CHAPTER 9 Hypothesis Tests CONTENTS 9.4 POPULATION MEAN: σ UNKNOWN One-Tailed Test Two-Tailed Test Summary and Practical Advice 9.5 POPULATION PROPORTION Summary 9.6 HYPOTHESIS TESTING AND DECISION MAKING 9.7 CALCULATING THE PROBABILITY OF TYPE II ERRORS 9.8 DETERMINING THE SAMPLE SIZE FOR A HYPOTHESIS TEST ABOUT A POPULATION MEAN STATISTICS IN PRACTICE: JOHN MORRELL & COMPANY 9.1 DEVELOPING NULL AND ALTERNATIVE HYPOTHESES The Alternative Hypothesis as a Research Hypothesis The Null Hypothesis
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follows: The Steps in Testing a Research Hypothesis Hypothesis testing begins with a statement and assumption that determines the population of the mean, (Lind, 2011, p.288.). The five steps listed in Lind are as follows: 1. State null and alternate hypothesis 2. Select a level of significance 3. Identify the test statistic 4. Formulate a decision rule 5. Take a sample and arrive at decision However in McClave, 2011, pages 324 and 325 the steps for testing of a hypothesis are listed as “Elements
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Nonparametric Hypothesis Testing RES/342 Nonparametric Hypothesis Testing During the course of the last three weeks, the team explored the hypothesis testing segment of statistics research. The first part of this assignment was the one sample hypothesis testing. The second was the two or more sample hypothesis testing, and finally in this third week, we will look at nonparametric hypothesis testing. This week’s project is a continuation of the previous projects and entails to build on
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series are best displayed in a scatter plot. The series value X is plotted on the vertical axis and time t on the horizontal axis. Time is called the independent variable (in this case however, something over which you have little control). There are two kinds of time series data: Continuous, where we have an observation at every instant of time, e.g. lie detectors, electrocardiograms. We denote this using observation X at time t, X(t). Discrete, where we have an observation at (usually regularly)
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draw valid and reliable conclusions about the population on the basis of the sample. It helps him decide whether to accept or eject a hypothesis after evaluating the sample. Statistical hypothesis Hypothesis is a theory, claim or assertion about a particular parameter of a population. It needs to be proven true. Once proven true, it is accepted; otherwise, it is rejected. Types of hypothesis: 1. Null hypothesis (Ho) is always one of status quo or no difference. Example: Ho : The mean
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“Inferential Statistics, Hypothesis Testing” Marketing Research MAHFOUD SOUKAINA Supervised by: Dr. Kim Chung Friday, April 16th, 2010 TABLE OF CONTENTS I. Introduction: Marketing Research 4 1) Marketing Research 4 2) The Marketing Research process 4 II- Body 1: Litterature Review 6 1) Inferential Statistics 6 a) Dummy Variables 7 b) Experimental Analysis 7 2) Normal Distribution 8 Figure 1: A normal
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limit theorem. Question 2 – Explain the essence of Hypothesis testing. How related are null hypothesis and Alternative Hypothesis. How do you apply confidence interval in hypothesis testing? Question 3 – Explain the difference between T distribution and Z distribution. When and how do we use T distribution? What is the meaning of the number of degrees of freedom? Left Tail, right tail, 2 tail test: Try to understand the idea of hypothesis testing! Understand how all are participating. The confidence
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Methods 4 3 Hypothesis Testing 5 3.1 Hypothesis 1 – Average Income level 5 Descriptive Statistics 5 Hypothesis of the test 5 Statistical Findings 6 Interpretation of results 6 3.2 Question 2: Satisfaction level between gender 7 Descriptive statistics 7 Hypothesis 7 Method used and nature of the test 7 Reporting of statistical analysis 8 Interpretation of results 8 3.3 Question 3: Difference between satisfaction levels across business divisions. 9 Descriptive Statistics 9 Hypothesis 9 Method
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to Hypothesis Testing Significance testing is used to help make a judgment about a claim by addressing the question, Can the observed difference be attributed to chance? We break up significance testing into three (or four) steps: Step A: Null and alternative hypotheses The first step of hypothesis testing is to convert the research question into null and alterative hypotheses. We start with the null hypothesis (H0). The null hypothesis is a claim of “no difference.” The opposing hypothesis is the
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and interpretation of statistical findings through applications and functions of statistical methods. Policies Faculty and students/learners will be held responsible for understanding and adhering to all policies contained within the following two documents: • University policies: You must be logged into the student website to view this document. • Instructor policies: This document is posted in the Course Materials forum. University policies are subject to change. Be sure to read
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