Decision-Based Learning - Null hypothesis for Friedman Test

1. Null-hypothesis for a
Friedman Test
Conceptual Explanation

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.
As you may recall, the Friedman Test attempts to
compare a dependent variable (e.g., test scores)
between the same sample on a number of occasions.

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.
As you may recall, the Friedman Test attempts to
compare a dependent variable (e.g., test scores)
between the same sample on a number of occasions.
Number of Pizza slices eaten by a Group of Football Players
BEFORE THE SEASON DURING THE SEASON AFTER THE SEASON
Player 1 1 14 2
Player 2 4 2 8
Player 3 3 3 9
Player 4 5 2 8
Player 5 4 1 7
Player 6 3 2 1
Player 7 4 3 8
Mean 3.9 3.4 6.9

5. 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.
As you may recall, the Friedman Test attempts to
compare a dependent variable (e.g., test scores)
between the same sample on a number of occasions. It
is favored over the Repeated-Measures ANOVA when the
distributions are skewed and/or the data is rank ordered
or ordinal.

6. 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.
As you may recall, the Friedman Test attempts to
compare a dependent variable (e.g., test scores)
between the same sample on a number of occasions. It
is favored over the Repeated-Measures ANOVA when the
distributions are skewed and/or the data is rank ordered
or ordinal.

7. Here is a template for writing a Friedman Test null
hypothesis.

8. Here is a template for writing a Friedman Test null
hypothesis.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].

9. Here’s an example:

10. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals
who move from the city to rural areas. Red-cell counts
are collected prior to leaving the city, three months, and
then six months after arriving in the rural location.

11. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:

12. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].

13. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:

14. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

15. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

16. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

17. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

18. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

19. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

20. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

21. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

22. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

23. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

24. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

25. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

26. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

27. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

28. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

29. Health researchers want to know if there is a statistically
significant difference in red cell counts in individuals who
move from the city to rural areas. Red-cell counts are
collected prior to leaving the city, three months, and then
six months after arriving in the rural location.
Template:
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null-hypothesis:
There is no significant difference in red cell counts before, three
months, and then six months after individuals moved from the
city to a rural location.

30. Here is a second example

31. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
Template:

32. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
Template:

33. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].

34. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Null Hypothesis:

35. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

36. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

37. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

38. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

39. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

40. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

41. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

42. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

43. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

44. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

45. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

46. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

47. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

48. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

49. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.

50. Let’s say we want to know if “A Sense of Wellbeing”
survey scores for teenagers listening to elevator music
increases over time. So, we select a group of teenagers
and subject them to daily doses of elevator music for two
months. We test their sense of wellbeing before, during
and after the experiment.
There is no significant difference in [insert the Dependent
Variable] [insert the time of the first data collection], [insert the
time of the second data collection], and [insert the time of the
third data collection] [insert the independent variable].
Template:
There is no significant difference in “A Sense of Wellbeing”
scores before, during, and after listening to elevator music.