chi-square_test
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| Both sides previous revisionPrevious revisionNext revision | Previous revision | ||
| chi-square_test [2016/05/16 08:21] – hkimscil | chi-square_test [2024/12/09 08:20] (current) – hkimscil | ||
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| 5.991 at 0.05 probability | 5.991 at 0.05 probability | ||
| 9.210 at 0.01 probability | 9.210 at 0.01 probability | ||
| + | < | ||
| + | > qchisq(0.95, | ||
| + | [1] 5.991465 | ||
| + | > qchisq(0.99, | ||
| + | [1] 9.21034 | ||
| + | > | ||
| + | </ | ||
| These critical values do not exceed the chi-square value you obtained from your table -- 37.58. How do you want to relate them together? Think about the expected values -- the ideal types. Suppose you obtained the same values (observed values) as those of expected values, what would be your chi-square value? --Yes, it is going to be zero. Why? If you look at the formula | These critical values do not exceed the chi-square value you obtained from your table -- 37.58. How do you want to relate them together? Think about the expected values -- the ideal types. Suppose you obtained the same values (observed values) as those of expected values, what would be your chi-square value? --Yes, it is going to be zero. Why? If you look at the formula | ||
| Line 251: | Line 258: | ||
| 5.991 (0.05 probability) | 5.991 (0.05 probability) | ||
| 9.210 (0.01 probability) | 9.210 (0.01 probability) | ||
| + | |||
| + | OR | ||
| + | < | ||
| + | > pchisq(2.73, | ||
| + | [1] 0.7446193 | ||
| + | </ | ||
| Now the rest of what you need to do is to compare the numbers (chi-square value and the critical values). | Now the rest of what you need to do is to compare the numbers (chi-square value and the critical values). | ||
chi-square_test.1463356315.txt.gz · Last modified: 2016/05/16 08:21 by hkimscil