H o Β 1 0 H a Β 1 0 The null hypothesis states that the slope is equal to zero

H o β 1 0 h a β 1 0 the null hypothesis states that

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H o : Β 1 = 0 H a : Β 1 ≠ 0 The null hypothesis states that the slope is equal to zero, and the alternative hypothesis states that the slope is not equal to zero.
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In general, an F-test in regression compares the fits of different linear models. Unlike t-tests that can assess only one regression coefficient at a time, the F-test can assess multiple coefficients simultaneously. The hypotheses for the F-test of the overall significance are as follows: Null hypothesis : The fit of the intercept-only model and your model are equal. Alternative hypothesis : The fit of the intercept-only model is significantly reduced compared to your model.
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“Multicollinearity " refers to predictors that are correlated with other predictors. Multicollinearity occurs when your model includes multiple factors that are correlated not just to your response variable, but also to each other. In other words, it results when you have factors that are a bit redundant.
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where R2k is the R 2 -value obtained by regressing the k th predictor on the remaining predictors. Note that a variance inflation factor exists for each of the k predictors in a multiple regression model .
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