## Description

# BUS 308 Statistics for Managers Complete Week 1 to 5

**BUS 308 Statistics for Managers, New Syllabus
**

**WEEK 1**

**Assignment Problem Set**

- Using the Excel Analysis ToolPak function descriptive statistics, generate descriptive statistics for the salary data. Which variables does this function not work properly for, even though we have some excel generated results?
- Sort the data by Gen or Gen 1 (into males and females) and find the mean and standard deviation for each gender for the following variables: Use the descriptive stats function for one gender and the Fx functions (average and stdev) for the other.

** 3a.**Randomly selected person being a male in a specific grade?

** 3b.**Randomly selected person being in a specific grade?

** 4a.** The z score for each male salary, based on the male salary distribution.

** 4b.** The z score for each female salary, based on only the female salaries.

** 5a.** The z score for each male compa, based on only the male compa.

** 5b.**The z score for each female salary, based on the female salary distribution.

- What conclusions can you make about the issue of male and female pay equality? Are all of the results consistent? If not, why not?

** Discussion 1**: Language

** Discussion 2**: Levels

**Quiz (03 Sets)**

**Â **

**WEEK 2**

**Assignment Problem Set**

- Is either that male or female salary equal to the overall mean salary? (Two hypotheses, one-sample tests needed.)
- Are male and female average salaries statistically equal to each other?
- Are the male and female compa average measures equal to each other?
- If the salary and compa mean tests in questions 2 and 3 provide different equality results, which would be more appropriate to use in answering the question about salary equity? Why?
- What other information would you like to know to answer the question about salary equity between the genders? Why?

** Discussion 1**: t-Test

** Discussion 2: **Â Variation

**Quiz (03 Sets)**

**Â **

**WEEK 3**

**Assignment Problem Set**

- Is the average salary the same for each of the grade levels? (Assume equal variance, and use the analysis toolpak function ANOVA.) Set up the input table/range to use as follows: Put all of the salary values for each grade under the appropriate grade label.
- The factorial ANOVA with only 2 variables can be done with the Analysis ToolPak function 2-Way ANOVA with replication. Set up a data input table like the following:
- Repeat question 2 for the compa values.
- Pick any other variable you are interested in and do a simple 2-way ANOVA without replication.Why did you pick this variable and what do the results show?
- What are your conclusions about salary equity now?

** Discussion 1**: ANOVA Testing

** Discussion 2:** Effect Size

**Quiz (02 Sets)**

**BUS 308 WEEK 4**

**Assignment Problem Set**

- Is the probability of having a graduate degree independent of the grade the employee is in?
- Construct a 95% confidence interval on the mean service for each gender? Do they intersect?
- Are males and females distributed across grades in a similar pattern?
- Do 95% confidence intervals on the mean length of service for each gender intersect?
- How do you interpret these results in light of our equity question?

** Discussion 1:** Â Confidence Intervals

** Discussion 2:**Â Chi-Square Tests

**Quiz (03 Sets)**

**WEEK 5**

** Final Paper: **Identify an issue in your life (work place, home, social organization, etc.) where a statistical analysis could be used to help make a managerial decision. Develop a sampling plan, an appropriate set of hypotheses, and an inferential statistical procedure to test them. You do not need to collect any data on this issue, but you will discuss what a significant statistical test would mean and how you would relate this result to the real-world issue you identified. Your paper should be three to five pages in length (excluding the cover and reference pages). In addition to the text, utilize at least three sources to support your points. No abstract is required. Use the following research plan format to structure the paper:

** Discussion 1**: Correlation

** Discussion 2: **Regression

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