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Find the range, variance, and standard deviation for the given sample data. Include appropriate units (such as "minutes") in your results. (The same data were used in Section 3-I, where we found measures of center. Here we find measures of variation.) Then answer the given questions. Listed below in dollars are the annual costs of tuition and fees at the 10 most expensive colleges in the United States for a recent year (based on data from \(U . S .\) News \& World Report). The colleges listed in order are Columbia, Vassar, Trinity, George Washington, Carnegie Mellon, Wesleyan, Tulane, Bucknell, Oberlin, and Union. What does this "top 10" list tell us about the variation among costs for the population of all U.S. college tuition? $$\begin{array}{rlllllllll} 49,138 & 47,890 & 47,510 & 47,343 & 46,962 & 46,944 & 46,930 & 46,902 & 46,870 & 46,785 \end{array}$$

Short Answer

Expert verified
Range: \(2,353 \text{ dollars}\), Variance: \(615,759.82 \text{ dollars}^2\), Standard Deviation: \(784.69 \text{ dollars}\).

Step by step solution

01

Order the Data

Ensure the data is listed from lowest to highest value. This helps to easily find the range and other measures. The ordered list is: 46,785, 46,870, 46,902, 46,930, 46,944, 46,962, 47,343, 47,510, 47,890, 49,138.
02

Calculate the Range

The range is the difference between the highest and lowest values in the data set. Range = \(49,138 - 46,785 = 2,353\) dollars.
03

Calculate the Mean

The mean \(\bar{x}\) is the sum of all data values divided by the number of values. \[\bar{x} = \frac{46,785 + 46,870 + 46,902 + 46,930 + 46,944 + 46,962 + 47,343 + 47,510 + 47,890 + 49,138}{10} = 47,327.4 \text{ dollars} \]
04

Calculate the Variance

Variance is the average of the squared differences from the Mean.\[\text{Variance} (\sigma^2) = \frac{(46,785 - 47,327.4)^2 + (46,870 - 47,327.4)^2 + \ \text{...} + (49,138 - 47,327.4)^2}{10 - 1} = 615,759.82 \text{ dollars}^2\]
05

Calculate the Standard Deviation

The standard deviation \(\sigma\) is the square root of the variance.\[\sigma = \sqrt{615,759.82} = 784.69 \text{ dollars}\]
06

Interpretation

The range, variance, and standard deviation are measures of variation that tell us how much the tuition costs vary among these top 10 expensive colleges. A higher standard deviation indicates a greater variation in costs.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Range Calculation
The concept of range is one of the simplest measures of variation. It tells us the spread of the data set by calculating the difference between the highest and lowest values. In the context of our exercise, the annual costs of tuition and fees reported are: 49,138, 47,890, 47,510, 47,343, 46,962, 46,944, 46,930, 46,902, 46,870, and 46,785 dollars. To find the range, we subtract the smallest value (46,785 dollars) from the largest value (49,138 dollars):
Range = 49,138 - 46,785 = 2,353 dollars.
This indicates that there is a 2,353 dollar difference between the most and least expensive tuitions among these colleges.
Variance Calculation
Variance measures the average squared differences from the mean, giving us a sense of how spread out the values are in a data set. For our data set, the colleges' tuitions are re-ordered as follows: 46,785, 46,870, 46,902, 46,930, 46,944, 46,962, 47,343, 47,510, 47,890, and 49,138 dollars.
First, we calculate the mean (average), \(\bar{x}\), of these values:
\[ \bar{x} = \frac{46,785 + 46,870 + 46,902 + 46,930 + 46,944 + 46,962 + 47,343 + 47,510 + 47,890 + 49,138}{10} = 47,327.4 \text{ dollars} \]
Next, we find the squared differences from the mean for each data point, sum those squared differences, and divide by one less than the number of data points (since we are dealing with a sample).
\[ \text{Variance} (\sigma^2) = \frac{(46,785 - 47,327.4)^2 + (46,870 - 47,327.4)^2 + \text{...} + (49,138 - 47,327.4)^2}{10 - 1} = 615,759.82 \text{ dollars}^2 \]
This variation value gives us an overall measure of how much the tuitions differ from the mean.
Standard Deviation Calculation
While variance gives us a useful measure of data spread, it is in squared units which can be difficult to interpret with the original data. This is where the standard deviation comes in handy as it is in the same units as the original data.
Standard deviation is the square root of the variance.
\[ \sigma = \sqrt{615,759.82} = 784.69 \text{ dollars} \]
Hence, the standard deviation for our data set of tuition costs is 784.69 dollars. This means that, on average, the tuition costs deviate from the mean by about 784.69 dollars, providing a more intuitive understanding of the variation in tuition costs for these top 10 expensive colleges.

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Most popular questions from this chapter

The 20 brain volumes \(\left(\mathrm{cm}^{3}\right)\) from Data Set 8 "IQ and Brain Size" in Appendix B vary from a low of \(963 \mathrm{cm}^{3}\) to a high of \(1439 \mathrm{cm}^{3} .\) Use the range rule of thumb to estimate the standard deviation \(s\) and compare the result to the exact standard deviation of \(124.9 \mathrm{cm}^{3}\).

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