An alternative hypothesis is a theory that contradicts a null hypothesis. A null hypothesis is an informed assumption about whether your premise is true.

2. Analysis of covariance

Analysis of covariance is a tool for evaluating data sets that contain two variables: effect, which is referred to as the variate, and treatment, which is the categorical variable.

3. Analysis of variance

An analysis of variance (ANOVA) compares the relationship between more than two factors to determine whether there’s a link between them.

4. Average

The average refers to the mean of data. You can calculate the average by adding up the total of the data and dividing it by the number of data points.

5. Bell curve

The bell curve, also called the normal distribution, displays the mean, median and mode of the data you collect.

6. Beta level

The beta level, or simply beta, is the probability of committing a Type II error in a hypothesis analysis, which entails agreeing to the null hypothesis when it isn’t true.

7. Binomial test

When a test has two alternative outcomes, either failure or success, and you know what the possibilities of success are, you may apply a binomial test.

8. Breakdown point

A lower breakdown point means the information may not be useful, whereas a higher number means there’s less chance of resistance.

9. Causation

Causation is a direct relationship between two variables. Two variables have a direct relationship if a change in one’s value causes a change in the other variable.