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How to Calculate Y Predicted and Residual Values in Simple Linear Regression
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.
The Formula for Calculation of the Determination Coefficient (R Square) Simple Linear Regression
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.
How to Calculate Coefficients bo and b1 of Simple Linear Regression Manually in Excel
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.
Why is Descriptive Statistical Analysis Important?
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.
Choosing Simple Random Sampling in Conducting Research
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.
Comparison of Two Sample Dependent (Paired t-test)
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.
How to Compute Spearman Rank Correlation Test
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.
Autocorrelation Test on Time Series Data using Linear Regression
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.