Statistics

Mean, Median, Mode, and Range

The mean is the average of all numbers and is found by adding all data points and dividing by the number of data points.
The median is the middle value when a data set is ordered from least to greatest. If there’s an even number of observations, the median is the average two middle numbers.
The mode is the value that appears most frequently in a data set. A set may have one mode, more than one mode, or no mode at all.
The range describes the difference between the lowest and highest figures in the set. It is calculated by subtracting the smallest observation from the greatest.

Standard Deviation and Variance

Variance measures how spread out the members of a data set are. It’s an extremely useful property and many of the commonly used statistical models and formula rely on it.
Standard Deviation is another measure of variation in statistics. It’s widely used because it’s expressed in the same units as the original data, which makes it relatively easy to interpret.

Probability

Probability measures the likelihood of a particular event occurring. It’s important to understand this concept, as it occurs in many statistical theories.
A probability distribution describes the possibilities for a random variable. It can either be discrete (like a coin flip) or continuous (like weight or height).

Hypothesis Testing

Hypothesis testing can be used to determine what outcomes of a study would lead to a rejection of the null hypothesis for a pre-specified level of significance.
It uses sample data to make inductive inferences about population parameters.

Regression and Correlation

Regression analysis helps understanding how the value of the dependent variable changes when any one of the independent variables is varied.
Correlation measures the strength and direction of association between two variables. There’s positive (+), negative (-), and no correlation (0).

Remember to study each topic thoroughly and understand each concept deeply. While it’s important to remember the definitions of key terms, it’s more important to understand how to apply them in a statistical analysis.