Take Home Exam

ED REM 7771 Take Home Exam Project

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Instruction:

This is an individually oriented work. No collaboration with others. You can, however, use any textbooks or library resources. Please note that the due date is on the last day of class.

The project is due on the last day of class.

Please remember, email the project in one file as an attachment. You should use this as the template and insert your answers as indicated. However, if you need your copy back, submit the project in hard copy. Also note that I only keep your copy for maximum ONE months, please pick it up within this time frame.

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[Insert Your Name Here]

Part I

Question 1 (15 points):

Think of this as a “virtual” study. Based on the data, specify your imaginary research questions (i.e., what questions are you trying to address?) that will be examined via in multiple regression analysis. As an requirement for the class, you should include at least one independent categorical variable (e.g., gender), two continuous independent variables, and the interaction between the categorical variable and each of the continuous independent variables. Of course, you can include more than one categorical independent variable in the model. Write your research question(s) and hypotheses.

[Please insert your writing here]

Question 2 (20 points):

Before you do regression analysis on your research questions, perform a preliminary analysis on the data to study and describe what data tells you based on the findings from distribution of variables, their means, and standard deviations.

[Please insert your analysis results and interpretations here]

Question 3:

Based on your research question(s), fit a multiple regression model to your data and write the model from the analysis (5 points).

[Please insert your model here]

Question 4:

Before you starting interpreting the results, please run residual analyses to:

(a) examine assumptions about linearity, normality, and homogeneity of variance (10 points):

[Please insert your analysis here]

(b) check whether there are any outliers that may influence your results (10 points):

[Please insert your analysis here]

Question 5:

(a) for the fitted model, to what degree the model fit the data? (5 points)

[Please insert your analysis here]

(b) interpret the regression coefficients from the analyses you performed, pay attention to the following (10 points):

--- What are the differences between a standardized and an unstandardized regression solution? Which one you used in your interpretation, and please justify?

[Please insert your interpretation of the results here]

Question 6:

Do results support your hypotheses of the study? (10 points)

[Please insert your statement of the results here]

Part II

Question 1:

It has been argued that how much students learn depend on the length of time the students spend on doing schoolwork per week. In the initial experiment, four groups of 10 students each were asked for four different lengths of study time---12, 18, 24, and 36 hours---at the standard school setting. Then, the test score of each of the 30 students was analyzed to determine the effect of study time on the test score, y.

1. Write a quadratic model relating the mean test score, E(y), to the length of study (10 points).

2. Suppose the research and development department is interested in knowing whether different study times will yield different learning outcome (y) Please develop a dummy coding scheme that should be used in the regression model. (10 points)

Question 2:

The principal of a school that has been in the office five years is scheduling his work load for next year, and he must estimate the number of staff available for work. He asks the school statistician to perform the following analyses based on the data in the table.

a. Fit the model to the data given in the table below (5 points).

[Please insert your model here]

b. Interpret the regression coefficients (6 points).

[Please insert your answer here]

c. Is there sufficient evidence to conclude that this model is useful in the prediction of attendance? (5 points)

[Please insert your answer here]

d. Is there sufficient evidence to conclude that mean absence rate increases? (5 points)

[Please insert your answer here]

e. Suppose the 90% prediction interval is (.35, .67). Interpret this interval. (5 points)

[Please insert your answer here]

Data:

where