Correlation analysis is the statistical tool that measures the relationship between two items. It describes the degree to which one variable is linearly related to another. To begin correlation analysis, firstly we have to select a field that we will make a research in. The collection of data whose properties are analyzed is called 'population'. The population is the complete collection to be studied; it contains all subjects of interest.
When we compare the correlation between two items, one item is called the 'dependent variable' and the other is 'independent variable'. The goal is to see if a change in the independent item will result in a change in the dependent item. In statistical terms, a hypothesis is a statement concerning the value of a population parameter. Alternative hypothesis is the hypothesis that we try to establish, and null hypothesis is "opposite" of the alternative hypothesis.
Statistics brings its features into different fields of business activity. I think that most often we use correlation analysis in Economics, Marketing, Finance, and other fields. It helps us to establish the relationship between two particular objects, measure the degree of association between them as two variables. I think that correlation analysis is very useful as it can help us to establish the relationship between different objects, predict some economical events, make some important decisions, analyzing statistical data and the behavior of that data.
I would like to consider several situations it which correlation analysis can be used. For example, we want to analyze security's price and an indicator. Security's price here is a dependent variable, while an indicator is an independent variable. The population we are investigating is securities. The alternative hypothesis we develop here assumes that the price of security is influenced by the indicator,