Types of Variables
Independent Variable: The variable that is manipulated by the researcher, such as treatment, and/or the variable(s) that that is/are thought to affect the outcome.
Dependent Variable: The variable that is measured as a study outcome; the variable of interest; the variable that is thought to depend on the independent variable(s).
Hypothesis Testing
Hypothesis testing allows us to draw inferences by rejecting or failing to reject the null hypothesis
Null hypothesis: The claim about the population – there is no difference or association.
Alternative hypothesis: The claim about the population – there is a difference or association
Statistical Testing
Type 1 Error: An error made when the null hypothesis is rejected and there truly is no difference/association.
Type 2 Error: An error made when the null hypothesis is not rejected and there truly is a difference/association.
p value: The probability of getting a value as or more extreme than the one you observed if the null hypothesis is true. If p <.05, you are more certain that there is a true difference, and that difference is not due to chance or normal variation.
Power: The chance of detecting a difference if there is one.
