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Determine the rate at which Cara traveled during the second part of her trip.Cara drives for 4 hours at a rate of 45 miles per hour. Later, she
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data in csv format , will give later.Hill running is a long-standing Scottish tradition, dating back to 1040. The races ta ...
GWU Hill Running Regression Worksheet
data in csv format , will give later.Hill running is a long-standing Scottish tradition, dating back to 1040. The races take place at various times of year throughout Scotland. The data set (scottish_hill_races.csv) posted on Blackboard contains recent information from 90 races regarding Distance (in kilometers), Climb (in meters), Time (record time in minutes), and Sex (1 for women and 0 for men).a) Find the equation of the estimated simple linear regression function that predicts Time based on Distance.b) Plot the data with regression function found in part a). Distinguish between data points for Women and data points for Men and include a key (legend).c) Now fit the first-order regression model that predicts Time based on Distance and Sex. Provide the equation.d) Plot Time against Distance with the two separate regression functions based on Sex (one for Women and one for Men). You also need to include the equations of the two regression functions.e) Find the joint confidence intervals for the slopes with a family (Bonferroni adjusted) confidence level of 98%. Include an interpretation of each.f) Test whether Sex should be dropped from the model while Distance is retained. Include the hypotheses, test-statistic, p-value, and conclusions.g) Finally, let us consider the model that predicts Time based on Distance and Sex with interaction. Provide the equation.h) Now test whether Sex should be dropped from the model while Distance and the interaction term are retained. Include the hypotheses, test-statistic, p-value, and conclusions.i) Report the final model with Sex dropped. Does this improve upon the model found in part d)? Explain.2. Continue with the data set scottish_hill_races.csv.a) Fit the first-order regression model that predicts Time based on all potential predictors- Distance Climb, and Sex. Provide the equation.b) Construct a 95% prediction interval for the time it takes a woman to complete a 10 km race with a “climb” of 500 meters.c) Perform an exhaustive search for the “best” subsets of predictors. Which model was chosen as “best” for one predictor? Was it the one we examined in #1? How about for the “best” model with two predictors? Is it the one we examined in #1?d) Examine important criteria for the three “best” models chosen in c). Which model(s) should be included for final consideration based on them?e) Use forward stepwise selection with partial 𝐹-tests and α-to-enter= 0.01. Then use backward stepwise selection with partial 𝐹-tests and α-to-remove= 0.01. Which model is chosen as “best” in each case?f) Considering all results, which model(s) should be considered? Assess the predictive ability of the model(s) by splitting the data into training and testing (sample size 𝑛 = 40) subsets and estimating the mean squared prediction error 𝑀𝑆𝑃𝐸.g) Is there any indication of nonlinear relationships between Time and any of the quantitative predictors? Explain.h) Using basic diagnostics, is there any evidence of multicollinearity?i) Find the variance inflation factors for the quantitative predictors. Explain
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Rasmussen College Fundraising Solving Using Substitution Method Problems
Review the slideshow assignment. After reviewing the slideshow, answer the three questions provided. Remember to type and ...
Rasmussen College Fundraising Solving Using Substitution Method Problems
Review the slideshow assignment. After reviewing the slideshow, answer the three questions provided. Remember to type and save your assignment as a Microsoft Word document and show all your work and explanations.Submit your completed assignment by following the directions linked below. Please check the Course Calendar for specific due dates.Save your assignment as a Microsoft Word document. (Mac users, please remember to append the ".docx" extension to the filename.)
GWU Hill Running Regression Worksheet
data in csv format , will give later.Hill running is a long-standing Scottish tradition, dating back to 1040. The races ta ...
