In a one-way ANOVA, if the computed F statistic is greater than the critical F value you may Question 1 options: reject H0 since there is evidence that not all the means are different. not reject H0 since there is no evidence of a difference in the means. not reject H0 because a mistake has been made. reject H0 since there is evidence all the means differ.

And the F statistic calculated from the mean squares if . And for this case we know that . So then we can reject the null hypothesis that all the means are equal at a significance level given . And the best conclusion would be:

reject H0 since there is evidence all the means differ.

Step-by-step explanation:

Previous concepts

Analysis of variance (ANOVA) "is used to analyze the differences among group means in a sample".  

The sum of squares "is the sum of the square of variation, where variation is defined as the spread between each individual value and the grand mean"  

Solution to the problem

The hypothesis for this case are:

Null hypothesis:

Alternative hypothesis: Not all the means are equal

If we assume that we have groups and on each group from we have individuals on each group we can define the following formulas of variation:  

And we have this property  

And the F statistic calculated from the mean squares if . And for this case we know that . So then we can reject the null hypothesis that all the means are equal at a significance level given . And the best conclusion would be:

reject H0 since there is evidence all the means differ.

y=mx+b

step-by-step explanation:

m is slope, b is y-intercept