Tag: statistics
How to Calculate Price Elasticity from Linear Regression Equation
Researchers and practitioners often calculate elasticity to see the response of a variable due to changes in other variables. The measure of the degree of response or the degree of sensitivity is called elasticity. The elasticity value is often used to predict changes in demand or supply of an item due to changes in the factors that influence it.
Quantitative data analysis using data analysis toolpak in Excel
Researchers very well know Excel to help research data analysis. So far, excel is mainly used to input data and then present the data in a more informative display. Excel is generally used more for descriptive statistical analysis, creating tables of research results, and creating graphs.
Multiple Linear Regression Analysis for Time Series Data in Excel
The selection of data analysis methods is important in determining the study’s results. Data analysis methods not following statistical theory and scientific principles can potentially cause errors in making research conclusions. The research hypotheses prepared at the beginning of the proposal need to be tested statistically so that the correct findings can be obtained. Therefore, a basic understanding of statistics needs to be understood by those conducting research activities.
The Best Guide for Optimizing Data Analysis in Excel
In addition to understanding the research topic, researchers also need basic data analysis knowledge. Excel is one of the tools often used by researchers to analyze research data. Researchers can use excel for various data analyses. On this occasion, Kanda Data will write the best guide for optimizing data analysis in excel.
How to Solve Multicollinearity in Multiple Linear Regression with OLS Method
Multiple linear regression equations must fulfill the required assumptions to obtain the best linear unbiased estimator. Several assumptions in linear regression using the ordinary least square (OLS) method must be met, one of which is non-multicollinearity.
How to Use Dummy Variables in Linear Regression with Ordinary Least Square Method
Many researchers have chosen linear regression using the ordinary least square (OLS) method because it can obtain the best linear unbiased estimator. To get the best linear unbiased estimator, researchers need to test the assumptions required for linear regression using the OLS method.
Finding the Best Regression Model Based on R Square
The regression model specification is an important step that researchers must consider. The exact specification will get the best regression model and represent real phenomena well.
Correlation Analysis for Variables Measured with a Likert Scale (Ordinal Scale)
Many researchers choose to use correlation analysis to know the relationship between variables. The simpler analysis technique causes correlation analysis to be widely used by researchers.