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Assumptions of Linear Regression

How to Test the Multicollinearity in Multiple Linear Regression

By Kanda Data / Date Mar 18.2022

When choosing multiple linear regression analysis, we include at least two independent variables into the model. To obtain the best linear unbiased estimator, we must test the assumptions. One of the assumptions that need to be tested is the multicollinearity test.

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Simple Linear Regression

How to Find Variance, Standard Error, and T-Value in Simple Linear Regression

By Kanda Data / Date Mar 15.2022

Calculating the value of variance, standard error, and t-value is the last stage in simple linear regression analysis. The variance value can be calculated if the estimate of the variance of u has been calculated. The value of estimate of the variance of u cannot be calculated if it has not calculated the value of the sum of residual squared.

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Simple Linear Regression

How to Calculate the Analysis of Variance (ANOVA) Table In Simple Linear Regression

By Kanda Data / Date Mar 11.2022

Analysis of Variance (ANOVA) is often used in experimental research with different treatments. In simple linear regression, there is also ANOVA. Some often refer to ANOVA as the F test. In simple linear regression analysis, the statistical software output will display an ANOVA table. In addition to understanding how to interpret the ANOVA table, you also need to understand how to calculate it manually.

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Simple Linear Regression

How to Determine Y Predicted, Residual, and Sum of Squares in Simple Linear Regression

By Kanda Data / Date Mar 08.2022

In simple linear regression analysis, the calculation of the predicted Y value, residual value, and sum of squares need to be well understood by researchers. If previously you would usually look at the output of statistical software, on this occasion, I will give a tutorial on how to calculate it manually using Excel.

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Simple Linear Regression

How to Calculate Coefficient of Determination (R Squared) in Simple Linear Regression

By Kanda Data / Date Mar 04.2022

In simple linear regression analysis, the coefficient of determination (R Squared) is one of the outputs that can be used to see the goodness of fit model. Data processing using statistical software, almost all of them, in one of the outputs, show the value of the coefficient of determination. This time, I will write an article on how to calculate the coefficient of determination (r squared) in simple linear regression.

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Simple Linear Regression

How to Calculate bo and b1 Coefficient Manually in Simple Linear Regression

By Kanda Data / Date Mar 01.2022

In conducting data analysis, we not only need to know how to analyze and interpret the results, but we also need to understand how to calculate manually. Calculating manually simple linear regression becomes essential, especially for researchers or students deepening econometrics or statistics. Did you know it turns out that doing simple linear regression calculations can be done easily? Manual linear regression calculations can be completed using a calculator or excel.

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Multiple Linear Regression

How to Compute Multiple Linear Regression and Interpreting the Output using SPSS

By Kanda Data / Date Feb 25.2022

Welcome back with me on the blog “Kanda Data”. On this occasion, I will discuss how to compute multiple linear regression and interpret the output using SPSS. This time, I took an example of a case study on how advertising costs and marketing personnel can influence product sales.

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Simple Linear Regression

Simple Linear Regression Analysis and Interpreting the Output in SPSS

By Kanda Data / Date Feb 22.2022

Researchers often choose linear regression analysis to determine the effect of the independent variable on the dependent variable. Simple linear regression was used to analyze the regression model with only one independent variable. There are many benefits of using simple linear regression analysis. Based on that, Kanda Data on this occasion will share a simple linear regression analysis tutorial and how to interpret the output in SPSS.

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Categories

  • Article Publication
  • Assumptions of Linear Regression
  • Comparison Test
  • Correlation Test
  • Data Analysis in R
  • Econometrics
  • Excel Tutorial for Statistics
  • Multiple Linear Regression
  • Nonparametric Statistics
  • Profit Analysis
  • Regression Tutorial using Excel
  • Research Methodology
  • Simple Linear Regression
  • Statistics

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