REGRESSION ANALYSIS IN HR
BY:
NITYA GARG
IBS BUSINESS SCHOOL- GURGAON
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.
TYPES OF REGRESSION ANALYSIS:
 LINEAR REGRESSION ANALYSIS
 LOGISTIC REGRESSION
 POLYNOMIAL REGRESSION
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).
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
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
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
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.
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.
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.
Thank You 

Regression analysis in HR

  • 1.
    REGRESSION ANALYSIS INHR BY: NITYA GARG IBS BUSINESS SCHOOL- GURGAON
  • 2.
    What is RegressionAnalysis? 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 REGRESSIONANALYSIS:  LINEAR REGRESSION ANALYSIS  LOGISTIC REGRESSION  POLYNOMIAL REGRESSION
  • 4.
    LINEAR REGRESSION  LinearRegression 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 regressionis 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 regressionequation 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 HRDEMAND 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 valuableforecasting 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 QUANTITATIVETECHNIQUE  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 regressionis 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.