Prof Eliud – Statistics

2 assignments; One is attached the other is copied and pasted

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 an 11 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 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
Explain the business problem or opportunity
Analyze why the business problem is important
Identify what variable(s) 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.

Title

ABC/

23 Version X

Practice Set 5

QNT/275 Version 6

University of Phoenix Material

Practice Set 5
Practice Set 5

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

becomes symmetric for large df. The entire distribution curve 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 = np where 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 independent and 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 dependent variable. 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

Practice Set 5

QNT/275 Version 6

2017

by University of Phoenix
. All rights reserved.

University of Phoenix Material

Practice S
et 5

Practice Set

1. This distribution
has

only

one

parameter
.

The

curve

skewed

the

right

for

small

and

becomes

symmetric

for

large

df
.

The entire

distribution

curve

lies

the

right

the

vertical

axis.

The

distribution

assumes
nonnegative

values

only

t distribution

Normal distribution

Chi
–
square distribution

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 c
urve. 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 tes
t

evaluates how well the observed frequencies fit the expected frequencies.

Goodness
–
of
–
fit test

Chi
–
square test

Linear regression

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

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

if the null hypothesis is true.

Observed frequencies

Expected frequencies

Fluctuating frequencies

7. The expected frequency of a category is given by Ε = np where 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 a
re k
–

1, where k denotes the number of possible

Practice Set 5
QNT/275 Version 6
1

Practice Set 5

1. This distribution has only one parameter. The curve is skewed to the right for small df and
becomes symmetric for large df. The entire distribution curve 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 = np where 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

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