Evaluate how data could be used to measure the implementation of such a solution

This assignment provides students with practice in understanding when or why ANOVA and linear regression are identified based on parameters. Students will learn to implement these statistical measures for better business decision-making.

Assignment Steps

Resources: Week 5 Videos; Week 5 Readings; Statistics Lab

Tutorial help on Excel® and Word functions can be found on the Microsoft® Office website. There are also additional tutorials via the web offering support for Office products.

Prepare a 7- to 10-minute 11- to 15-slide Microsoft® PowerPoint® presentation for the senior management team based on the business problem or opportunity you described in Weeks 3-4.

Include on the slides what you would want the audience to see (include appropriate visual aids/layout) and include in the speakers notes section what you would say as you present each slide. If any source material is quoted or paraphrased in the presentation, use APA citations and references.

Draw on material you developed in the Weeks 3and 4 assignments.

Include the following in your presentation:

• Introduction slide

• Agenda slide

• Describe the organization, with a brief description

• Explain the business problem or opportunity

• Describe the hypothesis

• Analyze why the business problem is important

• Identify what variable would be best to measure for this problem and explain why

• Identify statistical methods used to analyze data

• Apply data analysis techniques to this problem (tell which techniques should be used: descriptive statistics, inferential stats, probability) and explain why

• Apply a possible solution to the problem/opportunity, with rationale

• Evaluate how data could be used to measure the implementation of such a solution

• Conclusion

• Reference slide (if any source material is quoted or paraphrased throughout the presentation)

Format your assignment consistent with APA guidelines.

Click the Assignment Files tab to submit your assignment.

1. This distribution has only one parameter. The curve is skewedto the right for small df and

becomes symmetric for large df. The entire distributioncurve lies to the right of the vertical

axis. The distribution assumes nonnegative values only

A. t distribution

B. Normal distribution

C. Chi-square distribution

D. Linear regression.

2. Find the value of x2 for 12 degrees of freedom and an area of .025 in the right tail of the chi-

square distribution curve. What is the value of chi-square? Round to three decimal places

3. Determine the value of x2 for 14 degrees of freedom and an area of .10 in the left tail of the

chi-square distribution curve. What is the value of chi-square? Round to three decimal places

4. Determine the value of x2 for 23 degrees of freedom and an area of .990 in the left tail of the

chi-square distribution curve. What is the value of chi-square? Round to three decimal places.

5. ? ____________ compares the observed frequencies from a multinomial experiment with

expected frequencies derived from a certain pattern or theoretical distribution. The test

evaluates how well the observed frequencies fit the expected frequencies.

A. Goodness-of-fit test

B. Chi-square test

C. Linear regression

6. The __________ are the frequencies obtained from the performance of a

multinomial experiment. The expected frequencies are the frequencies that we expect to obtain

if the null hypothesis is true.

A. Observed frequencies

B. Expected frequencies

C. Fluctuating frequencies

7. The expected frequency of a category is given by ? = npwhere n is the sample size and p is the

probability that an element belongs to that category if the null hypothesis is true.