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1. True or false. A set is any collection of objects.
2. True or false. A proper subset of a set is itself a subset of the set, but not vice versa.
3. True or false. The empty set is a subset of every set.
4. True or false. If A ∪ B = ∅ , then A = ∅ and B = ∅ .
5. True or false. If A ∩ B = ∅ , then A = ∅ or B = ∅ or bothA and B are empty sets.
6. True or false. (A ∪ Ac)c = ∅ .
7. True or false. [A ∩ (B ∪ C)]c= (A ∩ B)c ∩ (A ∩ C)c
8. True or false. n(A) + n(B) = n(A ∪ B) +n(A ∩ B)
9. True or false. If A ∈ B, then n(B) =n(A) + n(Ac ∩ B).
10. True or false. The number of permutations of n distinct objects taken all together is n!
11. True or false. P(n, r) = r! C(n, r).
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MAT 243 SNHU Python Scripts for the Module Six And Python Script Discussion
DISCUSSION 1: In this discussion you will be interpreting output from your Python Scripts for the Module Six Discussion. I ...
MAT 243 SNHU Python Scripts for the Module Six And Python Script Discussion
DISCUSSION 1: In this discussion you will be interpreting output from your Python Scripts for the Module Six Discussion. If you did not complete the Module Six discussion, please complete that before working on this assignment.Last week’s discussion involved development of a multiple regression model that used miles per gallon as a response variable. Weight and horsepower were predictor variables. You performed an overall F-test to evaluate the significance of your model. This week, you will evaluate the significance of individual predictors. You will use output of Python script from Module Six to perform individual t-tests for each predictor variable. Specifically, you will look at Step 5 of the Python script to answer all questions in the discussion this week.In your initial post, address the following items:Is at least one of the two variables (weight and horsepower) significant in the model? Run the overall F-test and provide your interpretation at 5% level of significance. See Step 5 in the Python script. Include the following in your analysis:Define the null and alternative hypothesis in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. (Hint: F-Statistic and Prob (F-Statistic) in the output).Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?What is the slope coefficient for the weight variable? Is this coefficient significant at 5% level of significance (alpha=0.05)? (Hint: Check the P-value, , for weight in Python output. Recall that this is the individual t-test for the beta parameter.) See Step 5 in the Python script.What is the slope coefficient for the horsepower variable? Is this coefficient significant at 5% level of significance (alpha=0.05)? (Hint: Check the P-value, , for horsepower in Python output. Recall that this is the individual t-test for the beta parameter.) See Step 5 in the Python script.What is the purpose of performing individual t-tests after carrying out the overall F-test? What are the differences in the interpretation of the two tests?What is the coefficient of determination of your multiple regression model from Module Six? Provide appropriate interpretation of this statistic. Be sure to clearly communicate your ideas using appropriate terminology. DISCUSSION 2Use the link in the Jupyter Notebook activity to access your MODULE 8 DISCUSSION Python script. In this discussion, you will apply the statistical concepts and techniques covered in this week's reading about one-way analysis of variance (ANOVA). An investment analyst is evaluating the 10-year mean return on investment for industry-specific exchange-traded funds (ETFs) for three sectors: financial, energy, and technology. The analyst obtains a random sample of 30 ETFs for each sector and calculates the 10-year return of each ETF. The analyst has provided you with this data set. Run Step 1 in the Python script to upload the data file.Using the sample data, perform one-way analysis of variance (ANOVA). Evaluate whether the average return of at least one of the industry-specific ETFs is significantly different. Use a 5% level of significance.In your initial post, address the following items:Define the null and alternative hypothesis in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. See Step 2 in the Python script.Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?Does a side-by-side boxplot of the 10-year returns of ETFs from the three sectors confirm your conclusion of the hypothesis test? Why or why not? See Step 3 in the Python script.Finally, be sure to review the Discussion Rubric (ATTACHED) to understand how you will be graded on this assignment.
Use of Statistical Tools
During our course we have explored a number of different statistical applications and tools. In this week's forum you are ...
