Regression analysis in HR
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Regression analysis is a predictive modeling technique used to investigate relationships between variables. There are several types including linear, logistic, and polynomial regression. Linear regression establishes relationships between dependent and independent variables using a best fit line. Logistic regression is used when dependent variables are binary. Polynomial regression allows independent variables to have powers higher than one. Regression analysis can be useful for human resources forecasting, determining staffing needs based on factors like projected sales or call volumes. It indicates significant relationships between dependent targets and independent predictors.
Regression analysis in HR
- 1. REGRESSION ANALYSIS IN HR BY: NITYA GARG IBS BUSINESS SCHOOL- GURGAON
- 2. What is Regression Analysis? Regression analysis is a form of predictive modeling technique which investigates the relationship between a dependent (target) and independent variable (s) (predictor). This technique is used for forecasting, time series modeling and finding the causal effect relationship between the variables. For example, relationship between rash driving and number of road accidents by a driver is best studied through regression.
- 3. TYPES OF REGRESSION ANALYSIS: LINEAR REGRESSION ANALYSIS LOGISTIC REGRESSION POLYNOMIAL REGRESSION
- 4. LINEAR REGRESSION Linear Regression establishes a relationship between dependent variable (Y) and one or more independent variables (X) using a best fit straight line (also known as regression line).
- 5. LOGISTIC REGRESSION Logistic regression is used to find the probability of event=Success and event=Failure. We should use logistic regression when the dependent variable is binary (0/ 1, True/ False, Yes/ No) in nature. Here the value of Y ranges from 0 to 1 and it can represent by following equation: log(p) = ln(p/(1-p)) = b0+b1X1+b2X2+b3X3+ b k X k
- 6. POLYNOMIAL REGRESSION A regression equation is a polynomial regression equation if the power of independent variable is more than 1. The equation below represents a polynomial equation: y=a +b*x^2
- 7. REGRESSION IN HR DEMAND FORECASTING How regression analysis is useful in human resources demand forecasting Regression model would incorporate a rate of change based on historical productivity improvement trends. These models also can be used to evaluate the required mix of the employee categories
- 8. CONT. This valuable forecasting enables us to plan and execute recruitment, selection, training, and development program in planed, proactive fashion to ensure the trained marketing staff are on hand exactly when required the organization.
- 9. APPLICATION OF QUANTITATIVE TECHNIQUE In companies, linear regression technique is used to predict the number of employees to be recruited each year according to the projected sales. In call centers, linear regression technique is used to predict the number of employees required as per the no. of calls that need to be responded so that they do not lose their customers because of being under staffed.
- 10. LEARNING How regression is used in the field of HR. It indicates the significant relationships between dependent variable and independent variable. Scatter graphs are used to determine whether there is a relationship between the two variales. In scatter graphs ,ideally all the points should on the line and the deviation of the points from the line are the errors. The process of performing regression mathematically.
- 11. Thank You