Microsoft Office Tutorials and References

In Depth Information

In our example, the total sample size of the three groups is 33 since there are 11

bees in Group1, 10 bees in Group 2, and 12 bees in Group 3, and since there are

three groups, 33–3 gives a degrees of freedom for the ANOVA t-test of 30.

If you look up df = 30 in the t-table in Appendix E in the degrees of freedom

column (df), which is the second column on the left of this table, you will ﬁnd that

the critical t-value is 2.042.

Important note:

Be sure to use the degrees of freedom column (df) in Appendix E

for the ANOVA t-test critical t value

8.4.1.2 Stating the Decision Rule for the ANOVA t-Test

Objective: To learn the decision rule for the ANOVA t-test

Interpreting the result of the ANOVA t-test follows the same decision rule that

we used for both the one-group t-test (see
Sect. 4.1.6
) and the two-group t-test (see

Sect. 5.1.8
)
:

If the absolute value of t is less than the critical value of t, we accept

the null hypothesis.

or

If the absolute value of t is greater than the critical value of t, we

reject the null hypothesis and accept the research hypothesis.

Since we are using a type of t-test, we need to take the absolute value of t. Since

the absolute value of -3.80 is greater than the critical t-value of 2.042, we reject

the null hypothesis (that the population means of the two groups are equal) and

accept the research hypothesis (that the population means of the two groups are

signiﬁcantly different from one another).

This means that our conclusion, in plain English, is as follows:

The average number of sound bursts per cycle for SUBSPECIES C was

signiﬁcantly greater than the average number of sound bursts per cycle for

SUBSPECIES B (16.75 vs. 14.66).

8.4.1.3 Performing an ANOVA t-Test Using Excel Commands

Now, let’s do these calculations for the ANOVA t-test using Excel with the ﬁle

you created earlier in this chapter: BEE12

A36: SUBSPECIES B vs. SUBSPECIES C

A38: 1/n B + 1/n C

A40: s.e. B vs. C

A42: ANOVA t-test

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