SOC202H1 Lecture Notes - Heteroscedasticity, Null Character, Null Hypothesis

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A lot of people in canada compared to are neither believers nor non- believers. Cases drop off - people who didn"t answer the distress items are not in the issue. Ideal is, you want believers and non believers to be far apart. You don"t want a lot of spread between groups. if u ave believers here and non believers in other side in an index, far apart and uniformity within. Imagine that at some point u have to almost hypothetically, sample after sample, scooping up if null hypothesis is true, if its close to zero, just plot it on frequency distribution. Just like the dice example in the book, if you scoop up a population and it gives you a big difference, something is wrong, or null hypothesis is false. It"s like taking that dice example and pulling that to the example prof. But it"ll be statically significant because the sample population is large.

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