act14_regression_only_assignment_sheet KEY

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California State University, San Marcos *

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215

Subject

Biology

Date

Dec 6, 2023

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pdf

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2

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Biol 215 – Activity 14: Regression Name Due: EYE TESTS – use the class data to answer the following questions. 1. Run the regression, and look at the residual plots. Do we meet the normality and HOV of residuals assumptions? Yes 2. Based on the fitted line plot, is there any reason to think that a straight line is a poor model for the relationship between number of correct characters and distance from the screen? Are there any influential data points? It’s a good fit, no influential points. 4. Conduct a regression analysis of correct characters (response) as a function of distance from the screen (predictor). Fill in the ANOVA table to the right. Highlight the term that gives the variation explained by the line and highlight the unexplained variation. 5. Divide the SS regression by the SS total, report it here. 3623/3874 = 0.935 6. Report the coefficient of determination (r 2 ) from your JAMOVI output. Does it equal your calculation in 5? r 2 = 0.935, it equals the calculation 7. What would the coefficient of determination be if everyone at a particular distance from the screen had identical scores, and the change in correct characters was the same for every meter of increased distance from the screen? Source df SS MS F p Regression 1 3623 3622.50 404 <0.001 Residual 28 251 8.96 Total 29 3874
It would be equal to 1 or 100%. 8. Report the regression equation below. Number correct characters = 172.05 – 6.43 Distance 9. Circle the coefficient in the regression equation that tells you how many additional characters we can expect to get wrong when we move 1 m from the screen. What is the name of this coefficient? Slope 10. Underline the coefficient in the regression equation that tells you how many characters you would expect to get right if you were standing with your nose touching the screen? What is the name of this coefficient? Intercept 11. Why might you be less willing to interpret the intercept than the slope? Which one is an extrapolation beyond the range of observed data? We did not have anyone standing at the screen, so the intercept is a predicted value that's outside of the range of observed data. Given that it's telling us that 172.05 characters would be correct at a distance of 0, and there are only 165 characters, it can't be correct. 12. Predict the number of characters correct at 3 m from the screen using the regression equation. 153
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