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Chi-Square Distribution
COMPUTE CHI-SQUARE DISTRIBUTION
SCENARIO:
A phenomenon you are studying has been sub-divided into several categories, with its chi-square value derived from the observed and the expected values in each category.
The chi-square distribution is a goodness-of-fit test that will tell you if your observations are consistent with your expected model of a phenomenon.
From the given chi-square value, does your observation fit well with your expected model?
Chi-square value:
*
The unified value derived from the observed and the expected values
Number of categories:
*
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
The characteristics by which the data has been classified
Level of significance:
*
0.1%
0.5%
1%
5%
10%
Area covered by the critical region.
This is the opposite of confidence level.
(i.e. If level of significance = 0.1%, then confidence level = 99.9%)
Statistics
Chi-Square Distribution
Chi-Square Value
Difference between Two Proportions
Mean and Standard Deviation
Normal Distribution
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