Running head: DATA ANALYSIS AND APPLICATION ONE-WAY ANOVA 1 Data Analysis and Application of a One-Way ANOVA Capella University
DATA ANALYSIS AND APPLICATION OF A ONE-WAY ANOVA 2 Introduction In this assignment, data analysis and application for a one-way ANOVA comparing quiz3 scores across all three sections of a class. Analysis of variance (ANOVA) is a statistical analysis that tests whether there are statistically significant differences between group means on scores on a quantitative outcome variable across two or more groups (Warner, 2013). A one-way ANOVA is appropriate to use when a researcher is comparing more than two groups. Section 1: Data File Description In this one-way ANOVA, the mean scores on quiz3 across three sections will be compared. The independent variable is the section and it is a nominal scale of measurement. In a one-way ANOVA, the independent variable is called a factor (Warner, 2013). The factor is the sections. The other variable, quiz3, is an interval scale of measurement. Across all three sections there are 105 students which is the sample size. Section 2: Testing Assumptions The assumptions will be tested by analyzing the figures below. Assumption 1 is that the outcome variable will be normally distributed. This assumption will be determined by visually analyzing the histogram in figure 1. Assumption 2 is independence of observation (Warner, 2013). This assumption is based on setting up the research correctly and cannot be tested visually. Assumption 3 is homogeneity of variance (Warner, 2013). This is the assumption that the variances of the outcome variable of all three sections will be equal.
DATA ANALYSIS AND APPLICATION OF A ONE-WAY ANOVA 3 Figure 1. SPSS Histogram output for quiz3.