questions of goodness of fit
DESCRIPTION
Decision-Based Learning - Questions of goodness of fitTRANSCRIPT
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Questions of Goodness of Fit
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Is the problem you are working on a question of Goodness of Fit?
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Is the problem you are working on a question of Goodness of Fit?
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Questions of Goodness of Fit have become increasingly important in modern statistics.
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Goodness of fit is a method used to determine how close a hypothesized pattern fits an observed pattern.
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Goodness of fit is a method used to determine how close a hypothesized pattern fits an observed pattern.
Hypothesized Pattern- the way you think
things are.
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Goodness of fit is a method used to determine how close a hypothesized pattern fits an observed pattern.
fits
Hypothesized Pattern- the way you think
things are.
![Page 8: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/8.jpg)
Goodness of fit is a method used to determine how close a hypothesized pattern fits an observed pattern.
Observed Pattern – the way things
actually are.
Hypothesized Pattern- the way you think
things are.
fits
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For example, let’s say we hypothesize that there are an equal number of females as there are males in the town of Solvang, California.
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So, in a sample of 200 Solvangans we would hypothesize that 100 would be female.
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So, in a sample of 200 Solvangans we would hypothesize that 100 would be female.
The hypothesized number
of females in a sample of 200 is
100
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So, in a sample of 200 Solvangans we would hypothesize that 100 would be female.
The hypothesized number
of females in a sample of 200 is
100
That is because we assume that an equal number will be males and an equal number
will be females
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We then take a sample of 200 and find that there are actually 84.
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Once again, our hypothesized number of females from a sample of 200 is 100.
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Once again, our hypothesized number of females from a sample of 200 is 100.
The hypothesized number
of females in a sample of 200 is
100
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But, our actual number of females from a sample of 100 is 84.
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Is the difference between 100 and 84 statistically significant?
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Is the difference between 100 and 84 statistically significant?
Note - Even though we are using the word difference here, in this
case we are referring to how well the data FITS the hypothesis.
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Is the difference between 100 and 84 statistically significant?
The HYPOTHESIZED number
of females in a sample of 200 is
100
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Is the difference between 100 and 84 statistically significant?
The ACTUAL number
of females in a sample of 200 is
84
The HYPOTHESIZED number
of females in a sample of 200 is
100
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Is the difference between 100 and 84 statistically significant?
The ACTUAL number
of females in a sample of 200 is
84 16
The HYPOTHESIZED number
of females in a sample of 200 is
100
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Is the difference between 100 and 84 statistically significant?
The ACTUAL number
of females in a sample of 200 is
84 16
The HYPOTHESIZED number
of females in a sample of 200 is
100
This value can
be tested
statistically to
determine its
Goodness of
Fit
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If it is significantly different, then we may need to collect a new sample that is more representative of the hypothesized population.
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If it is significantly different, then we may need to collect a new sample that is more representative of the hypothesized population.
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Here is an equation that we will use as a guide to identify goodness of fit questions.
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Here is an equation that we will use as a guide to identify goodness of fit questions.
Hypothesized Number
fit theActual
NumberDoes the ?
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Examples of Goodness of Fit Tests
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Example #1
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Consider a standard package of milk chocolate M&Ms.
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Consider a standard package of milk chocolate M&Ms. There are six different colors: red, orange, yellow, green, blue and brown.
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Consider a standard package of milk chocolate M&Ms. There are six different colors: red, orange, yellow, green, blue and brown. Suppose that we are curious about the distribution of these colors and ask, do all six colors occur equally?
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Consider a standard package of milk chocolate M&Ms. There are six different colors: red, orange, yellow, green, blue and brown. Suppose that we are curious about the distribution of these colors and ask, do all six colors occur equally? You collect 24 M&Ms with 4 reds, 4 oranges, 3 yellows, 5 greens, 2 blues, & 6 browns.
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Consider a standard package of milk chocolate M&Ms. There are six different colors: red, orange, yellow, green, blue and brown. Suppose that we are curious about the distribution of these colors and ask, do all six colors occur equally? You collect 24 M&Ms with 4 reds, 4 oranges, 3 yellows, 5 greens, 2 blues, & 6 browns. Are these differences statistically significant?
![Page 34: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/34.jpg)
Consider a standard package of milk chocolate M&Ms. There are six different colors: red, orange, yellow, green, blue and brown. Suppose that we are curious about the distribution of these colors and ask, do all six colors occur equally? You collect 24 M&Ms with 4 reds, 4 oranges, 3 yellows, 5 greens, 2 blues, & 6 browns. Are these differences statistically significant?
Hypothesized Number
fit theActual
NumberDoes the ?
