In a study conducted to investigate browsing activity by shoppers, each shopper was initially classified as a nonbrowser, light browser, or heavy browser. For each shopper, the study obtained a measure to determine how comfortable the shopper was in a store. Higher scores indicated greater comfort. Suppose the following data were collected. LightHeavy NonbrowserBrowserBrowser 1097 11109 1297 989 9116 1088 11107 1099. Use to test for a difference among mean comfort scores for the three types of browsers.Compute the values identified below (to 2 decimals, if necessary).Sum of Squares, Treatment Sum of Squares, Error Mean Squares, Treatment Mean Squares, Error Calculate the value of the test statistic (to 2 decimals, if necessary). The -value is - Select your answer -less than .01between .01 and .025between .025 and .05between .05 and .10greater than .10Item 6 What is your conclusion?- Select your answer -Conclude that the mean comfort scores are not all the same for the browser groupsDo not reject the assumption that the mean comfort scores are equal for the browser groupsItem 7 b. Use Fisher's LSD procedure to compare the comfort levels of nonbrowsers and light browsers. Use .Compute the LSD critical value (to 2 decimals).

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Description: In a study conducted to investigate browsing activity by shoppers, each shopper was initially classified as a nonbrowser, light browser, or heavy browser. For each shopper, the study obtained a measure to determine how comfortable the shopper was in

To test the difference between the comfort scores of the three types of browsers, B1, B2, B3 (say).…

Answered: Light Heavy Nonbrowser Browser…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.6: Summarizing Categorical Data

Problem 4BGP

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In a study conducted to investigate browsing activity by shoppers, each shopper was initially classified as a nonbrowser, light browser, or heavy browser. For each shopper, the study obtained a measure to determine how comfortable the shopper was in a store. Higher scores indicated greater comfort. Suppose the following data were collected.

Light	Heavy
Nonbrowser	Browser	Browser
10	9	7
11	10	9
12	9	7
9	8	9
9	11	6
10	8	8
11	10	7
10	9	9

. Use to test for a difference among mean comfort scores for the three types of browsers.

Compute the values identified below (to 2 decimals, if necessary).

Sum of Squares, Treatment
Sum of Squares, Error
Mean Squares, Treatment
Mean Squares, Error

Calculate the value of the test statistic (to 2 decimals, if necessary).

The -value is - Select your answer -less than .01between .01 and .025between .025 and .05between .05 and .10greater than .10Item 6

What is your conclusion?

- Select your answer -Conclude that the mean comfort scores are not all the same for the browser groupsDo not reject the assumption that the mean comfort scores are equal for the browser groupsItem 7

b. Use Fisher's LSD procedure to compare the comfort levels of nonbrowsers and light browsers. Use .

Compute the LSD critical value (to 2 decimals).

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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