Tag: statistics
Interpretation of Negative Estimated Coefficients: A Case Study of the Effect of Price on Demand
Introduction
When we conduct regression analysis, it does not always produce positive estimated coefficients. In regression analysis, we often find estimated coefficients that are negative. Not infrequently, this makes us wonder: is this safe for my research?
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.
Regression Analysis for Binary Categorical Dependent Variables
When we talk about regression analysis, we often think about parametric variables measured on at least an interval or ratio scale. But what if we want to analyze the effect of independent variables on a dependent variable that happens to be categorical in nature?
How to Sort Values from Highest to Lowest in Excel
When conducting tabulation and data analysis, we sometimes need to sort values for a specific purpose. It turns out that sorting values from the highest to the lowest, or vice versa, can easily be done using Excel. We are, of course, already familiar with Excel as a tool that we use in our daily office work, one of which is its advantage in data processing.
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.