Wk 4 dsc 2 (1)

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National University *

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BST 322

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Statistics

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Apr 3, 2024

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docx

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1. Plot the data with a regression line and perform a regression with the appropriate statistical test in StatCrunch. Copy and paste your graph and regression output into your Word for posting. 2. What is the correlation coefficient r and what is the coefficient of determination here? R (correlation coefficient) = -0.157605 R-sq = 0.024839337 What does the coefficient of determination mean in this case? 2% of the optimism score variance can be explained by age. 3. Is there a statistically significant correlation between age and optimism in this sample? P-value is less than 0.05, so it is statistically significant. 4. What hypotheses did you test?
H 0 There is no relationship between age and optimism. H a There is a relationship between age and optimism. 5. Using StatCrunch (be sure to copy and paste your predicted Y output from StatCrunch into your submission), what is the predicted optimism score for someone aged 45? Predicted optimism score for one aged 45 is 42.3165 Simple linear regression results: Dependent Variable: Optimism Score Independent Variable: Age Optimism Score = 54.264144 - 0.26550274 Age Sample size: 1000 R (correlation coefficient) = -0.157605 R-sq = 0.024839337 Estimate of error standard deviation: 10.33807 Parameter estimates: Parameter Estimate Std. Err. Alternative DF T-Stat P-value Intercept 54.264144 1.9573379 ≠ 0 998 27.723442 <0.0001 Slope -0.26550274 0.052658904 ≠ 0 998 -5.0419344 <0.0001 Analysis of variance table for regression model: Source DF SS MS F-stat P-value Model 1 2716.898 2716.898 25.421102 <0.0001 Error 998 106661.95 106.8757 Total 999 109378.84 Predicted values: X value Pred. Y s.e.(Pred. y) 95% C.I. for mean 95% P.I. for new 45 42.316521 0.54800186 (41.241153, 43.391889) (22.001191, 62.631851)
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