Tag: statistics
How to Choose a 5% or 10% Margin of Error in Slovin’s Formula | Calculating the Minimum Sample Size
In calculating the minimum sample size using Slovin’s formula, researchers can choose a 5% or 10% margin of error. What’s the difference, and how do you choose the right one? In survey research, when observing a population, we are often faced with the challenge of a large population size that needs to be observed.
How to Create a Likert Scale Score Category (Ordinal Scale)
Creating Likert scale score categories is essential to answer one of the research objectives, particularly in descriptive statistical analysis. We can categorize non-parametric variables that use the Likert scale into high, medium, and low categories. This information will significantly enrich the research findings.
Differences Between the Null Hypothesis and the Alternative Hypothesis in Statistical Analysis
Statistical hypotheses, consisting of the null hypothesis and the alternative hypothesis, play a crucial role in the process of testing and analyzing statistical data. Understanding the concept of a hypothesis is a critical first step in ensuring that research results are valid and scientifically accountable.
Regression Analysis on Non-Parametric Dependent Variables: Is It Possible?
In multiple linear regression analysis, the measurement scale of the dependent variable is typically parametric. However, can multiple linear regression analysis be applied to a dependent variable measured on a nominal (non-parametric) scale?
Understanding the Differences in Using R Squared and Adjusted R Squared in Research
When you choose to use linear regression analysis, it’s essential to master and understand the interpretation of the coefficient of determination. The coefficient of determination is one of the key indicators in linear regression analysis that can be used as a metric to determine the goodness of fit of a regression model.
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).
How to Correctly Interpret a Negative Estimation Coefficient
The goal of linear regression analysis is to understand the influence of independent variables on dependent variables. The result of linear regression analysis is the regression coefficient, which indicates the size and magnitude of the influence of independent variables on dependent variables.
Correlation Analysis on Non-Parametric Variables Measured Using Likert Scale
For researchers, correlation analysis is a familiar tool used to measure the strength and direction of the relationship between two variables. However, correlation analysis on non-parametric variables measured using the Likert scale has fundamental differences compared to correlation analysis on parametric variables.