'Critical value approach' diaporamas de présentation

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A review of key statistical concepts

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Tests of Significance

Tests of Significance. An Inference Procedure We will study a procedure for learning about the unknown population mean on a quantitative variable. Background .

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Ch. 9 Fundamental of Hypothesis Testing

Ch. 9 Fundamental of Hypothesis Testing. There two types of statistical inferences, Estimation and Hypothesis Testing Hypothesis Testing: A hypothesis is a claim (assumption) about one or more population parameters. Average price of a six-pack in the U.S. is ? = $4.90

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T-tests continued

T-tests continued. Outline. Review the One-sample case Independent samples Basics Unequal N Example Issues Paired samples Basics Examples Comparing formulas Conclusion. Two samples. Previously compared sample mean to a known population mean Now want to compare two samples

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Confidence Interval for Population Mean

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Hypothesis Testing

Hypothesis Testing. An Inference Procedure We will study procedures for both the unknown population mean on a quantitative variable and the unknown population proportion on a qualitative variable. Background .

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Chapter 9 Learning Objectives

Chapter 9 Learning Objectives. Population Mean: s Unknown. Population Proportion. Tests About a Population Mean: s Unknown. Tests About a Population Mean: s Unknown. Test Statistic. This test statistic has a t distribution with n - 1 degrees of freedom.

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Multiple Comparisons

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Chi squared

Chi squared . A biologist randomly selects 20 fruit flies. All of them are placed in a tube with vinegar on one side and mustard on the other side. Do these fruit flies have a preference for either mustard or vinegar? The results are listed below. mustard : 5 vinegar: 15 .

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Chapter 12 Tests of Goodness of Fit and Independence

Chapter 12 Tests of Goodness of Fit and Independence. Goodness of Fit Test: A Multinomial Population . Test of Independence. Goodness of Fit Test: Poisson and Normal Distributions. Hypothesis (Goodness of Fit) Test for Proportions of a Multinomial Population.

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Correlation

Correlation. Review. We saw in the past that when you have two numeric or quantitative variables one thing to explore is the correlation between the two variables. The basic idea is to see if as one variable changes is there a systematic change in the other variable.

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