MULTIVARIATE REGRESSION ANALYSIS

Social Research Methods

What determines SALES of a Product?

Group 6Roll No. NameUM15010 Apoorv ShrivastavaUM15013 Asish ParekhUM15017 Debasis DashUM15023 Jaydeep SahooUM15036 Priya Ranjan MohantyUM15054 Shree Kumar SahuUM15055 Swagat Kumar DasUM15062 Vivek Tripathy

MULTIVARIATE REGRESSIONGeneral Purpose• The general purpose of multiple regression is

to learn more about the relationship between several independent or predictor variables and a dependent or criterion variable.

Example:A real estate agent might record for each listing the size of the house (in square feet), the number of bedrooms, the average income in the respective neighborhood according to census data, and a subjective rating of appeal of the house.

Objective:• We are here to analyze how the sales of a Product/Company is

determined by internal factors of the company.• Dependent Variable: Here dependent variable is Sales revenue. We

have taken the sales revenue for 25 companies.• Independent Variable: Chosen independent variables are:

1. Marketing Expense2. Research and Development(RnD)3. Investments4. Plant and Machinary

Industry: PharmaceuticalPharmaceutical companies are a different set of industries. The sales in this

industry may depend upon huge number of factors. Here we have analyzed some of the possible factor which may be the major influencer of sales.

By increasing marketing expense, a

company can persuade customers to buy their product and hence can boost

their sales.

R&D is the crucial factor in sales of a

pharmaceutical companies as by

investing in R&D more impactful solutions can

by drawn.

Investment if the factor which determines the Scale of operation of a

project. Hence the Sales will be very much

proportional to Investments.

A company which invests more in P&M, is expected to have more sophisticated

technology. Which will lead In better product and hence more sales.

Marketing R&D Investment Plant n Machinery

A priori reasoning: The Sales of a company basically depends upon1. Quality of products2. Pricing3. Necessity of that product(Demand)4. Awareness and Persuasion generated5. Brand Value6. Ability to produce more(Capacity)7. Innovation in products

Quantifying A priori: In order to statically analyse the determinants of sales, we selected following parameters…1. Marketing Expense(pricing, awareness and persuation)2. R & D(Innovation, Quality)3. Investment( Innovation, Pricing, Brand Value)4. Plant and Machinery(Ability to produce more)

Null hypothesis (H0): There is no relation between sales of a pharmaceutical company with any one of marketing expense, R&D expense, investment expense and plant & machine expense

Alternative hypothesis (H1): Sales of a pharmaceutical company is related with marketing expense, R&D expense, investment expense and plant & machine expense

Multiplicative modelDependent Constant/Intercept Slope Log X2

(Ln marketing exp.)Slope Log X3

(Ln r&d)Slope Log X4

(Ln investment)Slope Log X5

(Ln plant )Adjusted R2

Log Y 2.718(0.000) 0.318(0.013) 0.108(0.368) -0.001(0.994) 0.533(0.000) o.898

Log Y 4.937(0.000) 0.421(0.026) 0.294(0.100) 0.036(0.751) - 0.762

Log Y 2.717(0.000) 0.317(0.010) 0.107(0.336) - 0.533(0.000) 0.903

Log Y 2.546(0.000) 0.390(0.000) - 0.560(0.000) 0.019(0.784) 0.899

Log Y 2.746(0.000) - 0.577(0.000) 0.026(0.755) 0.322(0.004) 0.867

Dependent variable: – Sales Revenue(Log Y)

Multiplicative MODEL Summary

Independent variable: – Marketing Expense (Log X2)

Research and Development (Log X3)Investment (Log X4)

Plant and Machinery (Log X5)

Additive ModelDependent Intercept Slope X2

(Marketing)Slope X3

(RnD)Slope X4

(Investment)Slope X5(Plant &

Machinary)

Adjusted R2

Y 3790.499(0.278)

0.390(0.937)

9.164(0.021)

-0.055(0.479)

0.840(0.094)

0.832

Y 6259.117(0.067)

-0.666(0.8960

11.257(0.005)

-0.049(0.549)

_______

0.815

Y 3710(0.282)

1.544(0.737)

7.863(0.021)

_______

0.823(0.095)

0.836

Y 2093.940(0.580)

11.525(0.000) _______

0.039(0.606)

1.228(0.024)

0.790

Y 3853.858(0.246)

_______

9.433(0.000)

-0.057(0.426)

0.835(0.085)

0.840

Dependent variable: – Sales Revenue(Y)

Multiplicative MODEL Summary

Independent variable: – Marketing Expense (X2)

Research and Development (X3)Investment (X4)

Plant and Machinery (X5)

Thankyou