PSYC 301 Lecture Notes - Lecture 9: Regression Analysis, Heteroscedasticity, Multicollinearity
7 Sep 2020
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#using parenthood dataset, run regression predicting dan from baby. View (parenthood) reg. 1 baby"s sleep accounts for 39. 43% of the variance in dan"s sleep. #f-statistic 63. 8 on 1 and 98 df, p-value . 2696e-12. #baby"s sleep accounts for a signifciant proportion of the variance in dan"s sleep, f(1,98) = #or r-squared = . 394 is signifciantly different from 0. #the amount of sleep dan gets increases significantly as the baby gets more sleep, b = . 308, t(98)=7. 988, p < . 001. #compare to result for correlation: dan"s sleep and his baby"s sleep are significantly related, r = #run regression analysis now predicting dan from both baby and dan. grump reg. 2