Use of Statistical Tools
During our course we have explored a number of different statistical applications and tools. In this week's forum you are to share how you intend to use one or more of the tools that we have examined in our course. Be specific. Be sure to include a description of the situation, the way in which you will employ the statistical tool you have selected, and provide some commentary about why you think the approach you have selected is appropriate and will prove to be useful. This is your opportunity to consider--and then share--how you will employ the knowledge that you have gained during our course. I look forward to hearing from you.Please keep in mind that my evaluation of your post will be based on the extent to which you participated and fostered a positive and effective learning environment--for yourself and others. Your initial post(6 points) must contain comments regarding the rationale for using the specific statistical tool you have chosen and provide insights as to why that particular tool is appropriate.
Assignment 4
In this Assignment, you will be assessed based on the following outcome:
GB513-3: Predict business results by using quant ...
Assignment 4
In this Assignment, you will be assessed based on the following outcome:
GB513-3: Predict business results by using quantitative methods.
This Assignment requires you to use Excel in all three questions. Make sure you explain your
answers and provide the regression output tables for Questions 1 and 2.
Make sure to use the Unit 4 Assignment template from Course Documents when you turn in your
answers.
Question 1
Shown below are rental and leasing revenue figures for office machinery and equipment in the United
States over a 7-year period according to the U.S. Census Bureau. Use this data and the regression
tool in the data analysis tool pack to run a linear regression.
Based on the formula you get from the regression output, answer the following questions:
a) What is the forecast for the rental and leasing revenue for the year 2011?
b) How confident are you in this forecast? Explain your answer by citing the relevant metrics.
Year
Rental and
Leasing
($ millions)
2004 5,860
2005 6,632
2006 6,543
2007 5,952
2008 5,732
2009 5,423
2010 4,589
Question 2
Suppose a researcher gathered survey data from 19 employees and asked the employees to rate
their job satisfaction on a scale from 0 to 100 (with 100 being perfectly satisfied). Suppose the
following data represent the results of this survey. Assume that relationship with their supervisor is
rated on a scale from 0 to 50 (0 represents a poor relationship and 50 represents an excellent
relationship); overall quality of the work environment is rated on a scale from 0 to 100 (0 represents
poor work environment and 100 represents an excellent work environment); and opportunities for
GB513: Business Analytics
2 of 4
advancement is rated on a scale from 0 to 100 (0 represents no opportunities and 100 represents
excellent opportunities).
Answer the following questions:
a) What is the regression formula based on the results from your regression?
b) How reliable do you think the estimates will be based on this formula? Explain your answer by
citing the relevant metrics.
c) Are there any variables that do not appear to be good predictors of job satisfaction? How can
you tell?
d) If a new employee reports that her relationship with her supervisor is 40, rates her
opportunities for advancement to be at 30, finds the quality of the work environment to be at
75, and works 60 hours per week, what would you expect her job satisfaction score to be?
Job
satisfaction
Relationship
with
supervisor
Opportunities
for
advancement
Overall
quality of
work
environment
Total
hours
worked
per week
55 27 42 50 52
20 35 28 60 60
85 40 7 45 42
65 35 48 65 53
45 29 32 40 58
70 42 41 50 48
35 22 18 75 55
60 34 32 40 50
95 40 48 45 40
65 33 11 60 38
85 38 33 55 47
10 5 21 50 62
75 37 42 45 43
80 37 46 40 42
50 31 48 60 46
90 42 30 55 38
75 36 39 70 43
45 20 22 40 42
65 32 12 55 53
Question 3
GB513: Business Analytics
3 of 4
Investment analysts generally believe the interest rate on bonds is related to the prime interest rate
for loans.
a) Use the following data to construct a scatter graph and then fit a regression line to the data.
Report the regression formula and the r-squared values from the chart (right click on the data
points, select Add Trend line, and select options to show these metrics).
b) Do you think the bond rate can be predicted by the prime interest rate? Justify your answer
using the relevant metrics.
Prime
interest
rate
Bond
rate
5.0% 28.0%
12.0% 48.0%
9.0% 32.0%
1.5% 4.0%
0.4% 7.0%
11.0% 36.0%
6.0% 28.0%
2.0% 10.5%
Directions for submitting your Assignment
Make sure to use the Unit 4 Assignment template from Course Documents when you turn in your
answers. Submit your Assignment to the Unit 4 Dropbox.
Attached files to be done
I will attach the files that I would like done. If you could just write the answers out and take a picture of them that wo ...
Attached files to be done
I will attach the files that I would like done. If you could just write the answers out and take a picture of them that would be great. And for the multiple choice just write the correct answer. If there is anything else you need please just let me know. Thank you very much.
