Question

What are the major difference between univariate, bivariate, and multivariate analysis?

What is the difference between correlation and regression?

Inferential statistics allow us to

Answer 1

The major difference between univariate, bivariate and multivariate analysis-

Univariate analysis involves just one variable. For example - Analysing the mean/median/mode of the heights of the population in a city

Bivariate analysis involves two variables. For example- Checking if there is a correlation between the heights and weights of the population in a city

Multivariate analysis involves more than 2 variables. For example- Predicting the selling price of a house based on factors such as the size of the house, proximity to popular spots, climate (in terms of average monthly temperature) etc

Difference between regression and correlation

Regression is primarily establishing a relationship between two or more variables. Here the value of one variable depends on the other(s). For example- Given that crop output is dependent on rainfall, regression finds a relation between these 2 variables in mathematical terms as follows-

Output here is the dependent variable whereas rainfall is the independent variable.

Correlation, on the other hand, gives us the strength of the relationship between the variables. In our example, it would give us an idea of how close is output dependent on rainfall. Correlation is measured using the correlation coefficient and its value ranges from -1 to 1.

The below scatterplots show how the value of r varies depending on the strength of the relationship between crop output and rainfall-

Inferential statistics allow us to draw inferences or conclusion about the population parameters based on the sample statistics. Eg. Drawing a conclusion about the average income of all the residents in a city based on a sample of 1000 residents.