UNIT (4)
HERE IS THE LINK TO THE DATASET
Research Project Instructions: Using the Statistics Class dataset called “Stat_Grades.sav,” answer the following. ( LINK ABOVE)
1. Which of the five Quizzes has the strongest relationship with overall student performance on the Final Exam? Include all SPSS outputs that you will use to answer this question. Explain your choice. Is this relationship strong enough to use these variables in a prediction equation? Why or why not? Which is the best Quiz to use to predict the Final Exam?
2. Create a scatterplot to show the relationship between your chosen highest correlation quiz from problem 1 above, and the final exam points. Use your quiz as the independent variable and the final exam points as the dependent variable. Fully label your scatter plot graph. Assess this scatter plot and determine if it shows a strong correlation between the quiz and the final exam? Why or why not? Explain and discuss.
3. Using the most appropriate quiz, create a regression prediction equation that can be used to predict a final exam score given a quiz score. Show all work and SPSS results that you used to create the prediction equation. Be sure to specify which quiz you chose and why. Explicitly note the dependent or criterion variable and the independent or prediction variable. Show the entire prediction equation.
4. Using your prediction equation, evaluate and predict what the final exam score would be for a student who has a quiz score of 6. Show all work and how you calculated your prediction. Do you agree with this prediction? Why or why not? Are predictions such as this one 100% accurate? Are these types of predictions good estimates?
5. Suppose you would like to predict a student’s final exam points using their short-form IQ score and their Previous GPA. Calculate the appropriate correlations (include SPSS correlation results here) and discuss whether you expect your independent variables of short-form IQ score and Previous GPA to offer a good prediction for final exam points. Include both appropriate scatterplots in your discussion as well.
6. Create a prediction equation to predict a student’s final exam points using their short-form IQ score and their Previous GPA. Show all work and steps, including any SPSS results that you use. Using your prediction equation, predict the final exam score for a student with an IQ of 120 and a GPA of 3.5. Show all work. Assess your results and discuss whether you agree with this prediction?
For this Project, you will use the “Statistics Class” dataset called Stat_Grades.sav, which can be found in the Doc Sharing area under the Graded Projects category. This same “Statistics Class” dataset is used for the Projects in Units 2, 7, and 9. There is a full description of this dataset in the Graded Projects category of the Doc Sharing area. The Stat_Grades.sav dataset contains data collected about students in three sections of a statistics class taught by an instructor. You will also use SPSS for this Project.
HINTS AND HELP
Note: When asked to explain or discuss, make sure you use complete sentences, paragraph form (single spacing), proper grammar, and correct spelling. Minimal or incomplete responses can lose points. Include any SPSS results that you use, but do not include SPSS results that are not part of your solution.
Hint: In some cases, you are asked to determine “appropriate” variables and to make calculations. This means that you will have to determine which variable(s) you feel are best and why.
Remember to always show all of your work and each of your steps.
You may type and place your answers and SPSS results directly into this document.
Assignment Rubric Reminder for Unit 4 at the “A” range. Please check the class syllabus for a full rubric.
Unit 4 Project Grading Rubric
Point Possible
Grading Criteria
135 – 150 points
“A” range
Student work demonstrates mastery of the objectives assessed by the Project. This is evidenced by at least the following:
· The selection of the statistical procedure(s) is/are the most appropriate ones for answering the question.
· The statistical procedure was calculated correctly using SPSS.
· The interpretation of the SPSS output is correct and complete, including applying the regression equation to make a prediction.
· The results of the statistical analyses are presented in easy to understand, non-statistical language that addresses the research question.
· SPSS output that is not needed in the solution is not included. Only appropriate SPSS output are include.
· Appropriate Scatterplot Graphs are included and properly labeled.
· Appropriate regression prediction equations are created and evaluated.
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