The united States ranks ninth in the world in per capita chocolate consumption; the aver- age American eats 9.5 pounds of chocolate annually (Forbes, July 22, 2015). Suppose you are curious whether chocolate consumption is higher in Hershey, Pennsylvania, the location of The Hershey Company’s corporate headquarters. A sample of 36 individuals from the Hershey area showed a sample mean annual consumption of 10.05 pounds and a standard devi- ation of s = 1.5 pounds. using α = 0.05, do the sample results support the conclusion that mean annual consumption of chocolate is higher in Hershey than it is throughout the united States?

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Description: The united States ranks ninth in the world in per capita chocolate consumption; the aver- age American eats 9.5 pounds of chocolate annually (Forbes, July 22, 2015). Suppose you are curious whether chocolate consumption is higher in Hershey, Pennsylv

The Null hypothesis H0: μ ≤ 9.5. Alternative hypothesis H1: μ >9.5 Since sample size is small…

Answered: The united States ranks ninth in the…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

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Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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The united States ranks ninth in the world in per capita chocolate consumption; the aver- age American eats 9.5 pounds of chocolate annually (Forbes, July 22, 2015). Suppose you are curious whether chocolate consumption is higher in Hershey, Pennsylvania, the location of The Hershey Company’s corporate headquarters. A sample of 36 individuals from the Hershey area showed a sample mean annual consumption of 10.05 pounds and a standard devi- ation of s = 1.5 pounds. using α = 0.05, do the sample results support the conclusion that mean annual consumption of chocolate is higher in Hershey than it is throughout the united States?

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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