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Using Statistical Regression Methods in Education Research


Simple Linear Regression Module Quiz

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There are 15 questions here. Click the relevant box or drag and drop the answers as appropriate! Click VIEW FEEDBACK when you’re ready to see the answers. When you want to move on just click EXIT QUIZ. Enjoy!
1. A researcher wants to perform a simple linear regression to find out if the socio-economic status of a teacher can predict whether they work at a primary or a secondary school. Why can’t this be done?

2. Please use the table to decide which of the following statements are true about truancy rates and gender.

3. The SPSS/PASW output below displays the chi-square test based on the table in the previous question. Can we conclude that males are more likely to have been truant in the last 12 months than females?

4. Please indicate which of the statements about the following graph is true.

5. Please indicate the strength and direction of the relationships described by each of the following values of Pearson’s r by dragging them into the relevant box
Pearson's rStrong negativeWeak negativeNone Weak positiveStrong positive

6. A researcher collects data about students’ anxiety ahead of a spelling test and finds a correlation with test performance, r = .17, p = .12. Can the researcher conclude that test anxiety is significantly associated with test performance?

7. If a study found that there was a statistically significant strong positive correlatation between attitude to Maths and exam scores it could be concluded that a positive attitude causes better performance.

8. Under what circumstances is it better to use Spearman’s rho rather than Pearson’s r?

9. Please match each of the terms below with their definition.
Definition Regression lineResidualCoefficient of determinationOutcome variable
The variable the regression model predicts
A representation of the regression model
The difference between an actual outcome value and the value predicted by the model
Represents how much of the outcome the regression model explains

10. The following formula represents a regression model which uses the number of days a student spent revising to predict their score on a Spanish test (%). y = 5x + 15. Please match the explanations with the figures in the boxes by dragging and dropping each one – note each figure may have more than one matching explanation.
Explanation5 1517
The value of Y when X is 0 (intercept)
Extra % scored on test with each day spent revising
The number of days revision which the model predicts are necessary to score 100%
The expected exam score if the student did not spend any days revising
The gradient of the regression line

11. Please check next to the statements which are true of regression lines. Note there may be more than one!

13. The ANOVA table from the Simple Linear Regression in the previous question tells us that F = 368.1, df = 1, p < .05. What does this mean?

14. Below is the SPSS output about coeffiecients for the ‘attitude to school’ and KS3 results regression.

What does the model predict happens to KS3 score for each one point that the ‘attitide to school’ rating increases?

15. It is important that the residuals are normally distributed when preforming a regression analysis.

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