Statistics for Managers Using Microsoft Excel Chapter 10 Analysis of Variance (ANOVA)
Chapter 10 Analysis of Variance (ANOVA) Statistics for Managers Using Microsoft Excel
Chapter Goals After completing this chapter,you should be able to: Recognize situations in which to use analysis of variance Understand different analysis of variance designs Perform a single-factor hypothesis test and interpret results Conduct and interpret post-hoc multiple comparisons procedures Analyze two-factor analysis of variance tests
Chapter Goals After completing this chapter, you should be able to: Recognize situations in which to use analysis of variance Understand different analysis of variance designs Perform a single-factor hypothesis test and interpret results Conduct and interpret post-hoc multiple comparisons procedures Analyze two-factor analysis of variance tests
-Is there any difference among suppliers? If there is,which supplier's product is best? Supplier 1 Supplier 2 Supplier 3 Supplier 4 18.5 26.3 20.6 25.4 24.0 25.3 25.2 19.9 17.2 24.0 20.8 22.6 19.9 21.2 24.7 17.5 18.0 24.5 22.9 20.4
Is there any difference among suppliers? If there is, which supplier’s product is best? Supplier 1 Supplier 2 Supplier 3 Supplier 4 18.5 26.3 20.6 25.4 24.0 25.3 25.2 19.9 17.2 24.0 20.8 22.6 19.9 21.2 24.7 17.5 18.0 24.5 22.9 20.4
Chapter Overview Analysis of Variance(ANOVA) Data Analysis Analysis Tools OK Anova:Single Factor Anova:Two-Factor With Replication Cancel Anova:Two-Factor Without Replication Correlation Covariance Help Descriptive Statistics Exponential Smoothing F-Test Two-Sample for Variances Fourier Analysis Histogram
Chapter Overview Analysis of Variance (ANOVA) F-test TukeyKramer test One-Way ANOVA Two-Way ANOVA Interaction Effects
General ANOVA Setting ◆ Investigator controls one or more independent variables Called factors (or treatment variables) Each factor contains two or more levels (or groups or categories/classifications) Observe effects on the dependent variable Response to levels of independent variable Experimental design:the plan used to collect the data
General ANOVA Setting Investigator controls one or more independent variables Called factors (or treatment variables ) Each factor contains two or more levels (or groups or categories/classifications) Observe effects on the dependent variable Response to levels of independent variable Experimental design: the plan used to collect the data