Statistics Signature Assignment Assistance

Statistics Signature Assignment
Statistics Signature Assignment

Statistics Signature Assignment

About Your Statistics Signature Assignment

This signature assignment is designed to align with specific program student learning outcome(s) in your program. Program Student Learning Outcomes are broad statements that describe what students should know and be able to do upon completion of their degree. The signature assignments might be graded with an automated rubric that allows the University to collect data that can be aggregated across a location or college/school and used for program improvements.

Purpose of Assignment

The purpose of this assignment is for students to synthesize the concepts learned throughout the course. This assignment will provide students an opportunity to build critical thinking skills, develop businesses and organizations, and solve problems requiring data by compiling all pertinent information into one report.

Assignment Steps

Resources: Microsoft Excel®, Signature Assignment Databases, Signature Assignment Options, Part 3: Inferential Statistics

Scenario: Upon successful completion of the MBA program, say you work in the analytics department for a consulting company. Your assignment is to analyze one of the following databases:

  • Manufacturing
  • Hospital
  • Consumer Food
  • Financial

Select one of the databases based on the information in the Signature Assignment Options.

Provide a 1,600-word detailed, statistical report including the following:

  • Explain the context of the case
  • Provide a research foundation for the topic
  • Present graphs
  • Explain outliers
  • Prepare calculations
  • Conduct hypotheses tests
  • Discuss inferences you have made from the results

This assignment is broken down into four parts:

Part 1 – Preliminary Analysis
Part 2 – Examination of Descriptive Statistics
Part 3 – Examination of Inferential Statistics
Part 4 – Conclusion/Recommendations
Part 1 – Preliminary Analysis (3-4 paragraphs)

Generally, as a statistics consultant, you will be given a problem and data. At times, you may have to gather additional data. For this assignment, assume all the data is already gathered for you.

State the objective:
  • What are the questions you are trying to address?
  • Describe the population in the study clearly and in sufficient detail:
  • What is the sample?
  • Discuss the types of data and variables:
  • Are the data quantitative or qualitative?
  • What are levels of measurement for the data?

Part 2 – Descriptive Statistics (3-4 paragraphs)

  • Examine the given data.
  • Present the descriptive statistics (mean, median, mode, range, standard deviation, variance, CV, and five-number summary).
  • Identify any outliers in the data.
  • Present any graphs or charts you think are appropriate for the data.

Note: Ideally, we want to assess the conditions of normality too. However, for the purpose of this exercise, assume data is drawn from normal populations.

Part 3 – Inferential Statistics (2-3 paragraphs)

Use the Part 3: Inferential Statistics document.

  • Create (formulate) hypotheses
  • Run formal hypothesis tests
  • Make decisions. Your decisions should be stated in non-technical terms.

Hint: A final conclusion saying “reject the null hypothesis” by itself without explanation is basically worthless to those who hired you. Similarly, stating the conclusion is false or rejected is not sufficient.

Part 4 – Conclusion and Recommendations (1-2 paragraphs)

Include the following:

  • What are your conclusions?
  • What do you infer from the statistical analysis?
  • State the interpretations in non-technical terms.
  • What information might lead to a different conclusion?
  • Are there any variables missing?
  • What additional information would be valuable to help draw a more certain conclusion?

My Essay Choice:

Option 3: Consumer Food

1. Suppose you want to test to determine if the average annual food spending for a household in the Midwest region of the U.S. is more than $8,000. Use the Midwest region data and a 1% level of significance to test this hypothesis. Assume that annual food spending is normally distributed in the population.

2. Test to determine if there is a significant difference between households in a metro area and households outside metro areas in annual food spending. Let α = 0.01.

3. The Consumer Food database contains data on Annual Food Spending, Annual Household Income, and Non-Mortgage Household Debt broken down by Region and Location. Using Region as an independent variable with four classification levels (four regions of the U.S.), perform three different one-way ANOVA’s—one for each of the three dependent variables (Annual Food Spending, Annual Household Income, Non-Mortgage Household Debt). Did you find any significant differences by region?

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