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MANAGERIAL ECONOMICS

PRESENTATION REPORT SUBMITTED BY:-

Avinash Nair P-59

Prakash Panji P-23

Swati Khandelwal P-36

Rita Malhan P-49

Prahlad Walve P-56

Under the guidance of:-

Prof. Neelema Shastri

Dr. V.N. BEDEKAR COLLEGE OF MANAGEMENT STUDIES

Chendani Bunder Road, Thane 400601

SIGN:-

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ACKNOWLEDGEMENT

We are elated to present this topic and would like to take this

opportunity to express our sincere thanks to all, who by their direct or

indirect contribution have helped us make it possible.

We thank Prof. Neelima Shastri our project guide for her assistance.

Without her constant support and motivation this project would not have

been possible. We also thank her for giving us such a presentation topic

that is close to our heart as well as that would lead to our personal

development.

OBJECTIVES

The Objective of our presentation was to understand the

fundamentals of multiple regression analysis and its applications. The

report has not only helped us to understand comprehend regression

analysis but also theoretically but also understand its practical

applications.We also learnt the techniques wherein multipleregression analysis is used as a strategic business tool for decision

making.

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Why Learn Multiple Regression Analysis

Explain model building using multiple regression analysis:

To understand the model building process which is the

elementary

Apply multiple regression analysis to business decision-making

situations

Analyze and interpret the computer output for a multiple

regression model

Test the significance of the independent variables in a multiple

regression model

Recognize potential problems in multiple regression analysis

and take steps to correct the problems

Incorporate qualitative variables into the regression model by

using dummy variables

Use variable transformations to model nonlinear relationships

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An Introduction to Multiple Regression

Definition

Regression analysis applied to equation with two or more

independent variables

Multiple regression is a technique that allows additional factors

to enter the analysis separately so that the effect of each can be

estimated. It is valuable for quantifying the impact of various

simultaneous influences upon a single dependent variable. Further,

because of omitted variables bias with simple regression, multiple

regression is often essential even when the investigator is only

interested in the effects of one of the independent variables.

y Example

Consider the GDP Of any economy it is dependent on various

factors like growth rate, inflation rate, unemployment rate

and so on. A Simple regression analysis would fail to predict

the impact of other variables, this however is considered in a

multiple regression analysis. The future values can be

forecasted considering all the parameters that would tend toaffect the dependent variable.

Steps for Multiple Equation Regression Model

Select the dependent variableSelection of the dependent variable relies on the need or the

main objective of the research.

Identify the potential independent variablesThis step involves recognizing all possible parameters that

could tend to affect the the dependent variables. This stepIs the foundation of the model all further decisions are based

on this step.

Gather Sample DataThe data relevant to our research must be collected and the

observations must be tabulated accordingly.

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Steps of Multiple Regression Analysis

y

Construct a regression modely Estimate the regression and interpret

y the result

y Conduct diagnostic analysis of the results

y Change the original regression model if necessary

y Make predictions

Business Statistics: A Decision -

Making Approach, 7e 2008

Prentice-Hall, Inc.

Chap 15-8

Multiple Regression Model

Two variable model

y

x1

x2

22110xbxbby !

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St forM lti l Equation R ression Model

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