![Page 35: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/35.jpg)
Consider a standard package of milk chocolate M&Ms. There are six different colors: red, orange, yellow, green, blue and brown. Suppose that we are curious about the distribution of these colors and ask, do all six colors occur equally? You collect 24 M&Ms with 4 reds, 4 oranges, 3 yellows, 5 greens, 2 blues, & 6 browns. Are these differences statistically significant?
Hypothesized Number
fit theActual
NumberDoes the ?
![Page 36: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/36.jpg)
Consider a standard package of milk chocolate M&Ms. There are six different colors: red, orange, yellow, green, blue and brown. Suppose that we are curious about the distribution of these colors and ask, do all six colors occur equally? You collect 24 M&Ms with 4 reds, 4 oranges, 3 yellows, 5 greens, 2 blues, & 6 browns. Are these differences statistically significant?
fit theActual
NumberDoes the
Hypothesized Number =
4 red, 4 orange4 yellow, 4 green4 blue, 4 brown
?
![Page 37: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/37.jpg)
Consider a standard package of milk chocolate M&Ms. There are six different colors: red, orange, yellow, green, blue and brown. Suppose that we are curious about the distribution of these colors and ask, do all six colors occur equally? You collect 24 M&Ms with 4 reds, 4 oranges, 3 yellows, 5 greens, 2 blues, & 6 browns. Are these differences statistically significant?
fit theActual
NumberDoes the
Hypothesized Number =
4 red, 4 orange4 yellow, 4 green4 blue, 4 brown
?
![Page 38: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/38.jpg)
Consider a standard package of milk chocolate M&Ms. There are six different colors: red, orange, yellow, green, blue and brown. Suppose that we are curious about the distribution of these colors and ask, do all six colors occur equally? You collect 24 M&Ms with 4 reds, 4 oranges, 3 yellows, 5 greens, 2 blues, & 6 browns. Are these differences statistically significant?
fit theDoes the
Hypothesized Number =
4 red, 4 orange4 yellow, 4 green4 blue, 4 brown
Actual Number =
4 red, 4 orange3 yellow, 5 green2 blue, 6 brown
?
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Example #2
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Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate.
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Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate. Suppose that a study was done to determine if the actual student absenteeism follows faculty perception.
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Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate. Suppose that a study was done to determine if the actual student absenteeism follows faculty perception. The faculty expected that a group of 100 students would miss class according to the following chart.
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Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate. Suppose that a study was done to determine if the actual student absenteeism follows faculty perception. The faculty expected that a group of 100 students would miss class according to the following chart.
# of absences EXPECTED # of Students
0-2 50
3-5 30
6-8 12
9-11 6
12+ 2
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Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate. Suppose that a study was done to determine if the actual student absenteeism follows faculty perception. The faculty expected that a group of 100 students would miss class according to the following chart. Here were actual results of a random sample.
# of absences EXPECTED # of Students
0-2 50
3-5 30
6-8 12
9-11 6
12+ 2
![Page 45: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/45.jpg)
Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate. Suppose that a study was done to determine if the actual student absenteeism follows faculty perception. The faculty expected that a group of 100 students would miss class according to the following chart. Here were actual results of a random sample.
# of absences EXPECTED # of Students
0-2 50
3-5 30
6-8 12
9-11 6
12+ 2
# of absences ACTUAL # of Students
0-2 35
3-5 40
6-8 20
9-11 1
12+ 4
![Page 46: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/46.jpg)
Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate. Suppose that a study was done to determine if the actual student absenteeism follows faculty perception. The faculty expected that a group of 100 students would miss class according to the following chart. Here were actual results of a random sample. Did the faculty perception fit the reality?
Hypothesized Number
fit theActual
NumberDoes the ?
![Page 47: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/47.jpg)
Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate. Suppose that a study was done to determine if the actual student absenteeism follows faculty perception. The faculty expected that a group of 100 students would miss class according to the following chart. Here were actual results of a random sample. Did the faculty perception fit the reality?
Hypothesized Number
fit theActual
NumberDoes the ?
![Page 48: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/48.jpg)
Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate. Suppose that a study was done to determine if the actual student absenteeism follows faculty perception. The faculty expected that a group of 100 students would miss class according to the following chart. Here were actual results of a random sample. Did the faculty perception fit the reality?
Faculty Perceptions of Student
Absenteeism
fit theActual
NumberDoes the ?
![Page 49: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/49.jpg)
Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate. Suppose that a study was done to determine if the actual student absenteeism follows faculty perception. The faculty expected that a group of 100 students would miss class according to the following chart. Here were actual results of a random sample. Did the faculty perception fit the reality?
