7. Transformations. In some data sets, a transformation by some mathematical function applied to the original data, such as √√y or log y, can result in data that are simpler to work with statistically than the original data. To illustrate the effect of a transformation, consider the following data, which represent cycles to failure for a yarn product: 1150 2000 100 3650 175 290 375 675 Transform the data in 2 significant figures by taking the common logarithms of the eight values (example: log 675 = 2.8). Calculate the standard deviation of these transformed data. Express your answer in 2 significant digits.

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7. Transformations. In some data sets, a transformation by some mathematical function
applied to the original data, such as √y or logy, can result in data that are simpler to
work with statistically than the original data. To illustrate the effect of a transformation,
consider the following data, which represent cycles to failure for a yarn product:
675
3650
175
1150
290
2000
100
375
Transform the data in 2 significant figures by taking the common logarithms of the eight
values (example: log 675 = 2.8). Calculate the standard deviation of these transformed data.
Express your answer in 2 significant digits.
Transcribed Image Text:7. Transformations. In some data sets, a transformation by some mathematical function applied to the original data, such as √y or logy, can result in data that are simpler to work with statistically than the original data. To illustrate the effect of a transformation, consider the following data, which represent cycles to failure for a yarn product: 675 3650 175 1150 290 2000 100 375 Transform the data in 2 significant figures by taking the common logarithms of the eight values (example: log 675 = 2.8). Calculate the standard deviation of these transformed data. Express your answer in 2 significant digits.
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