#### Description of this paper

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Step-by-step Instant Solution

Question

• Perform certain calculations discussed in the assigned reading in order to derive an answer for each problem.
• use Microsoft Excel to complete each problem and submit a single Excel spreadsheet that contains a separate worksheet (i.e., separate tab) for each problem.
• have each worksheet be clearly labeled to identify the associated problem.
• to show all calculations or other work performed to derive your answer(s) for each problem.
• have your spreadsheet be fully functional (i.e., configured to allow the reader to not only see all numerical values, but also be able to see the underlying formula associated with each calculated value).
• to label your work in each worksheet to clearly identify the nature of each piece of data or calculated value.

No credit will be granted for problems that are not completed using Excel, for which your Excel worksheet is not fully functional, or for which you have not shown all of the calculations or other work performed to derive your answer(s). You may refer to the course textbooks, supplemental reading materials, online information, and your own notes in conjunction with completing the homework assignments.? Once you have completed the necessary calculations to solve each problem and answer the associated questions, select the hyperlink provided to submit your Excel spreadsheet for grading.

A college Admissions Officer is interested in determining the extent to which a prospective student?s high school GPA and/or SAT score can be used as a basis for predicting his or her college freshman GPA.? He believes that prospective students who have higher high school GPAs and SAT scores will have a higher college freshman GPA.? He randomly selected fifty students who recently completed their freshman year and collected the information reflected in the following table.

 Student No. College Freshman GPA High School GPA SAT Score 1 2.61 3.26 978 2 2.40 2.92 905 3 2.95 3.52 1125 4 3.34 3.88 1280 5 3.40 3.86 1313 6 3.56 3.95 1383 7 2.59 2.82 1014 8 3.09 3.29 1217 9 3.68 3.84 1458 10 2.91 2.97 1157 11 2.48 3.09 1238 12 2.34 2.85 856 13 2.38 2.84 880 14 2.58 3.00 959 15 2.70 3.06 1011 16 2.54 2.82 959 17 2.89 3.14 1100 18 3.02 3.21 1156 19 3.33 3.46 1282 20 3.16 3.23 1227 21 2.60 3.25 1266 22 2.65 3.23 1291 23 3.27 3.89 1168 24 2.89 3.36 1041 25 2.91 3.31 1060 26 2.85 3.16 1044 27 3.65 3.97 1350 28 3.54 3.77 1319 29 3.83 3.99 1436 30 3.05 3.11 1150 31 3.15 3.94 1498 32 2.35 2.86 1117 33 3.06 3.65 1458 34 3.25 3.78 1134 35 3.49 3.97 1230 36 3.02 3.36 1075 37 2.91 3.16 1043 38 3.48 3.70 1258 39 3.09 3.22 1128 40 3.66 3.73 1343 41 2.31 2.89 1069 42 2.49 3.04 1154 43 2.42 2.88 1122 44 2.78 3.23 1292 45 2.98 3.38 1015 46 3.07 3.41 1058 47 2.99 3.25 1039 48 3.74 3.98 1314 49 2.73 2.85 969 50 3.02 3.08 1077

• Perform a simple linear regression with a 95% confidence level using college freshman GPA as the dependent variable and high school GPA as the independent variable.
• Evaluate the statistical significance of the regression model.
• Perform a simple linear regression with a 95% confidence using college freshman GPA as the dependent variable and SAT score as the independent variable.
• Evaluate the statistical significance of the regression model.
• Compare the two simple linear regression models and select your preferred simple regression model.
• Explain the basis for selecting your preferred model.
• Perform a multiple linear regression with a 95% confidence using college freshman GPA as the dependent variable and high school GPA and SAT score as the independent variables.
• Evaluate the statistical significance of the regression model as a whole.
• Evaluate the statistical significance of the linear relationship between the dependent variable and each independent variable.
• Discuss the extent to which there is evidence of multicollinearity between the independent variables.
• Compare your preferred simple linear regression model (i.e., the regression model you selected in step 3) to the multiple linear regression model and discuss whether the simple regression model or multiple regression model would be your overall preferred regression model, including discussing the basis for why it would be your preferred model.
• Discuss the contribution of each independent variable for your overall preferred regression model (i.e., the model you selected in step 5) to predicting the value of the dependent variable.
• Discuss the range of values for the independent variable(s) for your preferred regression model (i.e., the regression model you selected in step 5) for which the regression model is valid.
• Discuss the p-value for the coefficient for the y-intercept for your overall preferred regression model.? Explain why a p-value that is not less than or equal to ? = 0.05 would not be cause for rejecting the regression model.? (Hint: Consider the range of values for the independent variables associated with the given data set.)
• Identify the regression equation associated with your overall preferred regression model and associated degree of error associated with using the model to predict a student?s college freshman GPA.
• Calculate the predicted college freshman GPA for a student with a high school GPA of 3.25 and an SAT score of 1115 using your overall preferred regression model.
• Identify the lower and upper limits associated with a 95% confidence level interval estimate for the predicted college freshman GPA for a student with a high school GPA of 3.25 and an SAT score of 1115 using your overall preferred regression model.

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College Freshman GPA

2.61

2.4

2.95

3.34...

Paper#9255594 | Written in 27-Jul-2016

Price : \$22