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Chapter 11 Chi Square Distribution and Its applications

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Title: Chapter 11 Chi Square Distribution and Its applications


1
Chapter 11Chi Square Distributionand Its
applications
2
What is a Chi Square?
  • Chi Square is another probability distribution
    (like Normal and Student t)
  • Symbol ?2
  • Picture

0
3
What is a Chi Square? (cont)
  • Features Mode (i.e. Peak) at n 2.
  • Degrees of Freedom n 2.

0
4
Why ?2?
  • The ?2 distribution allows you to test the
    independence of two factors.
  • For instance, what about getting a tattoo and the
    frequency of Hepatitis C? What if you got the
    tattoo in a tattoo parlor? What if your cousin
    Dwayne gave you that great tattoo of Count
    Chocula?
  • The Chi Squared test for independence allows you
    to decide whether the chance of having hepatitis
    is independent of the tattoo status.

5
Requirements
  • 1. Counted Data Condition
  • Data must be in counts
  • 2. Randomization Condition
  • Individuals who have been counted should
  • be a random sample from some
  • population.
  • 3. Expected Cell Frequency Condition
  • The expected values (which you will
  • calculate) should all be at least 5.

6
What to do?
  • Use a contingency table to find the differences
    between observed and expected values.

7
What to do?
  • Use a contingency table to find the differences
    between observed and expected values.

d.f. (R-1)(C-1) where R and C are the number of
rows/columns
8
Lets Try one
  • We have counts of 626 individuals categorized
    according to their tattoo status and their
    hepatitis status.

Hep C No Hep C Total
Tattoo, Parlor 17 35 52
Tattoo, Elsewhere 8 53 61
No Tattoo 22 491 513
Total 47 579 626
9
  • We want to test whether tattoo status and
    hepatitis status are independent.
  • HO Tattoo status and hepatitis status are
    independent
  • HA Tattoo status and hepatitis status are not
    independent
  • Check the conditions
  • 1. Counts of data categorized
  • 2. While you dont have the information, you can
    assume that they were selected to avoid biases.
  • 3. Well find out when we determine E for each
    cell

10
Compute E
Hep C No Hep C Total
Tattoo, Parlor 17 35 52
Tattoo, Elsewhere 8 53 61
No Tattoo 22 491 513
Total 47 579 626
48.096
3.904
56.420
4.580
38.516
474.484
11
Notice
  • There are some values below 5 well continue
    from here for the sake of the data.
  • What are the degrees of freedom?
  • Find the ?2 value.
  • Using a table, the value for P(?2 gt57.91)

2
57.91
Less than .0001
12
Conclusion
  • The P-value is very small, so I reject the null
    hypothesis and conclude that hepatitis status is
    not independent of tattoo status.

13
Resources
  • www.microbiologybytes.com/maths/graphics/chi.gif
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