Correlation and Regression Analysis: Learn Everything With Examples

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Correlation and Regression Analysis With Examples, Correlation Coefficient, Correlation:
Hello Friends,
Correlation and Regression Analysis are essential mathematical concepts to define the relationship between variables.
This video consists of the following points:
✅Introduction: Why Correlation and Regression are needed?
✅What is Correlation?
✅Correlation Analysis
✅Correlation Coefficient
✅Calculation of Correlation Coefficient
✅Correlation Coefficient In Excel
✅What is Regression?
✅Regression In Excel
✅r-Square value
✅r value and r-Squared value
✅Significance F and p-value
✅Coefficients
✅Residuals
✅Difference between Correlation and Regression analysis
✅Correlation and Regression
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0:00 Introduction
0:41 Correlation
1:56 Correlation Analysis
2:05 Correlation Coefficient
2:48 Calculation of Correlation Coefficient
3:06 Correlation Coefficient In Excel
4:28 Regression
5:45 Regression In Excel
6:40 R-Square
6:56 Significance F and P-value
7:41 Coefficients
8:08 Residuals
8:44 Conclusion
8:55 Correlation and Regression
#Correlation #Regression #CorrelationAnalysis #RegressionAnalysis #CorrelationAndRegression #CorrelationAndRegressionAnalysis #CorrelationExample #RegressionExample #leansixsigma #sixsigma #learnandapply #successfulcareerhub

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Residuals are computed as (Observed - Expected) and you need to do more tests in order to make sure that your model is corect and stable (when use OLS). 2 important tests: 1 check if the residuals follow a normal distribution, 2 check for heteroskedasticity. On the other hand you explained well

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Another nice tool of Excel is on the x-y scatter plot. You can add a curve-fit line of a more complex nature. Instead of just linear regression, you can also use exponential, logarithmic, and polynomial. It can display the resulting function and corresponding r-squared fit. Great when the data is correlated by something more than simple linear relationship.

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Congratulations show direction and degree of relation between 0 and 1. Regression shows this and also how one variable changes due to change in another and numerical relation and prediction can be made

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