When we test for differences between the means of two independent populations, we can only use a two-tailed test.
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Q. 2The Central Limit Theorem does not apply to the sample means of large samples drawn from a discrete distribution.
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Q. 3The sample size in each independent sample must be the same if we are to test for differences between the means of 2 independent populations.
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Q. 4The Central Limit Theorem describes the distribution of the sample mean except for populations that are normal.
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Q. 5Two samples of sizes 25 and 20 are independently drawn from two normal populations, where the unknown population variances are assumed to be equal. The number of degrees of freedom of the equal-variances t-test statistic is 44.
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Q. 6According to the Central Limit Theorem, for large samples the standard error of the sample mean is the population standard deviation divided by the square root of the sample size.
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Q. 7When the necessary conditions are met, a two-tail test is being conducted to test the difference between two population means, but your statistical software provides only a one-tail area of 0.045 as part of its output. The p-value for this test will be 0.09.
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Q. 8The sampling distribution of the sample mean is exactly normally distributed, regardless of the sample size n.
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Q. 9In testing the difference between two population means using two independent samples, the population standard deviations are assumed to be known, and the calculated test statistic equals 2.75 . If the test is two-tail and 5 level of significance has been specified, the conclusion should not be reject the null hypothesis.
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