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3.4 Measures of Position and Outliers

3.4 Measures of Position and Outliers. The Z-Score

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Page 1: 3.4 Measures of Position and Outliers. The Z-Score

3.4

Measures of Position and Outliers

Page 2: 3.4 Measures of Position and Outliers. The Z-Score

The Z-Score

Page 3: 3.4 Measures of Position and Outliers. The Z-Score

EXAMPLE Using Z-Scores

The mean height of males 20 years or older is 69.1 inches with a standard deviation of 2.8 inches. The mean height of females 20 years or older is 63.7 inches with a standard deviation of 2.7 inches. Data based on information obtained from National Health and Examination Survey. Who is relatively taller?

Kevin Garnett whose height is 83 inches

or

Candace Parker whose height is 76 inches

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Page 4: 3.4 Measures of Position and Outliers. The Z-Score

83 69.1

2.84.96

kgz

76 63.7

2.74.56

cpz

Kevin Garnett’s height is 4.96 standard deviations above the mean. Candace Parker’s height is 4.56 standard deviations above the mean. Kevin Garnett is relatively taller.

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Page 5: 3.4 Measures of Position and Outliers. The Z-Score

Sample Problem

• Score on ACT was 26 with a mean of 22 and sd of 3. Score on SAT was 950 with mean of 925 and sd of 25. Which score is "better"?

Page 6: 3.4 Measures of Position and Outliers. The Z-Score

Quartiles divide data sets into fourths, or four equal parts.

• The 1st quartile, denoted Q1, divides the bottom 25% the data from the top 75%. Therefore, the 1st quartile is equivalent to the 25th percentile.

• The 2nd quartile divides the bottom 50% of the data from the top 50% of the data, so that the 2nd quartile is equivalent to the 50th percentile, which is equivalent to the median.

• The 3rd quartile divides the bottom 75% of the data from the top 25% of the data, so that the 3rd quartile is equivalent to the 75th percentile.

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Page 7: 3.4 Measures of Position and Outliers. The Z-Score

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Page 8: 3.4 Measures of Position and Outliers. The Z-Score

A group of Brigham Young University—Idaho students (Matthew Herring, Nathan Spencer, Mark Walker, and Mark Steiner) collected data on the speed of vehicles traveling through a construction zone on a state highway, where the posted speed was 25 mph. The recorded speed of 14 randomly selected vehicles is given below:

20, 24, 27, 28, 29, 30, 32, 33, 34, 36, 38, 39, 40, 40

Find and interpret the quartiles for speed in the construction zone. In addition find the mean, median, and standard deviation. (using technology)

EXAMPLE Finding and Interpreting Quartiles

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Page 9: 3.4 Measures of Position and Outliers. The Z-Score

Interpretation:

• 25% of the speeds are less than or equal to the first quartile, 28 miles per hour, and 75% of the speeds are greater than 28 miles per hour.

• 50% of the speeds are less than or equal to the second quartile, 32.5 miles per hour, and 50% of the speeds are greater than 32.5 miles per hour.

• 75% of the speeds are less than or equal to the third quartile, 38 miles per hour, and 25% of the speeds are greater than 38 miles per hour.

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Page 10: 3.4 Measures of Position and Outliers. The Z-Score

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Interquartile Range

Page 11: 3.4 Measures of Position and Outliers. The Z-Score

EXAMPLE Determining and Interpreting the Interquartile Range

Determine and interpret the interquartile range of the speed data.

Q1 = 28 Q3 = 38

3 1IQR

38 28

10

Q Q

The range of the middle 50% of the speed of cars traveling through the construction zone is 10 miles per hour.

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Page 12: 3.4 Measures of Position and Outliers. The Z-Score

Suppose a 15th car travels through the construction zone at 100 miles per hour. How does this value impact the mean, median, standard deviation, and interquartile range?

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With Out 15th Car With 15th Car

Mean

Median

Standard Deviation

IQR

Which measures should we report now?

When we add the 15th car which changes less – the mean or median (measures of center)?

When we add the 15th car which changes les – the standard deviation or the IQR

(measures of dispersion)?

Page 13: 3.4 Measures of Position and Outliers. The Z-Score

Suppose a 15th car travels through the construction zone at 100 miles per hour. How does this value impact the mean, median, standard deviation, and interquartile range?

Without 15th car With 15th car

Mean 32.1 mph 36.7 mph

Median 32.5 mph 33 mph

Standard deviation 6.2 mph 18.5 mph

IQR 10 mph 11 mph

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Page 14: 3.4 Measures of Position and Outliers. The Z-Score

Outliers

Page 15: 3.4 Measures of Position and Outliers. The Z-Score

EXAMPLE Determining and Interpreting the Interquartile Range

Check the speed data for outliers.

Step 1: The first and third quartiles are Q1 = 28 mph and Q3 = 38 mph.

Step 2: The interquartile range is 10 mph.

Step 3: The fences are

Lower Fence = Q1 – 1.5(IQR) Upper Fence = Q3 + 1.5(IQR)

= 28 – 1.5(10) = 38 + 1.5(10)

= 13 mph = 53 mph

Step 4: There are no values less than 13 mph or greater than 53 mph. Therefore, there are no outliers.

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Page 16: 3.4 Measures of Position and Outliers. The Z-Score

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5-Number Summary and BoxPlots

Page 17: 3.4 Measures of Position and Outliers. The Z-Score

5-Number Summary

Page 18: 3.4 Measures of Position and Outliers. The Z-Score

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Boxplots

Page 19: 3.4 Measures of Position and Outliers. The Z-Score

EXAMPLE Constructing a Boxplot

Every six months, the United States Federal Reserve Board conducts a survey of credit card plans in the U.S. The following data are the interest rates charged by 10 credit card issuers randomly selected for the July 2005 survey. Draw a boxplot of the data.

Institution Rate

Pulaski Bank and Trust Company 6.5%

Rainier Pacific Savings Bank 12.0%

Wells Fargo Bank NA 14.4%

Firstbank of Colorado 14.4%

Lafayette Ambassador Bank 14.3%

Infibank 13.0%

United Bank, Inc. 13.3%

First National Bank of The Mid-Cities 13.9%

Bank of Louisiana 9.9%

Bar Harbor Bank and Trust Company 14.5%

Source: http://www.federalreserve.gov/pubs/SHOP/survey.htm

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Page 20: 3.4 Measures of Position and Outliers. The Z-Score

Step 1: The interquartile range (IQR) is 14.4% - 12% = 2.4%. The lower and upper fences are:

Lower Fence = Q1 – 1.5(IQR) Upper Fence = Q3 + 1.5(IQR)

= 12 – 1.5(2.4) = 14.4 + 1.5(2.4)

= 8.4% = 18.0%

Step 2:

[ ]*

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Page 21: 3.4 Measures of Position and Outliers. The Z-Score

TI-nspire – Creating a BoxPlot• See handout• Use the Nspire calculator to create a

boxplot of the data from the previous problem

Page 22: 3.4 Measures of Position and Outliers. The Z-Score

The interest rate boxplot indicates that the distribution is skewed left.

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