------o0o------ CHAPTER 14: CHI-SQUARE TESTING STATISTICS FOR BUSINESS TAs: Vo Vuong Van Anh‚ Le Phuoc Thien Thanh‚ and Le Nhat Ho December 21‚ 2013 TABLE OF CONTENTS • PART I: CHI-SQUARE TESTING FOR GOODNESS-OF-FIT. • PART II: CHI-SQUARE TESTING FOR NORMAL DISTRIBUTION. • PART III: CHI-SQUARE TESTING FOR INDEPENDENCE. December 2013 Powered by Vo Vuong Van Anh 2 1 12/21/2013 Hypothesis Testing Procedure for Chi-Square Testing 5 Steps to Perform an Chi-Square Testing STEP 01 State the null
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you conduct a chi-square test of independence‚ what is the expected frequency count of male Independents? b) If you conduct a chi-square test of independence‚ what is the expected frequency count of female Democrats? c) If you conduct a chi-square test of independence‚ what is the observed count of female Independents? d) If you conduct a chi-square test of independence‚ what is the expected frequency count of male Republicans? e) If you conduct a chi-square test of independence
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THE CHI-SQUARE GOODNESS-OF-FIT TEST The chi-square goodness-of-fit test is used to analyze probabilities of multinomial distribution trials along a single dimension. For example‚ if the variable being studied is economic class with three possible outcomes of lower income class‚ middle income class‚ and upper income class‚ the single dimension is economic class and the three possible outcomes are the three classes. On each trial‚ one and only one of the outcomes can occur. In other words‚ a family
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Individual Paper #3: Non parametric and Chi-square distribution Brief Summary: I worked for a logistic company. My major responsibility was in charge of the storage and transportation of parts of cars between two areas‚ which are about 1400 miles apart. One of my jobs is collecting the goods from suppliers and arranging the trucks to deliver them. There are five truck drivers‚ and each of them is assigned to deliver on each weekday throughout a whole year. Before the delivery
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Chi-Square Homogeneity Test The purpose of a chi-square homogeneity test is to compare the distributions of a variable of two or more populations. As a special case‚ it can be used to decide whether a difference exists among two or more population proportions. For a chi-square homogeneity test‚ the null hypothesis is that the distributions of the variable are the same for all the populations‚ and the alternative hypothesis is that the distributions of the variable are not all the same (i.e.‚ the
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Drosophila melanogaster: Mutant Fruit Flies Jessica E. Phillips Genetics 3301 April 13‚ 2012 Introduction: Drosophila melanogaster better known as the fruit fly can be found near rotting fruits‚ vegetables‚ or anywhere where there is food that has rotted and or fermented. (Potter‚ 2010) D. melanogaster has four different stages in its life cycle. The first stage of D. melanogaster is the egg which can last for about one day; then turns into a larva. The larva stage last for about 7-8 days
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Chi-square tests 1. INTRODUCTION 1.1 χ2 distribution and its properties A chi-square (χ2) distribution is a set of density curves with each curve described by its degree of freedom (df). The distribution have the following properties: - Area under the curve = 1 - All χ2 values are positive i.e. the curve begins from 0 (except for df=1) increases to a peak and decreases towards 0 as its asymptote - The curve is skewed to the right‚ and as the degree of freedom increases‚ the
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IB Math Studies Spring 2013 Table of Contents: Introduction/Purpose……………………………………………………………..p.3 Data Collection Method……………………………………………………….....p. 3 - 4 Data Analysis: Chi-Squared Statistic Frequency Table…………………………………………………………p. 4 - 5 Contingency Table……………………………………………………….p. 5 – 6 Chi – Squared Statistic…………………………………………………...p. 7 Degrees of Freedom………………………………………………………p. 7 Critical Value……………………………………………………………..p. 7 – 8 Conclusion……………………………………………………………………
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The Chi-Square (x2) Goodness-of-Fit Test: What It Is and What It Does The chi-square (x2) goodness-of-fit test is used for comparing categorical information against what we would expect based on previous knowledge. As such‚ it tests what are called observed frequencies (the frequency with which participants fall into a category) against expected frequencies (the frequency expected in a category if the sample data represent the population). It is a non-directional test‚ meaning that the alternative
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in researching and preparing this book. Also I would like to thank Dorothy Cummings; my editor‚ Jeff Soloway; Lauren Goldberg; and everyone else at Facts On File who helped prepare this volume. iv INTRODUCTION China covers nearly 4 billion square miles in Asia‚ roughly 14 percent of the world’s landmass. It has grasslands and deserts‚ a long coastline‚ and some of the highest mountains in the world. Its rich river
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