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Summary pdf,pdf of chi square distribution,derivation of pdf of chi square distribution,observed frequency,expected frequency,genetic map distance,chi square test,geology (field of study),geophysics (field of study),statistics,data analysis,statistical hypothesis
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Course
7795
Institution
Belagavi University
The Chi-Square Test is a statistical method used to determine whether there is a significant association between categorical variables. It is widely employed in various fields such as social sciences, biology, business, and others where categorical data analysis is crucial.
Key Aspects of the Ch...
Cathy Poliak, Ph.D. cathy@math.uh.edu Office Fleming 11c (Department
Chapter 12 of Mathematics University of Houston
Lecture) 14 - 3339
, Outline
1 Goodness of Fit Tests
2 Chi-Square
3 Examples
4 χ2 Test of Independence
5 Final Exam Review
6 Examples
Cathy Poliak, Ph.D. cathy@math.uh.edu Office Fleming 11c (Department
Chapter 12 of Mathematics University of Houston
Lecture) 14 - 3339
, Candy
Mars Inc. claims that they produce M&Ms with the following
distributions:
Brown 30% Red 20% Yellow 20%
Orange 10% Green 10% Blue 10%
A bag of M&Ms was randomly selected from the grocery store shelf,
and the color counts were:
Brown 14 Red 14 Yellow 5
Orange 7 Green 6 Blue 10
We want to know if the distribution of color the same as the
manufacturer’s claim.
Cathy Poliak, Ph.D. cathy@math.uh.edu Office Fleming 11c (Department
Chapter 12 of Mathematics University of Houston
Lecture) 14 - 3339
, Goodness-of-fit Test
This is a test to see how well on sample proportions of categories
"match-up" with the known population proportions.
The Chi-square goodness-of-fit test extends inference on
proportions to more than two proportions by enabling us to
determine if a particular population distribution has changed from
a specified form.
Hypotheses:
I H0 : The proportions are the same as what is claimed.
I Ha : At least one proportion is different as what is claimed.
This would be better in context of the problem. For example in our
M&Ms test;
I H0 : The distribution of candy colors is as the manufacturer claims.
I Ha : The distribution of candy colors is not what the manufacturer
claims.
Cathy Poliak, Ph.D. cathy@math.uh.edu Office Fleming 11c (Department
Chapter 12 of Mathematics University of Houston
Lecture) 14 - 3339
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