Trimmed Mean Because the mean is very sensitive to extreme values, we say that it is not a resistant measure of center. By deleting some low values and high values, the trimmed mean is more resistant. To find the 10% trimmed mean for a data set, first arrange the data in order, then delete the bottom 10% of the values and delete the top 10% of the values, and then calculate the mean of the remaining values. Refer to the BMI values for females in Data Set 1 in Appendix B, and change the highest value from 47.24 to 472.4, so the value of 472.4 is an outlier. Find (a) the mean; (b) the 10% trimmed mean; (c) the 20% trimmed mean. How do the results compare?
Trimmed Mean Because the mean is very sensitive to extreme values, we say that it is not a resistant measure of center. By deleting some low values and high values, the trimmed mean is more resistant. To find the 10% trimmed mean for a data set, first arrange the data in order, then delete the bottom 10% of the values and delete the top 10% of the values, and then calculate the mean of the remaining values. Refer to the BMI values for females in Data Set 1 in Appendix B, and change the highest value from 47.24 to 472.4, so the value of 472.4 is an outlier. Find (a) the mean; (b) the 10% trimmed mean; (c) the 20% trimmed mean. How do the results compare?
Solution Summary: The author explains that the data set represents the BMI values for females, and change the value 47.24 to 427.4 is an outlier.
Trimmed Mean Because the mean is very sensitive to extreme values, we say that it is not a resistant measure of center. By deleting some low values and high values, the trimmed mean is more resistant. To find the 10% trimmed mean for a data set, first arrange the data in order, then delete the bottom 10% of the values and delete the top 10% of the values, and then calculate the mean of the remaining values. Refer to the BMI values for females in Data Set 1 in Appendix B, and change the highest value from 47.24 to 472.4, so the value of 472.4 is an outlier. Find (a) the mean; (b) the 10% trimmed mean; (c) the 20% trimmed mean. How do the results compare?
Statistics that help describe, summarize, and present information extracted from data. Descriptive statistics include concepts related to measures of central tendency, measures of variability, measures of frequency, shape of distribution, and some data visualization techniques/tools such as pivot tables, charts, and graphs.
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