What implications does an insignificant F-test have in the context of multiple linear regression?
- The model does not explain a significant amount of the variance in the response
- The model explains a significant amount of the variance in the response
- The model has a high R-squared value
- The model has violated the assumption of homoscedasticity
The F-test in multiple linear regression tests the null hypothesis that all regression coefficients are equal to zero. An insignificant F-test suggests that the predictors do not explain a significant amount of the variance in the response variable.
Loading...
Related Quiz
- What does the F-statistic signify in an ANOVA test?
- The Breusch-Pagan test and the White test are common methods to detect __________ in the residuals.
- A Type II error occurs when we fail to reject the null hypothesis, even though it is _______.
- In _________ sampling, the population is divided into subgroups, and a simple random sample is drawn from each subgroup.
- What is the role of interaction effects in a two-way ANOVA?