Solving Probability Questions: Big Burger Chain Stores

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Discussion Overview

The discussion revolves around solving probability questions related to the advertising practices of Big Burger chain stores and their impact on sales. Participants analyze the probabilities of sales increases based on whether stores advertised in local newspapers, addressing both theoretical and applied aspects of probability.

Discussion Character

  • Mathematical reasoning
  • Homework-related
  • Technical explanation

Main Points Raised

  • One participant calculates the overall probability of a store having an increase in sales as 0.495, based on the advertising rates and sales increases.
  • Another participant points out a potential error in the notation of conditional probabilities, suggesting that the correct formulation for part (b) should be P(B|A) instead of P(A|B).
  • A subsequent participant proposes a calculation for P(B|A) as 0.848, using the previously defined probabilities and the total probability of increased sales.
  • A later reply confirms the calculation of P(B|A) as correct and provides an alternative method by simulating 1000 stores to illustrate the same result, arriving at approximately 84.8% of stores with increased sales having advertised.

Areas of Agreement / Disagreement

Participants generally agree on the calculations for part (a) and the final result for part (b), though there is a discussion about the correct interpretation of conditional probabilities. The initial confusion regarding the notation indicates some disagreement on the approach to part (b).

Contextual Notes

There is a reliance on specific assumptions regarding the independence of advertising and sales increases, as well as the definitions of events A and B. The calculations depend on these definitions and the overall structure of the problem.

Who May Find This Useful

This discussion may be useful for students or individuals interested in probability theory, particularly in understanding conditional probabilities and their applications in real-world scenarios such as marketing and sales analysis.

mkir
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Hi, I need some help with this question.

Seventy percent of all Big Burger chain stores decided to advertise in their local newspapers. Of those chain stores that advertised in their local newspapers, 60% had an increase in sales. Of those chain stores that did not advertise in their local newspapers, 25% had an increase in sales.
(a) What is the probability that a randomly selected store has an increase in sales.
(b) What is the probability that a randomly selected store with an increase in sales advertised in its local newspaper?

for a)
I did
(.7)(.6) + (.3)(.25) = 0.495

for b)
A = Increased sales
B = Advertised

P(A|B) = 0.495/0.7 = 0.707


Did I do this right?
 
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a.) Looks right.
b.) It looks like you have A & B reversed.
The question asks for the probability one advertised given one had an increase in sales. So that should be P(B|A) as you defined them.
 
So for b), would

P(B|A) = (.7)(.6)/(.495) = 0.848

be correct?
 
mkir said:
So for b), would

P(B|A) = (.7)(.6)/(.495) = 0.848

be correct?

yes it is
 
Another way to do (b) is to imagine that there are 1000 stores. Then 70% of them, or 700, advertise. Of those, 60%, or 420, have an increase in sales. 300 stores do not advertise and 25% of them, 75, also have an increase in sales. So a total of 420+ 75= 495 stores have an increase in sales and 420 advertised: that is, 420/495= .848 (approximately) or 84.8% of the stores that had an increase in sales advertised.
 

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