Faculty Perceptions of Student
Absenteeism
fit theActual
NumberDoes the ?
![Page 50: Questions of goodness of fit](https://reader035.vdocuments.site/reader035/viewer/2022062307/5562ed2bd8b42a38778b5367/html5/thumbnails/50.jpg)
Absenteeism of college students from math classes is a major concern to math instructors because missing class appears to increase the drop rate. Suppose that a study was done to determine if the actual student absenteeism follows faculty perception. The faculty expected that a group of 100 students would miss class according to the following chart. Here were actual results of a random sample. Did the faculty perception fit the reality?
Actual Student
Absenteeism
Faculty Perceptions of Student
Absenteeism
fit theDoes the ?
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An exception to the rule
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An exception to the rule
As was just shown, if you are comparing an observed count with a hypothesized count, then you will use goodness of fit statistical methods.
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An exception to the rule
As was just shown, if you are comparing an observed count with a hypothesized count, then you will use goodness of fit statistical methods.
Hypothesized Count = 100
Actual Count = 84
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An exception to the rule
As was just shown, if you are comparing an observed count with a hypothesized count, then you will use goodness of fit statistical methods.
Hypothesized Count = 100
Actual Count = 84
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An exception to the rule
However,
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An exception to the rule
However, if you are comparing a hypothesized proportion (5 out of 10) or percentage (50%)
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An exception to the rule
However, if you are comparing a hypothesized proportion (5 out of 10) or percentage (50%) with an actual proportion or percentage, then you will use a “Difference” method.
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An exception to the rule
However, if you are comparing a hypothesized proportion (5 out of 10) or percentage (50%) with an actual proportion or percentage, then you will use a “Difference” method.
Hypothesized Percentage =
50%
Actual Percentage =
42%
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An exception to the rule
However, if you are comparing a hypothesized proportion (5 out of 10) or percentage (50%) with an actual proportion or percentage, then you will use a “Difference” method.
Hypothesized Percentage =
50%
Actual Percentage =
42%
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Here are the two classifications with their equations:
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Question of Goodness of Fit:
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Question of Goodness of Fit:
Hypothesized Number
Actual Number
fit theDoes the ?
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Question of Goodness of Fit:
Question of Difference:
Hypothesized Number
Actual Number
fit theDoes the ?
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Question of Goodness of Fit:
Question of Difference:
Hypothesized Number
Actual Number
Hypothesized Percentage or
Proportion
differActual
Percentage or Proportion
Does the
fit theDoes the ?
?
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Let’s see an example:
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You have been asked to determine if a sample is representative of the general population in terms of gender.
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You have been asked to determine if a sample is representative of the general population in terms of gender. Since there are roughly equal numbers of men and women in the population, your sample of 500 should have 250 females.
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You have been asked to determine if a sample is representative of the general population in terms of gender. Since there are roughly equal numbers of men and women in the population, your sample of 500 should have 250 females. However, in your sample there are 325 females.
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You have been asked to determine if a sample is representative of the general population in terms of gender. Since there are roughly equal numbers of men and women in the population, your sample of 500 should have 250 females. However, in your sample there are 325 females. How well does your sample of 325 fit this hypothesized expectation statistically?
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You have been asked to determine if a sample is representative of the general population in terms of gender. Since there are roughly equal numbers of men and women in the population, your sample of 500 should have 250 females. However, in your sample there are 325 females. How well does your sample of 325 fit this hypothesized expectation statistically? Since this question is dealing with number
counts, it will be classified as a Goodness of Fit Question
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Now let’s see the same question but as a “difference” question.
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You have been asked to determine if a sample is representative of the general population in terms of gender.
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You have been asked to determine if a sample is representative of the general population in terms of gender. Since there are roughly equal numbers of men and women in the population, your sample should have 50% females.
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You have been asked to determine if a sample is representative of the general population in terms of gender. Since there are roughly equal numbers of men and women in the population, your sample should have 50% females. However, in your sample there are 65% females.
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You have been asked to determine if a sample is representative of the general population in terms of gender. Since there are roughly equal numbers of men and women in the population, your sample should have 50% females. However, in your sample there are 65% females. How much does your sample of 65% differ from the hypothesized expectation of 50% statistically?
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You have been asked to determine if a sample is representative of the general population in terms of gender. Since there are roughly equal numbers of men and women in the population, your sample should have 50% females. However, in your sample there are 65% females. How much does your sample of 65% differ from the hypothesized expectation of 50% statistically?
Since this question is dealing with percentages or proportions, it will be
classified as a Difference Question
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Examine the question or problem you are working on.
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Is it a question of goodness of fit?
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If so, select GOODNESS OF FIT