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January 18, 2021

Regression Analysis

Regression Analysis

by Stanley Ambasu / Monday, 10 June 2019 / Published in Big Data, Business, Business Intelligence, Data Analytics, Data Science
sirmirt data analytics

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

To help you interpret the tabulated results deeper and make empirical conclusion, Sirmirt is the best place for you. Contact us

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About Stanley Ambasu

Stanley is an enthusiastic data analyst. He possses a background of statistics and programming. He has skills in advanced spss, advanced Microsoft Excel, Stata software and R Programming language. He is vastly equipped with advanced scripting skills of ODK,KOBO, STG and Survey CTO. He posses reporting skills and presentations of data visualization using tableau and Watson analytics Softwares. He has experienced working with big data and developing business insights to various organizations.

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