statistic 222222

Passing Rate for the 12th Grade Proficiency Examination – c. 1995

This project is a regression study done on the rate at which students in schools in northwest Ohio passed the 12th grade proficiency examinations about the year 1995. (This is the year for which I have data.) The data comprises 8 variables for 88 districts. 6 additional school districts’ data has been placed at the right of the sheet. These have been removed from the data because they are outliers. A detailed description of the variables in the data set is below, and the data file is in the web portal. Your job is to do a regression analysis, and then think about the results and draw conclusions.

This project will contain at most 8 pages

Use the “Project 2 Data Schools file to complete the following:

1. Using the data in the Property Values Data sheet, produce a scatter plot with the passing rate as the response variable and the ‘Average Property Values in the District’ as the explanatory variable. Print as page 3.

2. Repeat Step 2. using the ‘Welfare Rate’ as the explanatory variable in the Welfare Rate Data sheet. Print as page 4.

3. Repeat Step 2. using the ‘Average Daily Attendance Rate’ as the explanatory variable in the Attendance Data sheet. Print as page 5.

4. Run a simple regression with the passing rate as the response variable and ‘Average Property Values in the District’ as the explanatory variable.

On the Results sheet :

Indicate the correlation coefficient (R)

Interpret the coefficient of determination (R²)

Interpret the significance

Give the linear regression equation

Use the regression equation to predict one passing rate value.

Note: These can be written by hand on the printouts, or typed into the sheet before printing. Print this as page 6.

5. Run a simple regression with the passing rate as the response variable and ‘Welfare Rate’ as the explanatory variable.

On the Results sheet :

Indicate the correlation coefficient (R)

Interpret the coefficient of determination (R²)

Interpret the significance

Give the linear regression equation

Use the regression equation to predict one passing rate value.

Note: These can be written by hand on the printouts, or typed into the sheet before printing. Print this as page 7.

6. Run a simple regression with the passing rate as the response variable and ‘Average Daily Attendance Rate’ as the explanatory variable.

On the Results sheet :

Indicate the correlation coefficient (R)

Interpret the coefficient of determination (R²)

Interpret the significance

Give the linear regression equation

Use the regression equation to predict one passing rate value.

Note: These can be written by hand on the printouts, or typed into the sheet before printing. Print this as page 8.

Report your findings:

Submit a typewritten 6-paragraph summary of the assignment and your findings. The summary should be formatted with one paragraph each for the introduction and conclusion and one paragraph of ANALYSIS/INTERPRETATION for each of the four questions below. Attach a copy of the EXCEL printouts to the report.

The questions you are asked to consider are:

➢ Which of the three possible explanatory variables in Part 4 is significantly tied to the passing rate? Justify your answer using significance.

➢ Which of the three possible explanatory variables in Part 4 is the best predictor of the passing rate? Justify your answer using correlation.

➢ Do any of the relationships look nonlinear? Which one or ones?

➢ Are any of the regression equations surprising? Which one or ones?

Print your paper as pages 1 and 2.

Procesamiento de datos

Nº del proyecto: #8879214

Sobre el proyecto