With these results, we do not know which groups are different from which groups, thus it is necessary to conduct multiple comparisons of groups. For this case, the test statistic is significant at an alpha of 0.05. Read the significance of the effect from the ANOVA table depending on your alpha level. The statistics for the combined sample are also displayed. The descriptive statistics table displays the means and the standard deviations by category. The following output will be generated for our analysis. Step 5: Click Continue and click OK to get the one-way ANOVA output inВ SPSS. Step 4: Click the options button to check the descriptive checkbox as shown below. Step 3: Click the Post Hoc button and check the TukeyВ box and click continue. Step 2: In the one-way ANOVA dialogueВ box transfer your dependent variable to the dependent listВ and the independent variable to the factor box as shown below. Step 1: Click Analyze > Compare Means > One-Way ANOVA, The screenshot is shown below Step by Step Analysis of one-way ANOVA data in SPSS Follow the following procedures to run the data analysis in SPSS. Therefore, there are three-course levels: beginner, intermediate and advanced course level. The following procedures relate to an analysis which was conducted to determine the time that the students took to complete a set of problems based on the course level. Remember that the first three assumptions are related to the data collection procedures. This assumption can be tested in SPSS using the Levene's test of homogeneity of variances. The Shapiro-Wilk normality test can be used to test the assumption in SPSS.ДЄssumption 6: The homogeneity of variances assumptions. The outliers can be detected by use of a Boxplot, a boxplot of each of the categories and the dependent.ДЄssumption 5: The distribution of the dependent variable for each of the category of the independent variable should be approximately normal. The observations for each group must be independent.ДЄssumption 4: No significant outliers.В Outliers can reduce the validity of your results. Generally, people will always use the independent two-sample t-test when they have two groups.ДЄssumption 3: Your observations must be independent. The assumption can be met by ensuring that appropriate data measurements are used when collecting the data.ДЄssumption 2: You should have at least two categories for the independent variable. Thus, it is an Omnibus test.Д«efore conducting an analysis using a one-way ANOVA, it is important to assess whether your data meets the following assumptions.ДЄssumption 1: The dependent variable should be measured on a continuous scale, i.e the variable should either interval or ratio. Remember that you can differentiate which group is different from which group when you use a one-way ANOVA. For example, one might be interested in testing how the students perform in an exam based on their anxiety level (low, medium and high-stressed). You will rarely see a comparison being made between two categories but it is a common practice especially inВ coursework activities to see three or more groups. The independent variable in a one-way ANOVA is called a factor and the categories of the variable are called factor levels. This model (the one-way ANOVA) is used to determine if there is a significant difference between the means of two or more independent groups given a continuous dependent variable.

One way anova spss