1. Asian School of Business PG Programme in Management (2005-06) Course: Quantitative Methods in Management I Instructor: Chandan Mukherjee Session 6b: Measuring Uncertainty – Binomial Distribution Model

2. Statement of the Problem: A Medical Representative Days left to meet the target: 27days Days required to meet the target: 25 days Decision Required: To participate in the All India Meet of the Medical Representatives Days required to participate: One day Uncertainty: Days may be lost due to Flood or Bandh A Decision Problem Under Uncertainty

3. From Past Data Chance of Flood Due to Rain in a Day: 1 in 30 14 Days of Bandh in Last Two Years In other words (taking Relative Frequencies as Estimates of Probabilities): P (Flood) = 1/30 = 0.03333 P (Bandh) = 14/730 = 0.01918

4. Read the note: binomial.pdf

5. Application of Binomial Distribution: Example 1 - Anticipating Events Market Research: 12% of the households will buy new vacuum cleaners during Onam Salesperson visits 10 households. What is the likely number of sales?

6. Application of Binomial Distribution: Example 2 – Checking Assumption Market Research: 12% of the households will buy new vacuum cleaners during Onam Salesperson visits 10 households & sales 3. Were the market researchers right?

7. Application of Binomial Distribution: Example 3 – Estimating Proportion Salesperson visits 100 households & sales 30 vacuum cleaners. What is the proportion of households in the area will buy vacuum cleaner? Principle of Maximum Likelihood L = n C k p k (1-p) n-k ln L = ln{ n C k } + k.ln(p) + (n-k) ln(1-p) sample proportion