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8-3  Statistics: Range and Standard Deviation
8-3 Statistics: Range and Standard Deviation

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... about a population based on data that we gather from a sample • Study results will vary from sample to sample strictly due to random chance (i.e., sampling error) • Inferential statistics allow us to determine how likely it is to obtain a set of results from a single sample • This is also known as t ...
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... combine them in some simple “2-dimensional confidence interval” for the pair ¹; ¾ 2 Note 2: Both estimates require the assumption that the data is coming from a normal distribution. This is a bit of a tall order, however it happens that applying a typical nonparametric test for normality to this dat ...
Hypothesis Testing - Personal.kent.edu
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... Much has been made of the concept of experimenter bias, which refers to the fact that for even the most conscientious experimenters there seems to be a tendency for the data to come out in the desired direction. Suppose we use students as experimenters. All the experimenters are told that subjects w ...
This file has the solutions as produced by computer
This file has the solutions as produced by computer

... way of rejecting the null hypothesis (that the mean is overweight). If we are following test #1, where the critical region is the right tail, we are in the acceptance region at any level lower than 8.247%, like the usual 1%, 5%, or even 8%, that is, at these levels, we cannot reject the hypothesis t ...
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Student's t-test

A t-test is any statistical hypothesis test in which the test statistic follows a Student's t-distribution if the null hypothesis is supported. It can be used to determine if two sets of data are significantly different from each other, and is most commonly applied when the test statistic would follow a normal distribution if the value of a scaling term in the test statistic were known. When the scaling term is unknown and is replaced by an estimate based on the data, the test statistic (under certain conditions) follows a Student's t distribution.
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