In regression analysis, the F test will provide the same conclusion as the t test if
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there is only one dependent variable |
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there is only one independent variable |
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there is a positive correlation between x and y |
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the y-intercept is positive |
In case of simple linear regression t-test and F-test both provide the same results.
To understand this , let us consider a simple linear regression model
The tests are used to conduct hypothesis tests on the regression coefficients obtained in simple linear regression.
The test statistic used for this test is:
The F ratio that underlies the analysis of variance test is the square of this,
The p-value for the t-test is the probability of recording a t-value as far from zero, and this equals the probability of getting as large an F-ratio as the one evaluated from the data.
Answer : there is only one independent variable (i.e. simple linear regression)
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