Reference no: EM131546625

Statistics Assignment

Purpose of Assignment

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

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.

Include on the slides what you would want the audience to see (include appropriate visual aids/layout) and include in the speaker's 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 Week's 3 and 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.

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. Α ____________ 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 Ε = npwhere n is the sample size and p is the probability that an element belongs to that category if the null hypothesis is true. The ________ for a goodness-of-fit test are k - 1, where k denotes the number of possible outcomes (or categories) for the experiment.
A. Number of observations
B. Degrees of freedom
C. Total population

8. This model includes only two variables, one independentand one dependent, is called a _____1______. The___2____ is the one being explained, and the ___3___ is the one used to explain the variation in the dependentvariable. Select the correct letter that would make the sentence true.
1. Select a letter from the list to make this statement true.
2. Select a letter from the list to make this statement true.
3. Select a letter from the list to make this statement true.
A. Linear model
B. Qualitative variable
C. Multivariate analysis of variance
D. Independent variable
E. Simple regression model
F. One-way Analysis of Variance
G. Dependent variable
H. Quantitative variable

9. A population data set produced the following information.

N=460, ∑x=3920, ∑y=2650, ∑xy=26,570, ∑x2=48,530

Find the population regression line. Round to three decimal places. Use the format as an example when submitting your equation 456.123 + 789.123x

10. The following information is obtained from a sample data set.

n=12, ∑x=66, ∑y=588, ∑xy=2244, ∑x2=396

Find the estimated regression line Use this format as an example when submitting your equation 123 - 45x.

Attachment:- Part-1-and-2.rar