3. Refer to the table below, the average number of chocolate chips per cookie in two competing products. Assume the population of the number of chocolate chips per cookie is normally distributed and the population variances are equal. Brand A Brand B Sample mean Sample size Sample standard deviation 6.4 5.6 11 10 1.1 1.7
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
![3. Refer to the table below, the average number of chocolate chips per cookie in two
competing products. Assume the population of the number of chocolate chips per cookie is
normally distributed and the population variances are equal.
Brand A
Sample mean
Sample size
Sample standard deviation
Brand B
5.6
11
6.4
10
1.1
1.7
The makers of Brand A claim that their cookies average more chocolate chips than Brand B.
Test this hypothesis at the a-05 level of significance.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fcb80be2b-8bba-4041-bb49-f3162a5db242%2F37d06e8c-0d8b-4d59-9ef7-b1ab25561b13%2Fo76scch_processed.jpeg&w=3840&q=75)
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