### regression analysis

Regression analysis

Regression analysis requires describing the relation between the dependent variable and one or more individual variables.

The framework of the relationship is theorized, and estimates of these parameter measures are used to create the estimated regression equation.

Several tests are then used to determine if this model is acceptable.

If this model is deemed acceptable, the calculated regression equation will be used to indicate the value of the dependent variable had measures for the individual variables.

The word correlation is used in daily life to refer some kind of organization.

We might say that we have found the correlation between cloudy times and attempts of wheeziness.

Nevertheless, in statistical terms we have statistics to denote association between two quantifiable variables.

We also assume that the organization is linear, that one variable increases or decreases the limited amount for one part gain or change in the other.

The other method that is frequently used in these conditions is regression, which requires calculating the best straight line to summarize the organization.

Statistics and regression analysis are linked in this meaning that both consider with relationships among variables.

This correlation coefficient is The method of linear union between two variables.

Measures of this correlation coefficient exist usually between -1 and 1.

The correlation coefficient of 1 suggests that two variables are perfectly related in the positive linear meaning, the correlation coefficient of -1 suggests that two variables are absolutely linked

in the negative linear sense, And the correlation coefficient of 0 suggests that there is no one-dimensional relation between these two variables.

For easy linear regression, the distribution correlation coefficient is the square root of this coefficient of judgment, with this mark of this correlation coefficient being the one as the

mark of B1, This constant of X1 in the calculated regression equation.

Regardless of what you’re using statistics and regression to look, using the business information structure is the best choice to clearly study the information you’re seeing around in a way

that is easy to pinpoint which actionable insights to take.

Mining the information with the business intelligence structure allows for easy testing of large data, real-time information, and unstructured data and define areas for improvement and other noteworthy trends