Consider two completely different data sets: price per gallon of gas in Fort Pierce and SAT scores of students at a certain high school. The price per gallon of gas data set has a mean of $2.48 and a standard deviation of $1.15. The high school SAT scores data set has a mean of 1100 and a standard deviation of 179. Calculate the Coefficient of Variation for both data sets. Round solutions to one decimal place, if necessary. Coefficient of Variation for the price per gallon of gas data set: % Coefficient of Variation for high school SAT scores data set: % Which data set has greater variability? Thus, we see that when comparing two data sets, the data set with the larger standard deviation necessarily have greater variabilty.
Consider two completely different data sets: price per gallon of gas in Fort Pierce and SAT scores of students at a certain high school. The price per gallon of gas data set has a mean of $2.48 and a standard deviation of $1.15. The high school SAT scores data set has a mean of 1100 and a standard deviation of 179. Calculate the Coefficient of Variation for both data sets. Round solutions to one decimal place, if necessary. Coefficient of Variation for the price per gallon of gas data set: % Coefficient of Variation for high school SAT scores data set: % Which data set has greater variability? Thus, we see that when comparing two data sets, the data set with the larger standard deviation necessarily have greater variabilty.
Consider two completely different data sets: price per gallon of gas in Fort Pierce and SAT scores of students at a certain high school. The price per gallon of gas data set has a mean of $2.48 and a standard deviation of $1.15. The high school SAT scores data set has a mean of 1100 and a standard deviation of 179. Calculate the Coefficient of Variation for both data sets. Round solutions to one decimal place, if necessary. Coefficient of Variation for the price per gallon of gas data set: % Coefficient of Variation for high school SAT scores data set: % Which data set has greater variability? Thus, we see that when comparing two data sets, the data set with the larger standard deviation necessarily have greater variabilty.
Consider two completely different data sets: price per gallon of gas in Fort Pierce and SAT scores of students at a certain high school.
The price per gallon of gas data set has a mean of $2.48 and a standard deviation of $1.15.
The high school SAT scores data set has a mean of 1100 and a standard deviation of 179.
Calculate the Coefficient of Variation for both data sets. Round solutions to one decimal place, if necessary.
Coefficient of Variation for the price per gallon of gas data set: %
Coefficient of Variation for high school SAT scores data set: %
Which data set has greater variability?
Thus, we see that when comparing two data sets, the data set with the larger standard deviation necessarily have greater variabilty.
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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