# F-ration and regression

• F-ratio = The most important part of the table is the F-ratio, which is calculated using equation, and the associated significance value of that F-ratio. For these data, F is 99.59, which is significant at p < .001 (because the value in the column labelled is less than .001). This result tells us that there is less than a 0.1% chance that an F-ratio this large would happen if the null hypothesis were true. Therefore, we can conclude that our regression model results in significantly better prediction of record sales than if we used the mean value of record sales. In short, the regression model overall predicts record sales significantly well.
• Regression: make a prediction about the future when the outcome is a continuous variable
• Logistic regression: when the outcome is a categorical outcome(fireman, doctor, or pimp)

A small standard error tells us that most pairs of samples from a population will have very similar means (i.e. the difference between sample means should normally be very small). A large standard error tells us that sample means can deviate quite a lot from the population mean and so differences between pairs of samples can be quite large by chance alone.

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