True or false?:
1) If the relationship between 2 variables is perfect the standard error of estimate equals 0.
2) F=-1.0 is never possible in ANOVA.
3) If F<1.0 in an ANOVA we don’t even have to bother to look at F critical values table since the result cannot be significant.
4) In an ANOVA, sample size n1=10, n2=12, n3=30, and n4=100, we can use Tukey’s HSD to conduct multiple comparisons.
Please explain your answers.
1. If the relationship between 2 variables is perfect the standard error of estimate equals 0 - True
since if the relationship between 2 variables is perfect i.e. R-squared = 1 so Standard Error = 0
2. F=-1.0 is never possible in ANOVA. - False
since F-value is always > 1 in ANOVA
3. If F<1.0 in an ANOVA we don’t even have to bother to look at F critical values table since the result cannot be significant. - False
4. In an ANOVA, sample size n1=10, n2=12, n3=30, and n4=100, we can use Tukey’s HSD to conduct multiple comparison - False
since given sample sizes are different so we have to use Tukey's Kramer Mutiple comparison.
True or false?: 1) If the relationship between 2 variables is perfect the standard error of estimate equals 0. 2) F=-1.0 is never possible in ANOVA. 3) If F<1.0 in an ANOVA we don’t even have to bo...
True or false?: 1) If the relationship between 2 variables is perfect the standard error of estimate equals 0. 2) F=-1.0 is never possible in ANOVA. 3) If F<1.0 in an ANOVA we don’t even have to bother to look at F critical values table since the result cannot be significant. 4) In an ANOVA, sample size n1=10, n2=12, n3=30, and n4=100, we can use Tukey’s HSD to conduct multiple comparisons.