Description
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.
Explanation & Answer
C
......................................
Completion Status:
100%
Review
Review
Anonymous
Awesome! Made my life easier.
Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4
24/7 Homework Help
Stuck on a homework question? Our verified tutors can answer all questions, from basic math to advanced rocket science!
Most Popular Content
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.
Something in My Personal Life that I Measure Regularly Discussion
By now you are adept at calculating averages and intuitively can estimate whether something is “normal” (a measurement ...
Something in My Personal Life that I Measure Regularly Discussion
By now you are adept at calculating averages and intuitively can estimate whether something is “normal” (a measurement not too far from average) or unusual (pretty far from the average you might expect). This class helps to quantify exactly how far something you measure is from average using the normal distribution. Basically, you mark the mean down the middle of the bell curve, calculate the standard deviation of your sample and then add (or subtract) that value to come up with the mile markers (z scores) that measure the distance from the mean.
For example, if the average height of adult males in the United States is 69 inches with a standard deviation of 3 inches, we could create the graph below.
Men who are somewhere between 63 and 75 inches tall would be considered of a fairly normal height. Men shorter than 63” or taller than 75” would be considered unusual (assuming our sample data represents the actual population). You could use a z score to look up exactly what percentage of men are shorter than (or taller than) a particular height.
Think of something in your work or personal life that you measure regularly (No actual calculation of the mean, standard deviation or z scores is necessary). What value is “average”? What values would you consider to be unusually high or unusually low? If a value were unusually high or low—how would it change your response to the measurement?
MM 305 Purdue Global University Statistics and Quantitative Analysis Discussion
Visit the dataset link to view the datasets that accompany our textbook. Review the dataset titles and select a data set o ...
MM 305 Purdue Global University Statistics and Quantitative Analysis Discussion
Visit the dataset link to view the datasets that accompany our textbook. Review the dataset titles and select a data set of interest to you. (Note: You may need to use more than one data set to complete this Discussion.) State the dataset that you selected. For each variable in your data, identify it as either qualitative or quantitative. (If your dataset does not have both types of variables, please pick an additional dataset to share at least one qualitative and one quantitative variable.)Select one of your quantitative variables and determine whether it is discrete or continuous. (Please do not select the same variable as a classmate.)For that same variable create a frequency distribution table including frequency, relative frequency and cumulative relative frequency. Copy and paste the table directly into your discussion post or attach it as a separate file.Please let me know if the links don't work so I can get you the datasets needed
10 pages
Project One Submission
1. Describe the report: Give a brief description of the purpose of your report. The study’s purpose is to determine medi ...
Project One Submission
1. Describe the report: Give a brief description of the purpose of your report. The study’s purpose is to determine median housing prices based on ...
HAP 602 GMU W 5 AA Spouse Depression Case Study
HAP 602 Statistics for Health Services Management Assignment Overview: Case Study 2Question 5 requires data to be formatte ...
HAP 602 GMU W 5 AA Spouse Depression Case Study
HAP 602 Statistics for Health Services Management Assignment Overview: Case Study 2Question 5 requires data to be formatted in a suggested way in order for a 2 way ANOVA to be run. How did you format the data and run the ANOVA?I'm stuck on this part of the assignment and need help a.s.a.p.Thanks,David52
Similar Content
Testing for Correlation and Bivariate Regression analysis
To prepare for this Assignment:Review this week’s Learning Resources and media program related to regression and correla...
Math word problem help needed
Barry spent 14 of his monthly salary for rent and 17 of his monthly salary for his utility bill. If&nb...
the question is down below.
What is the simplified form of V 2.1???
xx
х
...
Themes in epidemiology, statistics
Read
the article and utilize the content
for your discussion. (REFER TO ATTACHED ARTICLE)
respond to th...
Ashford University Library of Congress Worksheet
The following are the ages of a group of tourists visiting The Library of Congress: 36, 38, 33, 44, 37, 37, 38, 34, 34, 36...
Mymathlab homework, math homework help
I have a homework...
