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​In statistics, analysis of variance (ANOVA) is a collection of statistical models used to distinguish between an observed variance in a particular variable and its component parts. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes a test between these groups. One test often used by statisticians and researchers in their work is the Two-Way ANOVA, which determines the differences--and possible interactions--when variables are presented from the perspective of two or more categories. When a Two-Way ANOVA is implemented, it enables one to compare and contrast variables resulting from independent or joint actions. This brief provides guidance on how R can be used to facilitate Two-Way ANOVA for data analysis and graphical presentation. Along with instruction on the use of R and R syntax associated with Two-Way ANOVA, this brief will also reinforce the use of descriptive statistics and graphical figures to complement outcomes from parametric Two-Way ANOVA.




In statistics, analysis of variance (ANOVA) is a collection of statistical models used to distinguish between an observed variance in a particular variable and its component parts. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes a test between these groups. One test often used by statisticians and researchers in their work is the Two-Way ANOVA, which determines the differences--and possible interactions--when variables are presented from the perspective of two or more categories. When a Two-Way ANOVA is implemented, it enables one to compare and contrast variables resulting from independent or joint actions. This brief provides guidance on how R can be used to facilitate Two-Way ANOVA for data analysis and graphical presentation. Along with instruction on the use of R and R syntax associated with Two-Way ANOVA, this brief will also reinforce the use of descriptive statistics and graphical figures to complement outcomes from parametric Two-Way ANOVA.




In statistics, analysis of variance (ANOVA) is a collection of statistical models used to distinguish between an observed variance in a particular variable and its component parts. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes a test between these groups. One test often used by statisticians and researchers in their work is the Two-Way ANOVA, which determines the differences--and possible interactions--when variables are presented from the perspective of two or more categories. When a Two-Way ANOVA is implemented, it enables one to compare and contrast variables resulting from independent or joint actions. This brief provides guidance on how R can be used to facilitate Two-Way ANOVA for data analysis and graphical presentation. Along with instruction on the use of R and R syntax associated with Two-Way ANOVA, this brief will also reinforce the use of descriptive statistics and graphical figures to complement outcomes from parametric Two-Way ANOVA.


Content:
Front Matter....Pages i-vii
Learn R with Sample Lessons in Education and the Social Sciences, Health, and the Biological Sciences....Pages 1-7
Two-Way Analysis of Variance (ANOVA) Sample 1: Comparison of Scores on a Final Examination by Teaching Method and by Status as a Community College Graduate....Pages 9-29
Two-Way Analysis of Variance (ANOVA) Sample 2: Comparison of Systolic Blood Pressure Readings by Self-Declared Smoking Habits and by Self-Declared Drinking Habits....Pages 31-68
Two-Way Analysis of Variance (ANOVA) Sample 3: Comparison of Larvae Counts by AgChem Formulation and by AgChem Application Time-of-Day....Pages 69-139


In statistics, analysis of variance (ANOVA) is a collection of statistical models used to distinguish between an observed variance in a particular variable and its component parts. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes a test between these groups. One test often used by statisticians and researchers in their work is the Two-Way ANOVA, which determines the differences--and possible interactions--when variables are presented from the perspective of two or more categories. When a Two-Way ANOVA is implemented, it enables one to compare and contrast variables resulting from independent or joint actions. This brief provides guidance on how R can be used to facilitate Two-Way ANOVA for data analysis and graphical presentation. Along with instruction on the use of R and R syntax associated with Two-Way ANOVA, this brief will also reinforce the use of descriptive statistics and graphical figures to complement outcomes from parametric Two-Way ANOVA.


Content:
Front Matter....Pages i-vii
Learn R with Sample Lessons in Education and the Social Sciences, Health, and the Biological Sciences....Pages 1-7
Two-Way Analysis of Variance (ANOVA) Sample 1: Comparison of Scores on a Final Examination by Teaching Method and by Status as a Community College Graduate....Pages 9-29
Two-Way Analysis of Variance (ANOVA) Sample 2: Comparison of Systolic Blood Pressure Readings by Self-Declared Smoking Habits and by Self-Declared Drinking Habits....Pages 31-68
Two-Way Analysis of Variance (ANOVA) Sample 3: Comparison of Larvae Counts by AgChem Formulation and by AgChem Application Time-of-Day....Pages 69-139
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