesis Testing (Larger Sample Size)

The University has struggled for a number of years with its introductory statistics course. After another challenging outcome on exam 1, the Dean provided a teaching assistant that would work exclusively with the lowest performing quartile of students on exam 1.

The data for exams one and two are shown in the EXCEL file (Tab Student Test Scores). Does the data suggest that the teaching assistant helped the lesser performing students close the performance gap?

Example:

A hospital struggles to get its patients to complete the entire regimen of antibiotics when they are prescribed. Instead, many patients take the medicine until they feel better and then save the antibiotics in case they get another infection. To manage this issue, the hospital has decided to put a message on each bottle imploring patients to finish the entire bottle. The experts are confident that at worst, the message will go unheeded. It certainly will not cause them to take less medicine! They hope it causes them to take more.

If they gather data, they could use a one-tailed test in this instance to see if any observed increase in usage is significant.

One-Tailed Hypothesis Test Assignment:

See the data in Tab “Pharmacy”

1. Calculate the mean, median, and modal number of pills taken by participants in the control group and in the sample group.

2. With what level of confidence can the Pharmacy say that the message of encouragement to complete the full dosage caused a change in patient’s behavior (i.e., led to a increase in pills taken that is large enough to be statistically significant)?

The 3rd part

Hypothesis Testing ASSIGNMENT (small sample size)

At what confidence level can the CPA Review provider claim the in-class experience has incremental value?

(See scores in EXCEL file tab “CPA Exam Scores”)

Hypothesis Testing (Larger Sample Size)

Example:

If they gather data, they could use a one-tailed test in this instance to see if any observed increase in usage is significant.

One-Tailed Hypothesis Test Assignment:

See the data in Tab “Pharmacy”

1. Calculate the mean, median, and modal number of pills taken by participants in the control group and in the sample group.

The 4th part:

SIMPLE REGRESSION ASSIGNMENT

See EXCEL data tab “Bat Production Costs”

Use regression analysis to estimate the fixed and variable components of production costs at Louistown Masher

REGRESSION ASSIGNMENT

A local high tech company employs 26 information technology professionals. Their salaries are shown in the EXCEL spreadsheet.

Required:

1. Produce a scatter plot of salaries and tenure (months of service) and comment on the linear assumption (is it at least quasi-linear to become comfortable that the linearity assumptions holds).

2. Estimate the regression equation that represents salaries as a function of tenure with the company (months of service)

3. Analyze the fit of the regression model

· Comment on the F-value for the significance of the regression model

· What is the probability that there is no linear relation between the DV and the IV whatsoever?

· Comment on the R2

· What percentage of the variance in the salaries is explained by tenure?

· Comment on the plot of the residuals against the independent variable

4. Interpret the estimated regression coefficients

· How are salaries determined according to the regression model? What is the fixed component of salary and what is the amount resulting from raises while at the company?

5. Replicate the following values per the regression output using EXCEL formulas

· Average salary for all employees

· Total Residual (observed salary – mean salary) for each employee

· Predicted salary per the regression equation for each employee (Y-HAT)

· The Model Residual (the difference between the actual salary for the employee and the predicted salary per the regression equation) for each employee

· Total unexplained variance (residual variance)

· Total explained variance

MULTIPLE REGRESSION ASSIGNMENT:

Per our analysis of the residuals in the regression of salaries at the High Tech company against tenure (months of service) it was clear that there was some other variable of significance. One of our hypotheses was that it might be that some employees had additional education (i.e., a Master’s Degree) which earned them incremental salary.

See the data in the EXCEL file.

Required:

1. Use Multiple Regression to estimate the relationship between salaries and both tenure (months with the company) and education (indicator variable for a Master’s Degree).

2. Produce a histogram of the model residuals and analyze

3. Analyze the residual plots for each for each of the IVs

4. Analyze whether the model is improved with the two variables (is adjusted R-squared greater than regression R-squared with just the single variables)

5. Analyze the coefficients

6. Prepare a Pearson Correlation Matrix for the independent variables

The 5th part

Replicate the operations you watched in the video to compute BOTH the solution AND the shadow prices for the various constraints.

It is also important that you set up the problem in an organized way.

LP Maximization Problem

The scenario is described in the video, but all of the parameters you need for this problem can be found in the data pack, in the LP_Max_Gateway tab. This concerns Gateway Chair Company's profit maximization problem. If you don't like my spreadsheet layout you can substitute your own, as long as its clean and easily readable.

Go to the EXCEL file tab “LP_Max_Gateway”.

LP Minimization Problem

The scenario is described in the video, but all of the parameters you need for this problem can be found in the data pack, in the LP_Min_XY tab. This concerns X&Y Industries cost minimization. Take note of the variety of inequality constraints you encounter in this one. If you don't like my spreadsheet layout you can substitute your own, as long as its clean and easily readable.

Go to the EXCEL file tab “LP_Min_XY".