Post on 20-Jun-2015
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Null-hypothesis for a Friedman Test
Conceptual Explanation
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.
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.
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 SEASONPlayer 1 1 14 2Player 2 4 2 8Player 3 3 3 9Player 4 5 2 8Player 5 4 1 7Player 6 3 2 1Player 7 4 3 8Mean 3.9 3.4 6.9
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.
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.
Here is a template for writing a Friedman Test null hypothesis.
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].
Here’s an example:
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.
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:
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].
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:
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].
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
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:
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].
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.
Here is a second example
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:
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:
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].
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.
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].
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.
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:
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].
There is no significant difference in “A Sense of Wellbeing” scores before, during, and after listening to elevator music.