Tag: Statistical Analysis
How to Find the Standard Deviation of Sample Data in Excel
One of the metrics in statistics is the standard deviation. When conducting research, the standard deviation is crucial for describing the data you have obtained. It illustrates the dispersion of the data relative to the mean.
Differences in Assumptions of Normality, Heteroscedasticity, and Multicollinearity in Linear Regression Analysis
If you analyze research data using linear regression, it is crucial to understand the required assumptions. Understanding these assumption tests is essential to ensure consistent and unbiased analysis results.
Benefits of Using Cross Tabulation in Descriptive Statistical Analysis
When performing descriptive statistical analysis, the primary goal is to provide a general overview of the data being studied. One highly useful tool that supports descriptive analysis is cross tabulation (crosstabs).
Assumptions of Multiple Linear Regression on Cross-Section Data
Multiple linear regression is a statistical technique used to predict the value of a dependent variable based on several independent variables. This regression provides a way to understand and measure the influence of independent variables on the dependent variable.
Assumptions of Multiple Linear Regression on Time Series Data
Multiple linear regression is a statistical analysis technique used to model the relationship between one dependent variable and two or more independent variables. The multiple linear regression model is used to predict the value of the dependent variable based on the estimated values of the independent variables.
What to Do If the Regression Coefficient Is Negative?
Linear regression is one of the most commonly used statistical analysis techniques to understand the impact of independent variables on a dependent variable. In regression analysis, the estimated coefficients indicate the extent to which each independent variable affects the dependent variable.
Why Should Data Transformation Be Done Only Once?
Data transformation is an essential step in inferential statistical analysis. It can be a solution to ensure that research data meets certain required statistical model assumptions, such as normality, linearity, and homoscedasticity.
Analyzing Rice Production Changes with a Paired t-Test Before and After Training Using Excel
Evaluating the effectiveness of extension programs is crucial to ensure that the interventions implemented provide positive impacts for farmers. One way to measure this effectiveness is by comparing production before and after the program using a paired t-test.