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Module Evaluation Report
Module Evaluation Report

... Chapter 5 – The normal distribution 5.1 Probability distributions of continuous random variables A random variable X is called continuous if it can assume any of the possible values in some interval i.e. the number of possible values are infinite. In this case the definition of a discrete random var ...
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... did very poorly or very well on the test…but the mean was the same as period 3! The mean is not a good measurement of the performance of the students in Period 6 because most students didn’t get a C. • We use standard deviation to figure out if the mean is representing an accurate view of what is go ...
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Sample Exam Questions

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... difference by manipulating your independent variable. A p-value of .05 means that you will be wrong approximately 5% of the time if you reject the null hypothesis. In most psychology experiments, we require a p-value less than .05 to conclude that a significant difference exists between the samples ...
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... (D) Without knowing the number of test items, it is impossible to determine the better score. (E) Without knowing the number of students taking the exam in the county, it is impossible to determine the better score. 4. The heights of American men aged 18 to 24 are approximately normal with a mean of ...
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Unit 1 Review Packet

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Sample Size and Errors - Gail Johnson`s Research Demystified

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Review 6 with Answers

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Introduction to Hypothesis Testing

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Final Exam Review

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Comparing Means … Independent Samples

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The Assumptions of ANOVA - ROHAN Academic Computing

... – The residual mean square is the unbiased estimator of 2, the variance of a single observation – The between treatment mean squares takes into account not only the differences between observations, 2, just like the residual mean squares, but also the variance between treatments – If there was non ...
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... – fixed, unknown number that describes the population – known value calculated from a sample – a statistic is often used to estimate a parameter ...
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sampling distribution

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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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