Sample proportion vs sample mean
[DOC File]Name:___________________________________
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A) narrower when the sample proportion is 0.10 than when the sample proportion is 0.45. B) wider for 90% confidence than for 95% confidence. C) narrowest when the sample proportion is 0.5. D) narrower for a sample size of 50 than for a sample size of 100. E) wider when the sample proportion is 0.95 than when the sample proportion is 0.55.
[DOCX File]Wiley
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Which sample proportion correct would provide the greatest evidence that people have ESP: (If we assume the sample size is the same in every case.) p = 0.1 p = 0.25 p = 0.4 p = 0.7Since ESP means more correct. c). Write down the null and alternative hypotheses for testing whether people have ESP: H. 0: p = 0.2 . where p is the proportion ...
[DOC File]Topic 162: Sampling Distributions I: Proportions (Day Two)
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Parameter (Sample) Statistic Proportion “p-hat” Mean “mu” “x-bar” Standard Deviation “sigma” Identify each of the following as a parameter or statistic, indicate the sysmbol, and state the population of interest. The proportion of American voters from the 1996 election who voted for Ross Perot.
[DOC File]1 .edu
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So, it is a two sample proportion problem. A. The data is continuous (amount of ice cream), so it is a mean problem. There. is also only one sample of 20. One sample mean. C. The data is continuous (productivity), so it is a mean problem. Keyword: “same”. E. The data is categorical (male/female), so it is a proportion problem. There are
[DOC File]WAYLAND BAPTIST UNIVERSITY
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Sample mean vs. population mean (σ known) Sample mean vs. population mean (σ unknown) Sample proportion vs. population proportion Tests for differences in two means. Tests for differences in two variances Tests for differences in more than two mean. Tests for differences between two or more population proportions
[DOC File]ST 361 Normal Distribution
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II. Sampling Distribution of a Sample Mean (a) X ~ Normal Distribution (b) X ~ Non-normal Distribution. III. Central Limit Theorem. IV. Sampling Distribution of the Sample Proportion p-----I. Sampling Distribution. Population vs. Sample: Population (or process) = The object of interest (for which we would like to make inference
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