The t test for the difference between the means of two independent samples assumes that the respective:
Sample sizes are equal
Sample variances are equal
Populations are approximately normal
All of the above
If we are testing for the difference between the means of two independent samples with samples of n1=n20 and n2=20, the number of degrees of freedom is equal to :
38
40
10
39
In testing for the differences between the means of two independent population where the variances in each population are unknown but assumed equal, the degrees of freedom are:
n-1
N1+n2-1
N1+n2-2
n-2
In testing for differences between the means of two independent populations the null hypothesis states that:
The difference between the two population means is equal to 2
The difference between the two population means is equal to 0
The difference between the two population means is greater than 0
The difference between the two population means is less than 2
In testing for differences between the means of two related population where the variance of the difference is unknown, the degrees of freedom are:
n-1
N1+n2-1
N1+n2-2
n-2
If we are testing for the difference between the means of two related samples with samples of n1=20 and n2=20, the number of degrees of freedom is equal to :
39
40
10
19
In testing for differences between the means of two related populations the null hypothesis states that:
The population mean difference is equal to 2
The population mean difference is equal to 0
The population mean difference is greater than 0
The population mean difference is less than 2
The statistical distribution used for testing the difference between two population variances is the _________ distribution.
t
Normal
Binomial
F
When testing for the difference between two population variances with sample sizes of n1=8 and n2=10, the number of degrees of freedom are:
8,10
7,9
18
16
The test for the equality of two population variances is based on :
The difference between the two sample variances
The ratio of the two sample variances
The differences between the two population variances
The difference between the sample variances divided by the difference between the sample means
The one way ANOVA is used to test statistical hypothesis concerning:
Variances
Standard deviations
Mean squares
means
In a one-way ANOVA F test, the “among group” variation is attributable to:
Experimental error
Unexplained variation
Treatment effects
Residual variation
In a one-way ANOVA, if the computed F statistic exceeds the critical F value we may:
Reject Ho since there is evidence all the means differ
Reject Ho since there is evidence of a treatment effect
Not reject Ho since there is no evidence of a difference
Not reject Ho because a mistake has been made
Which of the following components in an ANOVA table are not additive?
Sum of squares
Degrees of freedom
Mean squares
It is not possible to tell
The Tukey-Kramer procedure would be used:
To test for normally
To test for homogeneity of variance
To test independence of errors
To test for differences in pair wise means
In order to calculate the F test statistic for a one-way ANOVA experiment you would use which of the following?
MSW/MS(A)
SSW/SS(A)
MSA/MSW
SSA/SSW
The degrees of freedom for the F test in a one-way ANOVA are:
(n-c) and (c-1)
(c-1) and (n-c)
(c-n) and (n-1)
(n-1)and (c-n)