Fytokem Products Inc., a Canadian pharmaceutical ingredients company, struggled with domestic sales but successfully launched Tyrostat internationally, resulting in a 22% average sales increase. Advanced multiple regression analysis showed company size significantly predicts purchase sizes, while other variables were deemed non-significant. The impact of employees on sales was highlighted, with a model explaining 80% of sales variability using transformed employee variables.

1. Fytokem Products Inc.
Advanced Multiple Regression Analysis
Presentation By:
Kamalika Some
Kruthik Kulkarni
Ritesh Prasad
Pankaj Kumar

2. Case Study
• Canada based company producing pharmaceutical ingredients.
• Facing poor sales with domestic customers due to lack of demand.
• Introduction of Tyrostat in the international market – Success.
• Increase in sales by an average of 22%

3. 1) Predicting the Size of Purchase

4. 1) Predicting the Size of Purchase : Scatter
Plots

5. 1) Predicting the Size of Purchase
1) Adjusted R-squared is 70%.
2) Company Size is a significant variable.
3) P-value of Cost of delivery and Similar
products >0.05, which indicates non-
significance of these variables in the
model.

6. Predicting Size of Purchase with
Company Size
1) Adjusted R-square is 66%.
2) P-value for company size is <0.05
which indicates significance.
3) Size of Purchase = 23.904 + 1.782
* Company Size

7. Residual Plot:
The most relevant variable alone
Company Size

8. 2) Analysing the response variable - Sales

9. 2) Analysing the response variable – Sales:
Scatter Plots

10. 2) Analysing the response variable - Sales
1) Adjusted R-squared is very low.
2) P-value for explanatory variables are
>0.05.
3) Exploratory variables do not explain
the response variable.

11. Effect of the variable - Hours worked per Week

12. Effect of the variable – Number of Customers

13. 3) Measuring the impact of the number of
Employees

14. Sales vs Number of Employees

15. Tukey’s 4 Quadrant Approach

16. Sales^2.5 vs (log(Number of
Employees)+Number of Employees)

17. 3) Measuring the impact of the number of
Employees
1) Adjusted R-squared is 80%.
2) Transformed exploratory variable,
log(Number of employees)+Number of
employees explains 80% of the variability
of response variable.
3) 2.5*Sales=-352961.7 + 86210.2 *
log(Number of employees) -477 *
Number of employees

18. Residual vs Fitted

19. Thank you