Question
R’s “lm” function is used to perform this task via the ordinary least squares method. For 10 points each:
[10e] Name this task of fitting a statistical model that describes a response variable as a linear combination of explanatory variables and an intercept.
ANSWER: linear regression [or ordinary least squares regression or OLS regression; accept regression analysis]
[10m] Checking the fit of a regression model involves examining these values for Wald tests. To reject a null hypothesis, this quantity must be below the significance level, denoted alpha.
ANSWER: p-values [or p-vals; prompt on p]
[10h] This phenomenon can be checked for by plotting a scatterplot matrix of the explanatory variables and calculating variance inflation factors. This violation of the assumptions of linear regression arises when explanatory variables are correlated.
ANSWER: multicollinearity
<David Bass, Science - Math> ~21122~ <Editor: David Bass>
Summary
| 2023 PACE NSC | 06/10/2023 | Y | 1 | 20.00 | 100% | 100% | 0% |
Data
| Barrington A | Thomas Jefferson A | 10 | 10 | 0 | 20 |