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Home/Archive for: February 2022

Month: February 2022

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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Simple Linear Regression

How to Calculate Y Predicted and Residual Values in Simple Linear Regression

By Kanda Data / Date Feb 18.2022

The residual value in linear regression analysis needs to be calculated first before calculating the variance. In addition, the linear regression of the ordinary least square method must pass the assumption test that the residuals must be normally distributed. However, before calculating the residual value, you must first calculate the predicted Y value. Therefore, we will discuss how to calculate the predicted Y value and residual value on this occasion.

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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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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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