Social Research Methods Project | Multivariate Regression

1. MULTIVARIATE
REGRESSION ANALYSIS
Social Research Methods
What determines SALES of a Product?
Group 6
Roll No. Name
UM15010 Apoorv Shrivastava
UM15013 Asish Parekh
UM15017 Debasis Dash
UM15023 Jaydeep Sahoo
UM15036 Priya Ranjan Mohanty
UM15054 Shree Kumar Sahu
UM15055 Swagat Kumar Das
UM15062 Vivek Tripathy

2. MULTIVARIATE REGRESSION
General 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.

3. 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 Expense
2. Research and Development(RnD)
3. Investments
4. Plant and Machinary

4. Industry: Pharmaceutical
Pharmaceutical 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

5. A priori reasoning: The Sales of a company basically depends upon
1. Quality of products
2. Pricing
3. Necessity of that product(Demand)
4. Awareness and Persuasion generated
5. Brand Value
6. 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)

6. 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

7. Multiplicative model
Dependent 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

8. 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)

9. 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

10. Dependent variable: –
Sales Revenue(Y)
Multiplicative MODEL Summary
Independent variable: –
Marketing Expense (X2)
Research and Development (X3)
Investment (X4)
Plant and Machinery (X5)

11. Thank
you