The success-failure condition different kinds of inference about proportions Many statistical inferences about sample proportions rely...
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The success-failure condition different kinds of inference about proportions Many statistical inferences about sample proportions rely on a normal approximation of the sampling distribution of proportions, but it is not always wise to rely on this approximation; instead, we should first make sure that the success-failure conditions are met. You have been introduced to three separate "success-failure conditions" that are appropriate for different kinds of inference about sample proportions. Which of the following success-failure conditions goes with which kind of statistical inference? Choose only one of these success-failure conditions per question for Questions 4 through 6 and write the letter of your choice in the blank. a. nл 10 and n(1-0) ≥10 b. np 10 and n(1-p) ≥ 10 c. nippooled ≥10 and n₁(1-Ppooled) ≥ 10, and n₂Ppooled 10 and n₂(1-Ppooled) ≥ 10 (1) A test for independence between two indicator variables: (2) A confidence interval for one sample proportion: (3) A goodness-of-fit test for one sample proportion: The success-failure condition different kinds of inference about proportions Many statistical inferences about sample proportions rely on a normal approximation of the sampling distribution of proportions, but it is not always wise to rely on this approximation; instead, we should first make sure that the success-failure conditions are met. You have been introduced to three separate "success-failure conditions" that are appropriate for different kinds of inference about sample proportions. Which of the following success-failure conditions goes with which kind of statistical inference? Choose only one of these success-failure conditions per question for Questions 4 through 6 and write the letter of your choice in the blank. a. nл 10 and n(1-0) ≥10 b. np 10 and n(1-p) ≥ 10 c. nippooled ≥10 and n₁(1-Ppooled) ≥ 10, and n₂Ppooled 10 and n₂(1-Ppooled) ≥ 10 (1) A test for independence between two indicator variables: (2) A confidence interval for one sample proportion: (3) A goodness-of-fit test for one sample proportion:
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Related Book For
Essentials of Statistics for the Behavioral Sciences
ISBN: 978-1285056340
8th Edition
Authors: Frederick J Gravetter, Larry B. Wallnau
Posted Date:
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