Tag: multiple linear regression
Hypothesis Testing: Unveiling Insights in Multiple Linear Regression Analysis
In inferential statistics, we need to formulate research hypotheses. These research hypotheses are formulated according to the research objectives. Furthermore, statistical hypotheses need to be established in the analysis method, consisting of null and alternative hypotheses.
How to Calculate the Regression Coefficient of 4 Independent Variables in Multiple Linear Regression
A multiple linear regression includes at least two independent variables and one dependent variable. In some previous articles, I’ve written about manually calculating multiple linear regression with two and three independent variables.
Calculate Coefficients bo, b1, b2, and b3 Manually (3 Independent Variable) in Multiple Linear Regression
Multiple linear regression is a regression analysis consisting of at least two independent variables and one dependent variable. In several articles I have written previously, I have discussed calculating multiple linear regression with two independent variables manually.
Determining Variance, Standard Error, and T-Statistics in Multiple Linear Regression using Excel
The T-statistics in multiple linear regression analysis can be used for statistical hypothesis testing in research. Comparing T-statistics with the T table or p-value can be used to accept statistical hypotheses. T-statistics value can decide whether to accept or reject the null hypothesis based.
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.
Create Residual and Y Predicted in Excel
Residual and predicted Y have an important role in linear regression analysis using the Ordinary Least Square (OLS) method. Several OLS linear regression method assumptions were conducted to test the residuals, including normally distributed residuals and constant residual variance.
Multiple Linear Regression Analysis and Interpreting the Output in Excel
We can use multiple linear regression analysis to estimate the effect of the independent variable on the dependent variable. Multiple linear regression using at least two independent variables.
How to Calculate Variance, Standard Error, and T-Value in Multiple Linear Regression
Finding variance, standard error, and t-value was an important stage to test the research hypothesis. The formula used in multiple linear regression is different from simple linear regression. On this occasion, I will discuss calculating the multiple linear regression with two independent variables.