Differences

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--- chi-square_test [2016/05/16 08:13] – hkimscil
+++ chi-square_test [2016/05/16 08:15] – hkimscil
@@ Line 261: / Line 261: @@
 In the first place, you assumed that there would be no differences in the abortion issue among the religious groups to get the expected values. And you compared the expected values to the observed values. In other words, you tested your survey result (the observed values) against the idea of "no difference." Your plans were: If the some of the comparison (chi-square) is big enough, you'd say that the idea of "no difference" was not likely true. If the some of the comparison (chi-square) is small enough, you'd say that there seems to be no reason to reject the idea of "no difference." In other words, in the first place, you assumed that there would be no difference, and you tested your survey result against this idea. What you conclude from this testing was you failed to disapprove the idea -- the idea of no differences.
-{{raritan-river-01.jpg?132|Princeton Park river}} __Why null?__ -- Someone in the class cleverly asked why we should use null hypothesis in the first place. As you see the above, it would be harder to test whether the researcher is right. Most statistic methods (chi-square, t-test, ANOVA, and others) test against the idea of 0 (zero -- no difference).
+{{raritan-river-01.jpg?132 |Princeton Park river}} __Why null?__ -- Someone in the class cleverly asked why we should use null hypothesis in the first place. As you see the above, it would be harder to test whether the researcher is right. Most statistic methods (chi-square, t-test, ANOVA, and others) test against the idea of 0 (zero -- no difference). Therefore, it would not have been safe, had you ever said, "Sure 45% and 62.5% are different."
-Therefore, it would not have been safe, had you ever said, "Sure 45% and 62.5% are different."
 __Another note:__ You might have a question... Hey, wait a minute... If I pick up some other numbers from the chi-square distribution table, the result would be totally different!
+<WRAP clear />
-*** For your information, the table looks as follows. And the chi-square value you got from your data was 2.73.
+For your information, the table looks as follows. And the chi-square value you got from your data was 2.73.
 | df  | .30  | .20  | .10  | .05  | .02  | .01  | .001  |
 | 1  | 1.074  | 1.642  | 2.706  | 3.841  | 5.412  | 6.635  | 10.827  |