## How to Create and Analyze Variables using a Likert Scale

In statistics, research variables can be measured in parametric and non-parametric variables. Variables measured by interval scale and ratio scale are grouped in parametric variables.

In statistics, research variables can be measured in parametric and non-parametric variables. Variables measured by interval scale and ratio scale are grouped in parametric variables.

Variance and standard deviation are components of statistical values that are most often found in descriptive analysis. When we perform statistical software analysis, we will find the value of variance and standard deviation if we enable descriptive statistics.

Will a high variance value affect the statistical test on linear regression? Many questions related to this topic were Kanda Data obtained. On this occasion, Kanda Data will discuss the impact of the variance value on hypothesis testing on linear regression.

The linearity test is one of the assumption tests in linear regression using the ordinary least square (OLS) method. The objective of the linearity test is to determine whether the distribution of the data of the dependent variable and the independent variable forms a linear line pattern or not?

One of the assumptions in linear regression using the ordinary least square (OLS) method is that there is no strong correlation between independent variables. To get the Best Linear Unbiased Estimator in linear regression with ≥ 2 independent variables, you must be fulfilled the non-multicollinearity assumption.