Regression Analysis
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Monday, 10 June 2019
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Published in
Big Data, Business, Business Intelligence, Data Analytics, Data Science
Regression analysis helps us understand effect level of the independent variable on the response variable. It also gives more insight on the relationship between the two variables. We can look at an example of a survey where the age of individuals and their salary was captured. To understand if the education of an individual affects their wage, we could run a regression analysis of wage against education. In this analysis, wage is our response variable while education is the independent variable. We then state our hypotheses to be;
H0: There is no significant difference in the wage and education of workers.
H1: There is significant difference in the wage and education of workers.
This regression will be tested at 95% confidence level, that is, when alpha level is 0.05 (∝=0.05). From the results the p-value is < 2e – 16 which is less that the ∝ = 0.05
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