Tag: econometrics
Alternative to the t-test When Data Are Not Normally Distributed
The t-test is one of the most popular methods for comparing the means of two sample groups. In practice, the t-test can be used for two paired sample groups or two independent sample groups. We can perform this difference test using a paired-samples t-test or an independent-samples t-test, depending on the characteristics of the data being analyzed.
When Should Natural Logarithmic Data Transformation Be Applied?
When researchers, practitioners, or students are conducting data analysis on research results, they are often faced with data that do not meet the assumptions required by the chosen analytical method. After testing, it may turn out that the data distribution is highly skewed, the variance is not constant, or non-linear relationships between variables are observed. These conditions represent common challenges in statistical analysis, especially when using parametric methods such as linear regression analysis.
Should Data Normality Testing Always Be Performed in Statistical Analysis?
In statistical analysis of research results, normality testing is often treated as an analytical step that is almost always conducted before proceeding to further analysis. Many researchers, students, and data practitioners believe that without a normality test, statistical analysis results become less scientific.
Differences in Nominal, Ordinal, Interval, and Ratio Data Measurement Scales for Research
In research activities, data serve as the main foundation for analysis and drawing conclusions. However, not all data have the same characteristics. One of the common challenges faced by novice researchers is understanding and applying data measurement scales. In fact, an understanding of data scales greatly determines the type of statistical analysis that can be used as well as the validity of research results.
Reasons Why the R-Squared Value in Time Series Data Is Higher Than in Cross-Section Data
If you’re doing regression analysis, R-squared is one of the most important metrics you need to understand. R-squared shows how much of the variation in the dependent variable can be explained by the variation in the independent variables in a regression model.
How to Perform Descriptive Statistics in Excel in Under 1 Minute
Descriptive statistical analysis is essential to carry out for your research data. From the output of descriptive statistics, you can obtain information such as the minimum, maximum, mean, standard deviation, standard error, and more. These values are important to interpret for each variable observed in your research.
How to Tabulate Data Using Pivot Table for Your Research Results
For those of you currently conducting research, the stages of data entry and data tabulation are important parts of the process. Excel, which we already use daily for data processing, can also help us perform data tabulation quickly.
Dummy Variables: A Solution for Categorical Variables in OLS Linear Regression
If you’re analyzing data using OLS linear regression, there are certain assumptions you need to meet. The purpose of these assumption tests is to ensure that the estimation results are consistent and unbiased.