Homework Answers
The sample of students was obtained randomly
The sample size is too large
There seems to be curved or non linear pattern in residual
There is no pattern in residual
The residual seem to.vary more for lower MATH SAT SCORES
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Use the following for questions 21-27 The following is software output from a regression analysis on...
6. Interpreting statistical software output in regression Aa Aa Suppose you work in the admission...
6. Interpreting statistical software output in regression Aa Aa Suppose you work in the admissions department of a small liberal arts college. You wonder if you can predict students' college grade point averages (GPAs) by their SAT scores. You randomly select 50 recent graduates and collect their SAT scores and college GPAs. You use a statistical software package to run a regression predicting college GPA from SAT score. Use the following output to answer the questions that follovw Descriptive Statistics...
The data from the sample were used to produce the following computer output (using R software):...
The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 (Intercept) HoursPlaying 0.0000 44.84 -18.85 0.0079 0.0000 Analysis of Variance Table Response: GPA DF Mean Sq F value Prob 1 Sum Sa 21.4263 1.9935 21.4263 354.69 HoursPlaying Residuals 0.0000 33 0.0604 2d. Identify the regression model generated from the sample data. Include...
The data from the sample were used to produce the following computer output (using R software):...
The data from the sample were used to produce the following computer output (using R software): mean sd n 2.6923 0.8300 35 GPA Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 44.84 (Intercept) HoursPlaying 0.0000 0.0079 -18.85 0.0000 Analysis of Variance Table Response: GPA DF F value Prob 1 Sum Sa 21.4263 1.9935 Mean Sq 21.4263 0.0604 HoursPlaying Residuals 354.69 0.0000 33 2b. Calculate the correlation between GPA and the amount of time...
The data from the sample were used to produce the following computer output (using R software):...
The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 (Intercept) HoursPlaying 0.0000 44.84 -18.85 0.0079 0.0000 Analysis of Variance Table Response: GPA DF Mean Sq F value Prob 1 Sum Sa 21.4263 1.9935 21.4263 354.69 HoursPlaying Residuals 0.0000 33 0.0604 2e. One of the students in the study reported playing video...
The data from the sample were used to produce the following computer output (using R software):...
The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 (Intercept) HoursPlaying 0.0000 44.84 -18.85 0.0079 0.0000 Analysis of Variance Table Response: GPA DF Mean Sq F value Prob 1 Sum Sa 21.4263 1.9935 21.4263 354.69 HoursPlaying Residuals 0.0000 33 0.0604 28. The researcher wanted to test if it makes sense to...
The data from the sample were used to produce the following computer output (using R software):...
The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 (Intercept) HoursPlaying 0.0000 44.84 -18.85 0.0079 0.0000 Analysis of Variance Table Response: GPA DF Mean Sq F value Prob 1 Sum Sa 21.4263 1.9935 21.4263 354.69 HoursPlaying Residuals 0.0000 33 0.0604 28. The researcher wanted to test if it makes sense to...
2f. Should we use the regression model in part d to predict the GPA for an...
2f. Should we use the regression model in part d to predict the GPA for an undergraduate who plays video games 27 hours per week? Clearly explain your answer in context using complete sentences. 12pt Paragraph BI U AX & Tev ... The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967...
2h. What is your decision regarding the hypothesis test? Use the information from the computer output...
2h. What is your decision regarding the hypothesis test? Use the information from the computer output and complete sentences in context to support your answer. Include the correct statistical notation. 12pt Paragraph BI U ALTv The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 (Intercept) HoursPlaying 0.0000 44.84 -18.85 0.0079 0.0000...
QUESTION 19 For the following software output, check each assumption/condition to run linear regression and state...
QUESTION 19 For the following software output, check each assumption/condition to run linear regression and state whether it is appropriate to use linear regression. Bivariate Fit of pluto By alpha 20 15 10 5 0 e 0.05 0.15 C 0.1 alpha Linear Fit Linear Fit pluto -0.597417 16543195*alpha Summary of Fit RSquare RSquare Adj Root Mean Square Error Mean of Response Observations (or Sum Wgts) 0.915999 0.911999 2.172963 6.73913 23 Analysis of Variance Sum of DF Squares Mean Square Source...