GWU Hill Running Regression Worksheet
data in csv format , will give later.Hill running is a long-standing Scottish tradition, dating back to 1040. The races take place at various times of year throughout Scotland. The data set (scottish_hill_races.csv) posted on Blackboard contains recent information from 90 races regarding Distance (in kilometers), Climb (in meters), Time (record time in minutes), and Sex (1 for women and 0 for men).a) Find the equation of the estimated simple linear regression function that predicts Time based on Distance.b) Plot the data with regression function found in part a). Distinguish between data points for Women and data points for Men and include a key (legend).c) Now fit the first-order regression model that predicts Time based on Distance and Sex. Provide the equation.d) Plot Time against Distance with the two separate regression functions based on Sex (one for Women and one for Men). You also need to include the equations of the two regression functions.e) Find the joint confidence intervals for the slopes with a family (Bonferroni adjusted) confidence level of 98%. Include an interpretation of each.f) Test whether Sex should be dropped from the model while Distance is retained. Include the hypotheses, test-statistic, p-value, and conclusions.g) Finally, let us consider the model that predicts Time based on Distance and Sex with interaction. Provide the equation.h) Now test whether Sex should be dropped from the model while Distance and the interaction term are retained. Include the hypotheses, test-statistic, p-value, and conclusions.i) Report the final model with Sex dropped. Does this improve upon the model found in part d)? Explain.2. Continue with the data set scottish_hill_races.csv.a) Fit the first-order regression model that predicts Time based on all potential predictors- Distance Climb, and Sex. Provide the equation.b) Construct a 95% prediction interval for the time it takes a woman to complete a 10 km race with a “climb” of 500 meters.c) Perform an exhaustive search for the “best” subsets of predictors. Which model was chosen as “best” for one predictor? Was it the one we examined in #1? How about for the “best” model with two predictors? Is it the one we examined in #1?d) Examine important criteria for the three “best” models chosen in c). Which model(s) should be included for final consideration based on them?e) Use forward stepwise selection with partial 𝐹-tests and α-to-enter= 0.01. Then use backward stepwise selection with partial 𝐹-tests and α-to-remove= 0.01. Which model is chosen as “best” in each case?f) Considering all results, which model(s) should be considered? Assess the predictive ability of the model(s) by splitting the data into training and testing (sample size 𝑛 = 40) subsets and estimating the mean squared prediction error 𝑀𝑆𝑃𝐸.g) Is there any indication of nonlinear relationships between Time and any of the quantitative predictors? Explain.h) Using basic diagnostics, is there any evidence of multicollinearity?i) Find the variance inflation factors for the quantitative predictors. Explain
8 pages
Spss Solution
6. Use the correct bivariate statistical test to examine the relationship between the Instit_Confid index (the index you c ...
Spss Solution
6. Use the correct bivariate statistical test to examine the relationship between the Instit_Confid index (the index you created in question 3) and ...
Precalculus: Analytic Geometry and Algebra - Project 3
I am needing help with my project 3 in Precalculus: Analytic Geometry and Algebra. Needing it by Saturday, June 23rd. Mu ...
Precalculus: Analytic Geometry and Algebra - Project 3
I am needing help with my project 3 in Precalculus: Analytic Geometry and Algebra. Needing it by Saturday, June 23rd. Much appreciated.
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CXU9ACreate a research question using the General Social Survey that can be answered by multiple regression.What is your r ...
Multiple Regression
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UCLA Statistical Significance Meaningfulness & Confidence Level Discussion
To prepare for this Discussion: Review the Learning Resources related to hypothesis testing, meaningfulness, and statisti ...
UCLA Statistical Significance Meaningfulness & Confidence Level Discussion
To prepare for this Discussion: Review the Learning Resources related to hypothesis testing, meaningfulness, and statistical significance.Review Magnusson’s web blog found in the Learning Resources to further your visualization and understanding of statistical power and significance testing.Review the American Statistical Association’s press release and consider the misconceptions and misuse of p-values.Consider the scenario:A research paper claims a meaningful contribution to the literature based on finding statistically significant relationships between predictor and response variables. In the footnotes, you see the following statement, “given this research was exploratory in nature, traditional levels of significance to reject the null hypotheses were relaxed to the .10 level.” Post your response to the scenario in which you critically evaluate this footnote. As a reader/reviewer, what response would you provide to the authors about this footnote?
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