Author: Kanda Data
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.
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.
The Difference Between Residual and Error in Statistics
For those of you who are learning statistics, you’ve probably come across theories explaining the concepts of residual and error. At first glance, they seem almost identical, and many people even think they mean the same thing. However, in statistics, residual and error actually have different meanings.
Use Stratified Random Sampling When the Population Is Not Entirely Homogeneous
Sampling techniques are very important, especially when we’re observing a specific population. By taking samples, we can save on costs, time, and effort—yet still obtain results that represent the population being studied.
Snowball Sampling Technique: A Solution When the Population Size Is Unknown
In conducting research, we generally take samples from a population under observation. Of course, it’s much easier if we already have data on the population size, so we can take a representative sample that reflects the population as a whole.
How to Create Dummy Variables in Multiple Linear Regression Analysis
For those of you conducting multiple linear regression analysis, have you ever used dummy variables? These variables are very useful when we want to include categorical variables in a multiple linear regression equation.