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2. The manager of a sandwich shop gathers data on what people spend on lunch on a particular day of the week.

The results are $4.20, $4.22, $2.35, $4.32, $5.25, $6.48, $6.78, $8.59, $6.95, $5.52, $6.83, $7.35, $4.36, $9.39, $6.42.

To the degree that this represents the population of all those who eat lunch at sandwich shops, what percentage of customers spend:
1. less than $4.34?
2. between $3.50 and $4.80?
3. less than $2.35?

Imagine that you are the manager of a sandwich shop. Based on your calculations, what do you think is the best pricing point for your shop? What would you do to increase sales at the sandwich shop?

  • statistics -

    Find the mean first = sum of scores/number of scores

    Subtract each of the scores from the mean and square each difference. Find the sum of these squares. Divide that by the number of scores to get variance.

    Standard deviation = square root of variance

    Z = (score-mean)/SD

    Find table in the back of your statistics text labeled something like "areas under normal distribution" to find the proportions/probabilities related to the Z scores.

    I'll let you do the calculations and come to your own conclusions.

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