You must attempt all questions. You must use Minitab and/or Excel to solve all questions. Show...
You must attempt all questions. You must use Minitab and/or Excel to solve all questions. Show all of your works. State your hypothesis if required, Do NOT give the numerical final answer only, you MUST comment on all of your final finding. If required, use ?=0.05 for all the tests. Q1) 10 points A study of speeding violations and drivers who use cell phones produced the following fictional data: Speeding ticket No speeding ticket Uses cell phone while driving 40...
6. Interpreting statistical software output in regression Aa Aa Suppose you work in the admissions department of a small liberal arts college. You wonder if you can predict students' college grade point averages (GPAs) by their SAT scores. You randomly select 50 recent graduates and collect their SAT scores and college GPAs. You use a statistical software package to run a regression predicting college GPA from SAT score. Use the following output to answer the questions that follovw Descriptive Statistics...
The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 (Intercept) HoursPlaying 0.0000 44.84 -18.85 0.0079 0.0000 Analysis of Variance Table Response: GPA DF Mean Sq F value Prob 1 Sum Sa 21.4263 1.9935 21.4263 354.69 HoursPlaying Residuals 0.0000 33 0.0604 2d. Identify the regression model generated from the sample data. Include...
The data from the sample were used to produce the following computer output (using R software): mean sd n 2.6923 0.8300 35 GPA Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 44.84 (Intercept) HoursPlaying 0.0000 0.0079 -18.85 0.0000 Analysis of Variance Table Response: GPA DF F value Prob 1 Sum Sa 21.4263 1.9935 Mean Sq 21.4263 0.0604 HoursPlaying Residuals 354.69 0.0000 33 2b. Calculate the correlation between GPA and the amount of time...
The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 (Intercept) HoursPlaying 0.0000 44.84 -18.85 0.0079 0.0000 Analysis of Variance Table Response: GPA DF Mean Sq F value Prob 1 Sum Sa 21.4263 1.9935 21.4263 354.69 HoursPlaying Residuals 0.0000 33 0.0604 2e. One of the students in the study reported playing video...
The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 (Intercept) HoursPlaying 0.0000 44.84 -18.85 0.0079 0.0000 Analysis of Variance Table Response: GPA DF Mean Sq F value Prob 1 Sum Sa 21.4263 1.9935 21.4263 354.69 HoursPlaying Residuals 0.0000 33 0.0604 28. The researcher wanted to test if it makes sense to...
The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 (Intercept) HoursPlaying 0.0000 44.84 -18.85 0.0079 0.0000 Analysis of Variance Table Response: GPA DF Mean Sq F value Prob 1 Sum Sa 21.4263 1.9935 21.4263 354.69 HoursPlaying Residuals 0.0000 33 0.0604 28. The researcher wanted to test if it makes sense to...
2f. Should we use the regression model in part d to predict the GPA for an undergraduate who plays video games 27 hours per week? Clearly explain your answer in context using complete sentences. 12pt Paragraph BI U AX & Tev ... The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967...
2h. What is your decision regarding the hypothesis test? Use the information from the computer output and complete sentences in context to support your answer. Include the correct statistical notation. 12pt Paragraph BI U ALTv The data from the sample were used to produce the following computer output (using R software): mean sd n GPA 2.6923 0.8300 35 Hours Playing 11.0429 5.3322 35 Coefficients: Std Error t value Prob Estimate 4.3363 -0.1489 0.0967 (Intercept) HoursPlaying 0.0000 44.84 -18.85 0.0079 0.0000...
QUESTION 19 For the following software output, check each assumption/condition to run linear regression and state whether it is appropriate to use linear regression. Bivariate Fit of pluto By alpha 20 15 10 5 0 e 0.05 0.15 C 0.1 alpha Linear Fit Linear Fit pluto -0.597417 16543195*alpha Summary of Fit RSquare RSquare Adj Root Mean Square Error Mean of Response Observations (or Sum Wgts) 0.915999 0.911999 2.172963 6.73913 23 Analysis of Variance Sum of DF Squares Mean Square Source...
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