Null hypothesis for One way RM ANOVA

1. Null-hypothesis for One-Way
Repeated Measures Analysis of
Variance (ANOVA)

2. With hypothesis testing we are setting up a null-hypothesis
– the probability that there is no effect or
relationship – and then we collect evidence that leads
us to either accept or reject that null hypothesis.

3. With hypothesis testing we are setting up a null-hypothesis
– the probability that there is no effect or
relationship – and then we collect evidence that leads
us to either accept or reject that null hypothesis.

4. With hypothesis testing we are setting up a null-hypothesis
– the probability that there is no effect or
relationship – and then we collect evidence that leads
us to either accept or reject that null hypothesis.

5. As you may recall, a One-Way Repeated Measures
ANOVA attempts to compare a dependent variable
(e.g., test scores) between usually at least three
repeated levels (e.g., before, during and after)
associated with an independent variable (e.g., type of
instruction).

6. Here is a template for writing a One-Way
Repeated Measures ANOVA

7. Here is a template for writing a One-Way
Repeated Measures ANOVA
There is no significant difference [insert the Dependent
Variable] [insert level or time 1 of the IV], [insert level or
time 2 of the IV], and [insert level or time 3 of the IV].

8. Example #1

9. Example #1
Researchers conduct an experiment to determine which
TV network make people laugh more on Thursday
nights. Three randomly sampled groups are assembled:
One group watches NBC, the second group watches ABC,
and the third group watches CBS. All participants watch
TV from 8pm-10pm with an audio recorder. The
experimenter listens to the recording and counts the
number of times the participants laugh.
which TV network make people laugh more on Thursday
nights. Three randomly sampled groups are assembled: One
group watches NBC, the second group watches ABC, and the
third group watches CBS. All participants watch TV from
8pm-10pm with an audio recorder. The experimenter listens
to the recording and counts the number of times the
participants laugh.

10. Template

11. Template
There is no significant difference in [insert the
Dependent Variable] between [insert description of the
sample and the time information on the dependent
variable was collected] and [insert information about
subsequent data collections].

12. Researchers conduct an experiment to determine
which TV network make people laugh more on a
particular week night. Three randomly sampled groups
are assembled: One group watches Network A, the
second group watches Network B, and the third group
watches Network C. All participants view the
programming on these networks from 8-10pm with an
audio recorder. The experimenter listens to the
recording and counts the number of times the
participants laugh.

13. Researchers conduct an experiment to determine
which TV network make people laugh more on a
particular week night. Three randomly sampled groups
are assembled: One group watches Network A, the
second group watches Network B, and the third group
watches Network C. All participants view the
programming on these networks from 8-10pm with an
audio recorder. The experimenter listens to the
recording and counts the number of times the
participants laugh.
There is no significant difference in [insert the Dependent
Variable] between [insert description of the sample and the
time information on the dependent variable was collected]
and [insert information about subsequent data collections].

14. Null Hypothesis
There is no significant difference in the number of times
participants laughed from 8-10pm on specific
weeknight between Networks A, B, and C.

15. Null Hypothesis
There is no significant difference in the number of times
participants laughed from 8-10pm on specific
weeknight between Networks A, B, and C.

16. Example #2

17. Farmers wish to compare the number of apples
produced by an apple orchard at years one, two, and
three.
There is no significant difference [insert the Dependent Variable] between
[insert description of the sample and the time information on the dependent
variable was collected] and [insert information about subsequent data
collections]
Null Hypothesis
There is no significant difference in the number of oranges produced from
between year 1, 2, and 3.

18. Farmers wish to compare the number of apples
produced by an apple orchard at years one, two, and
three.
There is no significant difference in [insert the
Dependent Variable] between [insert description of the
sample and the time information on the dependent
variable was collected] and [insert information about
subsequent data collections].

19. Farmers wish to compare the number of apples
produced by an apple orchard at years one, two, and
three.
There is no significant difference [insert the Dependent
Variable] between [insert description of the sample and
the time information on the dependent variable was
collected] and [insert information about subsequent
data collections].
Null Hypothesis
There is no significant difference in the number of
oranges produced from between year 1, 2, and 3.

20. Farmers wish to compare the number of apples
produced by an apple orchard at years one, two, and
three.
There is no significant difference [insert the Dependent
Variable] between [insert description of the sample and
the time information on the dependent variable was
collected] and [insert information about subsequent
data collections].
Null Hypothesis
There is no significant difference in the number of
oranges produced from between year 1, 2, and 3.