B Com > Business Mathematics and Statistics > Regression analysis - Correlation & Regression, Business Mathematics & Statistics
Regression analysis - Correlation & Regression, Business Mathematics & Statistics Video Lecture - Business Mathematics and Statistics - B Com
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FAQs on Regression analysis - Correlation & Regression, Business Mathematics & Statistics Video Lecture - Business Mathematics and Statistics - B Com
| 1. What is regression analysis? |  |
Ans. Regression analysis is a statistical technique used to model the relationship between a dependent variable and one or more independent variables. It helps in understanding how the value of the dependent variable changes when the independent variables are varied.
| 2. What is the difference between correlation and regression analysis? | |
Ans. Correlation analysis measures the strength and direction of the linear relationship between two variables, while regression analysis determines the mathematical equation that best represents the relationship between the dependent and independent variables.
| 3. How is regression analysis used in business mathematics and statistics? | |
Ans. Regression analysis is widely used in business mathematics and statistics to make predictions, forecast future outcomes, and understand the impact of independent variables on the dependent variable. It helps businesses in decision-making, marketing strategies, financial analysis, and risk assessment.
| 4. What are the assumptions of regression analysis? | |
Ans. Regression analysis assumes that there is a linear relationship between the dependent and independent variables, the residuals (errors) are normally distributed, the residuals have constant variance (homoscedasticity), and there is no multicollinearity (high correlation) among the independent variables.
| 5. How can regression analysis help in making business decisions? | |
Ans. Regression analysis provides valuable insights for making business decisions by identifying the key factors that influence the dependent variable. It helps in determining the optimal pricing strategy, forecasting sales, evaluating the effectiveness of marketing campaigns, analyzing customer behavior, and optimizing resource allocation. By understanding the relationship between variables, businesses can make informed decisions and improve their overall performance.
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