6 pages
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MAT 243 SNHU Python Scripts for the Module Six And Python Script Discussion
DISCUSSION 1: In this discussion you will be interpreting output from your Python Scripts for the Module Six Discussion. I ...
MAT 243 SNHU Python Scripts for the Module Six And Python Script Discussion
DISCUSSION 1: In this discussion you will be interpreting output from your Python Scripts for the Module Six Discussion. If you did not complete the Module Six discussion, please complete that before working on this assignment.Last week’s discussion involved development of a multiple regression model that used miles per gallon as a response variable. Weight and horsepower were predictor variables. You performed an overall F-test to evaluate the significance of your model. This week, you will evaluate the significance of individual predictors. You will use output of Python script from Module Six to perform individual t-tests for each predictor variable. Specifically, you will look at Step 5 of the Python script to answer all questions in the discussion this week.In your initial post, address the following items:Is at least one of the two variables (weight and horsepower) significant in the model? Run the overall F-test and provide your interpretation at 5% level of significance. See Step 5 in the Python script. Include the following in your analysis:Define the null and alternative hypothesis in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. (Hint: F-Statistic and Prob (F-Statistic) in the output).Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?What is the slope coefficient for the weight variable? Is this coefficient significant at 5% level of significance (alpha=0.05)? (Hint: Check the P-value, , for weight in Python output. Recall that this is the individual t-test for the beta parameter.) See Step 5 in the Python script.What is the slope coefficient for the horsepower variable? Is this coefficient significant at 5% level of significance (alpha=0.05)? (Hint: Check the P-value, , for horsepower in Python output. Recall that this is the individual t-test for the beta parameter.) See Step 5 in the Python script.What is the purpose of performing individual t-tests after carrying out the overall F-test? What are the differences in the interpretation of the two tests?What is the coefficient of determination of your multiple regression model from Module Six? Provide appropriate interpretation of this statistic. Be sure to clearly communicate your ideas using appropriate terminology. DISCUSSION 2Use the link in the Jupyter Notebook activity to access your MODULE 8 DISCUSSION Python script. In this discussion, you will apply the statistical concepts and techniques covered in this week's reading about one-way analysis of variance (ANOVA). An investment analyst is evaluating the 10-year mean return on investment for industry-specific exchange-traded funds (ETFs) for three sectors: financial, energy, and technology. The analyst obtains a random sample of 30 ETFs for each sector and calculates the 10-year return of each ETF. The analyst has provided you with this data set. Run Step 1 in the Python script to upload the data file.Using the sample data, perform one-way analysis of variance (ANOVA). Evaluate whether the average return of at least one of the industry-specific ETFs is significantly different. Use a 5% level of significance.In your initial post, address the following items:Define the null and alternative hypothesis in mathematical terms and in words.Report the level of significance.Include the test statistic and the P-value. See Step 2 in the Python script.Provide your conclusion and interpretation of the test. Should the null hypothesis be rejected? Why or why not?Does a side-by-side boxplot of the 10-year returns of ETFs from the three sectors confirm your conclusion of the hypothesis test? Why or why not? See Step 3 in the Python script.Finally, be sure to review the Discussion Rubric (ATTACHED) to understand how you will be graded on this assignment.
Use of Statistical Tools
During our course we have explored a number of different statistical applications and tools. In this week's forum you are ...
Use of Statistical Tools
During our course we have explored a number of different statistical applications and tools. In this week's forum you are to share how you intend to use one or more of the tools that we have examined in our course. Be specific. Be sure to include a description of the situation, the way in which you will employ the statistical tool you have selected, and provide some commentary about why you think the approach you have selected is appropriate and will prove to be useful. This is your opportunity to consider--and then share--how you will employ the knowledge that you have gained during our course. I look forward to hearing from you.Please keep in mind that my evaluation of your post will be based on the extent to which you participated and fostered a positive and effective learning environment--for yourself and others. Your initial post(6 points) must contain comments regarding the rationale for using the specific statistical tool you have chosen and provide insights as to why that particular tool is appropriate.
Assignment 4
In this Assignment, you will be assessed based on the following outcome:
GB513-3: Predict business results by using quant ...
Assignment 4
In this Assignment, you will be assessed based on the following outcome:
GB513-3: Predict business results by using quantitative methods.
