This article gives a brief description about the types of variables in statistics and research and the different ways in which they can be used. A statistic is a number that describes some aspect of a population. It can be used to understand the characteristics of that population, and it can help you make informed decisions. Statistics are used in research, which is the process of investigating questions about phenomenon using evidence from experiments or surveys. There are many different types of statistics; this article covers three: descriptive statistics, inferential statistics, and causal inference.

Descriptive statistics provide information about the distribution (shape) and variability (size) of samples from a population. This type of statistic helps you understand how your sample differs from the population. For example, you can use descriptive statistics to find out how many people in your sample are female and how much variability there is in the size of samples from different populations.

Inference is the process of working out relationships between variables based on evidence collected in an experiment or survey. Inference helps us make predictions about what will happen as a result of changes to one variable (the independent variable) when another variable (the dependent variable) is changed. For example, if you want to know whether eating fast food increases rates of obesity, you would carry out an experiment measuring weight and height before and after people eat fast food.

Causal inference is the process of trying to find out why one event (the cause) leads to another event (the effect). Causal inference can be used to determine whether one factor causes other factors, and it can also help us understand how two or more factors are related. For example, if you want to know how smoking cigarettes affects your health, you might conduct a study in which participants smoke cigarettes for a few days and then have their blood samples taken. There are many different types of statistics, and this article covers three: descriptive statistics, inferential statistics, and causal inference. Descriptive statistics are used to describe the characteristics of a population. They include measures such as mean, median, and range. Descriptive statistics can be used to find out how many people in your sample are female and how much variability there is in the size of samples from different populations.

Inferential Statistics help us make predictions about what will happen as a result of changes to one variable (the independent variable) when another variable (the dependent variable) is changed. For example, if you want to know whether eating fast food increases rates of obesity, you would carry out an experiment measuring weight and height before and after people eat fast food.