The term 'experimental design' refers to a plan for assigning experimental units to treatment conditions. A good experimental design serves three purposes.
Causation: It allows the experimenter to make causal inferences about the relationship between independent variables and a dependent variable.
Control: It allows the experimenter to rule out alternative explanations due to the confounding effects of extraneous variables, i.e., variables other than the independent variables.
Variability: It reduces variability within treatment conditions, which makes it easier to detect differences in treatment outcomes.
In this Module, you will learn how to use experimental design.
Next, you will become familiar with chi-square tests which tests for different purposes. A chi-square test, for testing goodness of fit, is used to decide whether there is any difference between the observed (experimental) value and the expected (theoretical) value. For example, given a sample, we may like to test if it has been drawn from a normal population.
Lastly, we bring the whole course together by learning about the powerful tool of regression analysis.
The basic concept of experimental design.
How to use the one-way analysis of variance to test for differences among the means of several groups.
When and how to use a randomized block design.
How to use two-way analysis of variance and interpret the interaction effect.