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Author: Kanda Data

Simple Linear Regression

The Formula for Calculation of the Determination Coefficient (R Square) Simple Linear Regression

By Kanda Data / Date Feb 15.2022

The coefficient of determination in regression analysis has an important function. Therefore, it is not surprising that various research papers using regression analysis will generally always bring up the value of the coefficient of determination. Based on this, Kanda data will write this topic to be discussed together. This article continues the previous week’s theme, which discussed manually calculating the coefficients bo and b1 in simple linear regression.

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Simple Linear Regression

How to Calculate Coefficients bo and b1 of Simple Linear Regression Manually in Excel

By Kanda Data / Date Feb 11.2022

Linear regression analysis is generally the choice of researchers to test the effect of one variable on other variables. Various scientific fields, both exact and social sciences, have used this analysis. Maybe you are very familiar with the stages of analysis and how to interpret using this simple linear regression analysis. However, do you understand the chronology of getting the values from the analysis results? It is also important to know and understand well. Based on this background, Kanda Data will discuss manual calculations for simple linear regression analysis on this occasion.

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Statistics

Why is Descriptive Statistical Analysis Important?

By Kanda Data / Date Feb 08.2022

When you are completing your final project as a student, you will usually find descriptive statistical analysis results in one of the chapters. It can be seen in a separate sub-chapter or part of one of the chapters written in the thesis. For example, sub-chapters have used descriptive statistical analysis in economics and agribusiness research. Therefore, I will choose this topic to discuss.

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Research Methodology

Choosing Simple Random Sampling in Conducting Research

By Kanda Data / Date Feb 04.2022

Simple random sampling has often been used by researchers when determining the sample. In this case, the researchers chose a random sample. Researchers who choose this technique must meet the required assumptions. Incidentally, on this occasion, I will discuss the topic of simple random sample selection techniques.

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Comparison Test

Comparison of Two Sample Dependent (Paired t-test)

By Kanda Data / Date Jan 28.2022

The comparison of two paired samples becomes interesting to discuss this time. This two-sample comparison test is often analyzed using a paired t-test. Many researchers or students who are conducting research choose to use this test.

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Correlation Test

How to Compute Spearman Rank Correlation Test

By Kanda Data / Date Jan 21.2022

A correlation test is still often an option to solve problems in research. The correlation test includes the Pearson correlation test, Spearman rank correlation test, and chi-square test. Determining the type of correlation test to use depends on the measurement data scale. Well, on this occasion, I will discuss using the Spearman rank correlation test.

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Assumptions of Linear Regression

Autocorrelation Test on Time Series Data using Linear Regression

By Kanda Data / Date Jan 14.2022

The autocorrelation test is one of the assumptions of linear regression with the OLS method. On this occasion, I will discuss the autocorrelation test on time series data. Before discussing the autocorrelation test, you need to know first that the autocorrelation test was conducted on time series, not cross-sectional data.

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Assumptions of Linear Regression

Regression Assumption Test: How and Why to Do?

By Kanda Data / Date Jan 07.2022

Incidentally, the topic that I will discuss this time is the linear regression assumption test using the ordinary least square method. “Why do we have to use the linear regression assumption test? Can I directly do a regression analysis?” To answer this question, you need to go back a little bit by turning page after page from a book on econometric theory or socio-economic statistics, okay? One of the main points that you need to pay attention to is that you are doing an estimate when you analyze research data and then choose regression as an analysis tool.

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