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Tag: statistics

Normality Test in Regression: Should We Test the Raw Data or the Residuals?

By Kanda Data / Date Jun 09.2025 / Category Assumptions of Linear Regression

When we choose to analyze data using linear regression with the OLS method, there are several assumptions that must be met. These assumptions are essential to ensure that the estimation results are consistent and unbiased. This is what we refer to as the Best Linear Unbiased Estimator (BLUE).

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How to Find the T-Table Value for Regression Using Excel

By Kanda Data / Date Jun 07.2025 / Category Multiple Linear Regression

In linear regression analysis, we often want to determine whether the independent variable truly influences the dependent variable. Therefore, linear regression analysis is one type of associative test that aims to determine how the independent variable affects the dependent variable.

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How to Automatically Display Residual Values in Regression Analysis Using Excel

By Kanda Data / Date Apr 25.2025 / Category Regression Tutorial using Excel

Residual values play an important role in linear regression analysis. These residuals are used for OLS assumption tests, such as normality tests and heteroskedasticity tests. For instance, one of the key assumptions in linear regression analysis is that the residuals are normally distributed.

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How to Calculate the Variance Inflation Factor (VIF) in a Multicollinearity Test for Regression

By Kanda Data / Date Jan 29.2025 / Category Assumptions of Linear Regression

In linear regression analysis, to obtain the best linear unbiased estimator, you need to perform a series of assumption tests. One of the assumption tests required in linear regression is the multicollinearity test.

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How to Determine Alpha Values of 5% and 1% in Hypothesis Testing

By Kanda Data / Date Jan 27.2025 / Category Statistics

If you are conducting research, you certainly have a hypothesis for your study. Hypothesis testing is crucial in research, especially if you’re performing inferential statistical analysis. In statistical hypothesis testing, you are often faced with the choice of using an alpha value of 5% or 1% for your study.

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The Impact of Residual Variance on P-Value in Regression Analysis

By Kanda Data / Date Jan 24.2025 / Category Statistics

When conducting linear regression analysis on your research data, you naturally hope that some independent variables significantly affect the dependent variable. Achieving this indicates that you’ve successfully selected independent variables that are presumed to influence the dependent variable.

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Differences in the Formulas for Calculating Standard Deviation for Sample Data and Population Data

By Kanda Data / Date Jan 16.2025 / Category Statistics

Standard deviation is a crucial measure in explaining how data is distributed relative to its mean. Generally, when conducting research and performing descriptive statistical analysis, the value of the standard deviation will often appear.

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How to Find the Standard Deviation of Sample Data in Excel

By Kanda Data / Date Jan 05.2025 / Category Statistics

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.

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