In ANOVA our interest lies in knowing if one continuous dependent variable is affected by one or more categorical independent variables. MANOVA is an extension of ANOVA where we are now able to understand how several dependent variables are affected by independent variables. For example consider an investigation where a ... [Read more...]

One way, two way and n way ANOVA are used to test difference in means when we have one, two and n factor variables. A key assumption when performing these ANOVAs is that the measurements are independent. When we have repeated measures this assumption is violated, so we have to ... [Read more...]

One way analysis of variance helps us understand the relationship between one continuous dependent variable and one categorical independent variable. When we have one continuous dependent variable and more than one independent categorical variable we cannot use one way ANOVA. When we have two independent categorical variable we need to ... [Read more...]

When we are interested in finding if there is a statistical difference in the mean of two groups we use the t test. When we have more than two groups we cannot use the t test, instead we have to use analysis of variance (ANOVA). In one way ANOVA we ... [Read more...]

The paired samples t test is used to check if there are any differences in the mean of the same sample at two different time points. For example a medical researcher collects data on the same patients before and after a therapy. A paired t test will show if the ... [Read more...]

The independent t test is used to test if there is any statistically significant difference between two means. Use of an independent t test requires several assumptions to be satisfied. The assumptions are listed below The variables are continuous and independent The variables are normally distributed The variances in each ... [Read more...]