This Assignment requires you to use Excel in all three questions. Make sure you explain your
answers and provide the regression output tables for Questions 1 and 2.
Make sure to use the Unit 4 Assignment template from Course Documents when you turn in your
answers.
Question 1
Shown below are rental and leasing revenue figures for office machinery and equipment in the United
States over a 7-year period according to the U.S. Census Bureau. Use this data and the regression
tool in the data analysis tool pack to run a linear regression.
Based on the formula you get from the regression output, answer the following questions:
a) What is the forecast for the rental and leasing revenue for the year 2011?
b) How confident are you in this forecast? Explain your answer by citing the relevant metrics.
Year
Rental and
Leasing
($ millions)
2004 5,860
2005 6,632
2006 6,543
2007 5,952
2008 5,732
2009 5,423
2010 4,589
Question 2
Suppose a researcher gathered survey data from 19 employees and asked the employees to rate
their job satisfaction on a scale from 0 to 100 (with 100 being perfectly satisfied). Suppose the
following data represent the results of this survey. Assume that relationship with their supervisor is
rated on a scale from 0 to 50 (0 represents a poor relationship and 50 represents an excellent
relationship); overall quality of the work environment is rated on a scale from 0 to 100 (0 represents
poor work environment and 100 represents an excellent work environment); and opportunities for
GB513: Business Analytics
2 of 4
advancement is rated on a scale from 0 to 100 (0 represents no opportunities and 100 represents
excellent opportunities).
Answer the following questions:
a) What is the regression formula based on the results from your regression?
b) How reliable do you think the estimates will be based on this formula? Explain your answer by
citing the relevant metrics.
c) Are there any variables that do not appear to be good predictors of job satisfaction? How can
you tell?
d) If a new employee reports that her relationship with her supervisor is 40, rates her
opportunities for advancement to be at 30, finds the quality of the work environment to be at
75, and works 60 hours per week, what would you expect her job satisfaction score to be?
Job
satisfaction
Relationship
with
supervisor
Opportunities
for
advancement
Overall
quality of
work
environment
Total
hours
worked
per week
55 27 42 50 52
20 35 28 60 60
85 40 7 45 42
65 35 48 65 53
45 29 32 40 58
70 42 41 50 48
35 22 18 75 55
60 34 32 40 50
95 40 48 45 40
65 33 11 60 38
85 38 33 55 47
10 5 21 50 62
75 37 42 45 43
80 37 46 40 42
50 31 48 60 46
90 42 30 55 38
75 36 39 70 43
45 20 22 40 42
65 32 12 55 53
Question 3
GB513: Business Analytics
3 of 4
Investment analysts generally believe the interest rate on bonds is related to the prime interest rate
for loans.
a) Use the following data to construct a scatter graph and then fit a regression line to the data.
Report the regression formula and the r-squared values from the chart (right click on the data
points, select Add Trend line, and select options to show these metrics).
b) Do you think the bond rate can be predicted by the prime interest rate? Justify your answer
using the relevant metrics.
Prime
interest
rate
Bond
rate
5.0% 28.0%
12.0% 48.0%
9.0% 32.0%
1.5% 4.0%
0.4% 7.0%
11.0% 36.0%
6.0% 28.0%
2.0% 10.5%
Directions for submitting your Assignment
Make sure to use the Unit 4 Assignment template from Course Documents when you turn in your
answers. Submit your Assignment to the Unit 4 Dropbox.
Attached files to be done
I will attach the files that I would like done. If you could just write the answers out and take a picture of them that wo ...
Attached files to be done
I will attach the files that I would like done. If you could just write the answers out and take a picture of them that would be great. And for the multiple choice just write the correct answer. If there is anything else you need please just let me know. Thank you very much.
6 pages
Mba501 Excel Template 2015
NEWS understands the issues that they must overcome in terms of quality, speed, and NEWS believes that the analysis that y ...
Mba501 Excel Template 2015
NEWS understands the issues that they must overcome in terms of quality, speed, and NEWS believes that the analysis that your team has provided in the ...
3 pages
Unit 5 Project
1. A projectile is fired upward from the ground with an initial velocity of 300 feet per second. Neglecting air resistance ...
Unit 5 Project
1. A projectile is fired upward from the ground with an initial velocity of 300 feet per second. Neglecting air resistance, the height of the ...
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