How Do Sales Representatives' Earnings Vary in a Canadian Clothing Chain?

In summary, the clothing store has 25 sales representatives in each of their offices in Toronto, Montreal, Vancouver, and Calgary. The weekly sales for these representatives follow a normal distribution with a mean of $12,000 and a standard deviation of $2,000. For a given representative, the probability of their weekly sales falling within 0.9973 of the mean is between $8,000 and $16,000. For the average weekly sales per representative of the Montreal office, the probability of it falling within that range is also between $8,000 and $16,000. Similarly, for the average weekly sales per representative of the entire company, the probability of it falling within that range is also between $8,000
  • #1
adeel
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A clothing store has offices in Toronto, Montreal, Vancouver and Calgary, and each office has 25 sales representatives. The weekly sales for the sales representatives are normally distributed with a mean of $12,000 and a standard deviation of $ 2,000. Within what range about the mean is the probability 0.9973 that:

1. A given representatives weekly sales will fall
2. The average weekly sales per representative of the Montreal office will fall
3. The average weekly sales per representative of the company will fall.

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I have the answers, but I have no idea from where to even begin. If someone can help me understand and explain this id be very appreciative.
 
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  • #2
I don't quite understand the wording of (1) or the rest of the question about the range of the mean enough to give a complete answer.

If a representative has sales of x for week one, then the probability of him having less than x sales for the next week is the integral of the normal distribution from -infinity to x.

If you give the answer to (1) maybe one could work backward and understand the wording better.
 
  • #3


Sure, I'd be happy to help you understand this problem and its solutions. Let's break it down step by step.

1. A given representative's weekly sales will fall:
The probability that a given representative's weekly sales will fall within a certain range is 0.9973. This means that there is a 99.73% chance that the representative's weekly sales will fall within this range. To determine this range, we need to use the mean and standard deviation provided.

The mean is $12,000 and the standard deviation is $2,000. Since we are looking for a range, we need to find the upper and lower limits. To do this, we can use the following formula:

Upper limit = mean + (3 x standard deviation)
Lower limit = mean - (3 x standard deviation)

Plugging in the numbers, we get:
Upper limit = $12,000 + (3 x $2,000) = $18,000
Lower limit = $12,000 - (3 x $2,000) = $6,000

Therefore, the range around the mean of $12,000 where the probability is 0.9973 is $6,000 to $18,000.

2. The average weekly sales per representative of the Montreal office will fall:
To find the range for the average weekly sales per representative of the Montreal office, we need to use the same formula as above, but with a different mean. The mean for the Montreal office is not given, but we can calculate it by dividing the total weekly sales for the office by the number of representatives (25).

Total weekly sales for the Montreal office = $12,000 x 25 = $300,000
Mean for the Montreal office = $300,000 / 25 = $12,000

Using the same formula as before, we get:
Upper limit = $12,000 + (3 x $2,000) = $18,000
Lower limit = $12,000 - (3 x $2,000) = $6,000

Therefore, the range around the mean of $12,000 for the average weekly sales per representative of the Montreal office is $6,000 to $18,000.

3. The average weekly sales per representative of the company will fall:
To find the range for the average weekly sales per representative of the company, we need to use the same formula as above
 

FAQ: How Do Sales Representatives' Earnings Vary in a Canadian Clothing Chain?

What is probability?

Probability is a measure of the likelihood of an event occurring. It is expressed as a number between 0 and 1, with 0 representing impossibility and 1 representing certainty.

How is probability calculated?

The probability of an event is calculated by dividing the number of favorable outcomes by the total number of possible outcomes. This is known as the classical definition of probability.

What is the difference between theoretical probability and experimental probability?

Theoretical probability is based on mathematical calculations and assumes that all outcomes are equally likely. Experimental probability, on the other hand, is based on actual data collected from experiments or observations.

What are independent and dependent events?

Independent events are events where the outcome of one event does not affect the outcome of another event. Dependent events are events where the outcome of one event does affect the outcome of another event.

How can probability be used in real-life situations?

Probability is used in many real-life situations, such as predicting stock market trends, weather forecasting, and risk analysis in insurance. It can also be used to make informed decisions in situations where there is uncertainty, such as in gambling or sports betting.

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