# Everything you need to know for Stats Test II Term Test 2

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1. Assumptions for using (1-)100% Confidence Interval for two populations when σ is known
• 1) Two samples are random & independent
• 2) Both samples came from two independent, normal populations
• 3) σ121) and σ222) are known
2. Assumptions for using (1-)100% Confidence Interval for t-distribution
• 1) Two samples are random & independent
• 2) Both samples came from normal populations
• 3) σ121) and σ222) are unknown but equal
3. The point estimator for the unknown common variance σ2 is
sp2
4. To test the hypothesis about unknown p1 & p2
we combine the information given in both samples to compute estimated variance of p1 & p2
5. To construct a (1-)100% confidence interval for p1 and p2
we do NOT combine the information contained in both samples to compute the estimated variance
6. A goodness of fit test
Tests the Null Hypothesis that the observed frequencies follow a pattern or theoretical distribution. The test is goodness-of-fit because the hypothesis tested is how good the observed frequencies fit a given pattern
7. The -squared goodness of fit test
used to test whether of not the sampled multinomial data is in agreement with the hypothesized distribution. OR Testing 3 or more unknown population proportions.
8. In a goodness of fit test, when is the Null Hypothesis rejected?
A good agreement between the observed and expected frequencies results in a small value of . A perfect agreement would result in =0. Thus the Null Hypothesis is rejected if is large [upper tail test]
9. For tests of Independence between Criterion A and B...
Ho: The two criteria A&B are
INDEPENDENT or not related (HoI)
10. For tests of Independence between Criterion A and B...
HA: The two criteria A&B are