Attachment
The waiting times for commuters on the Red Line during peak rush hours follow a a) State the random variable in the contex...
Tutor Soh Cah Toa Question
I use SOH CAH TOA to help me remember. When talking about opposite and adjacent it is in reference to the angle you have b...
Ie 3301 Project
I ……………………………………………………………….did not give or receive any assistance on this ...
Related Tags
Book Guides
The Handmaids Tale
by Margaret Atwood
Twelve Years A Slave
by Solomon Northrup
The House of the Seven Gables
by Nathaniel Hawthorne
Cat on a Hot Tin Roof
by Tennessee Williams
Mrs Dalloway
by Virginia Woolf
Enders Game
by E. M. Forster
All Quiet on the Western Front
by Erich Maria Remarque
Beowulf
by Anonymous Anglo-Saxon poet
The Metamorphosis
by Franz Kafka
Get 24/7
Homework help
Our tutors provide high quality explanations & answers.
Post question
Most Popular Content
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.
Something in My Personal Life that I Measure Regularly Discussion
By now you are adept at calculating averages and intuitively can estimate whether something is “normal” (a measurement ...
Something in My Personal Life that I Measure Regularly Discussion
By now you are adept at calculating averages and intuitively can estimate whether something is “normal” (a measurement not too far from average) or unusual (pretty far from the average you might expect). This class helps to quantify exactly how far something you measure is from average using the normal distribution. Basically, you mark the mean down the middle of the bell curve, calculate the standard deviation of your sample and then add (or subtract) that value to come up with the mile markers (z scores) that measure the distance from the mean.
For example, if the average height of adult males in the United States is 69 inches with a standard deviation of 3 inches, we could create the graph below.
Men who are somewhere between 63 and 75 inches tall would be considered of a fairly normal height. Men shorter than 63” or taller than 75” would be considered unusual (assuming our sample data represents the actual population). You could use a z score to look up exactly what percentage of men are shorter than (or taller than) a particular height.
Think of something in your work or personal life that you measure regularly (No actual calculation of the mean, standard deviation or z scores is necessary). What value is “average”? What values would you consider to be unusually high or unusually low? If a value were unusually high or low—how would it change your response to the measurement?
MM 305 Purdue Global University Statistics and Quantitative Analysis Discussion
Visit the dataset link to view the datasets that accompany our textbook. Review the dataset titles and select a data set o ...
MM 305 Purdue Global University Statistics and Quantitative Analysis Discussion
Visit the dataset link to view the datasets that accompany our textbook. Review the dataset titles and select a data set of interest to you. (Note: You may need to use more than one data set to complete this Discussion.) State the dataset that you selected. For each variable in your data, identify it as either qualitative or quantitative. (If your dataset does not have both types of variables, please pick an additional dataset to share at least one qualitative and one quantitative variable.)Select one of your quantitative variables and determine whether it is discrete or continuous. (Please do not select the same variable as a classmate.)For that same variable create a frequency distribution table including frequency, relative frequency and cumulative relative frequency. Copy and paste the table directly into your discussion post or attach it as a separate file.Please let me know if the links don't work so I can get you the datasets needed
10 pages
Project One Submission
1. Describe the report: Give a brief description of the purpose of your report. The study’s purpose is to determine medi ...
Project One Submission
1. Describe the report: Give a brief description of the purpose of your report. The study’s purpose is to determine median housing prices based on ...
HAP 602 GMU W 5 AA Spouse Depression Case Study
HAP 602 Statistics for Health Services Management Assignment Overview: Case Study 2Question 5 requires data to be formatte ...
HAP 602 GMU W 5 AA Spouse Depression Case Study
HAP 602 Statistics for Health Services Management Assignment Overview: Case Study 2Question 5 requires data to be formatted in a suggested way in order for a 2 way ANOVA to be run. How did you format the data and run the ANOVA?I'm stuck on this part of the assignment and need help a.s.a.p.Thanks,David52
Earn money selling
your Study Documents