Students in an experimental psychology class did research on depression as a sign of stress. A test was administered to a sample of 30 students. The scores are shown below. 44 50 10 91 76 36 64 37 43 72 53 62 36 74 50 D 72 37 28 38 61 48 63 36 41 21 37 50 47 86 14 To find the 10% trimmed mean of a data set, order the data, delete the lowest 10% of the entries and the highest 10% of the entries, and find the mean of the remaining entries. Complete parts (a) through (c). (a) Find the 10% trimmed mean for the data. The 10% trimmed mean is. (Round to the nearest tenth as needed.) (b) Compare the four measures of central tendency, including the midrange. Mean = (Round to the nearest tenth as needed.) Median = Mode = (Use comma to separate answers as needed.) The midrange is found by the following formula. (Maximum data entry) + (Minimum data entry) 2 Midrange = (Round to the nearest tenth as needed.) (c) What is the benefit of using a trimmed mean versus using a mean found using all data entries? O A. It permits the comparison of the measures of central tendency.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.4: Distributions Of Data
Problem 19PFA
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Students in an experimental psychology class did research on depression as a sign of stress. A test was administered to a sample of 30 students. The scores are shown below.
44 50 10 91 76 36 64 37 43 72 53 62 36 74 50 D
72 37 28 38 61 48 63 36 41 21 37 50 47 86 14
To find the 10% trimmed mean of a data set, order the data, delete the lowest 10% of the entries and the highest 10% of the entries, and find the mean of the remaining entries. Complete parts (a) through (c).
(a) Find the 10% trimmed mean for the data.
The 10% trimmed mean is
(Round to the nearest tenth as needed.)
(b) Compare the four measures of central tendency, including the midrange.
Mean =|
(Round to the nearest tenth as needed.)
Median =
Mode = (Use a comma to separate answers as needed.)
The midrange is found by the following formula.
(Maximum data entry) + (Minimum data entry)
2
Midrange =
(Round to the nearest tenth as needed.)
(c) What is the benefit of using a trimmed mean versus using a mean found using all data entries?
O A. It permits the comparison of the measures of central tendency.
Transcribed Image Text:Students in an experimental psychology class did research on depression as a sign of stress. A test was administered to a sample of 30 students. The scores are shown below. 44 50 10 91 76 36 64 37 43 72 53 62 36 74 50 D 72 37 28 38 61 48 63 36 41 21 37 50 47 86 14 To find the 10% trimmed mean of a data set, order the data, delete the lowest 10% of the entries and the highest 10% of the entries, and find the mean of the remaining entries. Complete parts (a) through (c). (a) Find the 10% trimmed mean for the data. The 10% trimmed mean is (Round to the nearest tenth as needed.) (b) Compare the four measures of central tendency, including the midrange. Mean =| (Round to the nearest tenth as needed.) Median = Mode = (Use a comma to separate answers as needed.) The midrange is found by the following formula. (Maximum data entry) + (Minimum data entry) 2 Midrange = (Round to the nearest tenth as needed.) (c) What is the benefit of using a trimmed mean versus using a mean found using all data entries? O A. It permits the comparison of the measures of central tendency.
(c) What is the benefit of using a trimmed mean versus using a mean found using all data entries?
O A. It permits the comparison of the measures of central tendency.
O B. It eliminates potential outliers that could affect the mean of the entries.
OC. It simply decreases the number of computations in finding the mean.
O D. It permits finding the mean of a data set more exactly.
Transcribed Image Text:(c) What is the benefit of using a trimmed mean versus using a mean found using all data entries? O A. It permits the comparison of the measures of central tendency. O B. It eliminates potential outliers that could affect the mean of the entries. OC. It simply decreases the number of computations in finding the mean. O D. It permits finding the mean of a data set more exactly.
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