Applying ANOVA and Non Parametric Tests a. What are three lessons you learned relative ANOVA and Nonparametric tests? While doing the simulation; the three lessons learned are as follows: Monitor – the situation Measure – provide measurements‚ accumulate data Improve – provide solutions for improvement. b. As a result of using this simulation‚ what concepts and analytic tools will you be able to use in your workplace (i.e.‚ how do you expect to apply what you learned)? As a result of using
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Prentice-Hall‚ Inc. Chapter 11 11-2 Student Lecture Notes Chapter Overview Analysis of Variance (ANOVA) One-Way ANOVA Randomized Complete Block ANOVA Two-factor ANOVA with replication F-test F-test TukeyKramer test Fisher’s Least Significant Difference test Business Statistics: A Decision-Making Approach‚ 6e © 2005 Prentice-Hall‚ Inc. Chap 11-3 General ANOVA Setting Investigator controls one or more independent variables Called factors (or treatment variables)
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ANALYSIS OF VARIANCE? WHAT NULL HYPOTHESIS ISTESTED BY ANOVA? ANALYSIS OF VARIANCE IS A STATISTICAL METHOD USED TO TEST DIFFERENCES BETWEEN TWO OR MORE MEANS. IT IS USED TO TEST GENERAL RATHER THAN SPECIFIC DIFFERENCES AMONG MEANS. THUS THE NULL HYPOTHESIS IS CALLED AN OMNIBUS NULL HYPOTHESIS IT MEANS THAT AT LEAST ONE POPULATION MEAN IS DIFFERENT FROM AT LEASTONE OTHER MEAN. THE ANOVA DOES NOT REVEAL WHICH PAIR IS SIGNIFICANT‚ THUS A FOLLOW UP TEST IS NECESSARY TO DETERMINEWHICH PAIR
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treatment group. Thus‚ the analysis test result is carried out using the technique of one-way analysis of variance ANOVA (Analysis of Variance - single factor). Assumptions of ANOVA The assumptions of ANOVA are: Observations were randomly and independently chosen from the populations‚ population distributions are normal for each group; and population variances are equal for all groups. The assumptions of ANOVA are identical to the t-test and the calculated statistic is called an F-value
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purpose of this paper is to explain the logic and vocabulary of one-way analysis of variance (ANOVA). The null hypothesis tested by one-way ANOVA is that two or more population means are equal. The question is whether (H0) the population means may equal for all groups and that the observed differences in sample means are due to random sampling variation‚ or (Ha) the observed differences between sample means are due to actual differences in the population means. The logic used in ANOVA to compare
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CHART FOR STATISTICAL ANALYSIS ANOVA One-way Analysis of Variance (ANOVA) is used with one categorical independent variable and one continuous variable. The independent variable can consist of any number of groups (levels). A statistical technique by which we can test if three or more means are equal. It tests if the value of a single variable differs significantly among three or more levels of a factor. Example: Problem: Susan Sound predicts that students will learn most effectively with a constant
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Marcia Landell Applied Statistics Week 6: Analysis of Variance (ANOVA) Exercise 36 Analysis of Variance (ANOVA) I 1. A major significance is identifiable between the control group and the treatment group with the F value at 5% level of significance. The p value of 0.005 is less than 0.05 indicating that the control group and the treatment group are indeed different. Based on this fact‚ the null hypothesis is to be rejected. 2. Null hypothesis: The mean mobility scores for the control group and
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exposed to three different counselling approaches. The dependent variable‚ self-concept‚ may be measured through a standardized self-concept instrument which yields interval scores for the subjects. In this problem‚ application of the one-factor ANOVA will test the following hypothesis: There is no significant difference in self-concept among the three groups of students exposed to different counselling approaches. Step 1 Enter the data in a worksheet table. (See below.) Step 2 Find the square
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ANOVA Hypothesis Test ANOVA Hypothesis Test Living near a major city can be a positive aspect of being a homeowner or someone who uses real estate as an investment. Increasing population contributes to land and space diminishing‚ resulting in high demand for what is available. Industry and markets are in the city‚ attracting buyers who want to have the convenience of living near commercial properties. The difference in the pay scale between jobs in the city and jobs in the suburbs could
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| Analyzing with ANOVA | Two-Way | | | 1/23/2013 | | Submit your answers to the following questions using the ANOVA source table below. The table depicts a two-way ANOVA in which gender has two groups (male and female)‚ marital status has three groups (married‚ single never married‚ divorced)‚ and the means refer to happiness scores (n = 100): a. What is/are the independent variable(s)? What is/are the dependent variable(s)? The independent variables are gender and marital status
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