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Section 2.4. Measures of Variation. Section 2.4 Objectives. Determine the range of a data set Determine the variance and standard deviation of a population and of a sample Use the Empirical Rule and Chebychev’s Theorem to interpret standard deviation

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Section 2 4

Section 2.4

Measures of Variation

Larson/Farber 4th ed.


Section 2 4 objectives
Section 2.4 Objectives

  • Determine the range of a data set

  • Determine the variance and standard deviation of a population and of a sample

  • Use the Empirical Rule and Chebychev’s Theorem to interpret standard deviation

  • Approximate the sample standard deviation for grouped data

Larson/Farber 4th ed.


Range
Range

Range

  • The difference between the maximum and minimum data entries in the set.

  • The data must be quantitative.

  • Range = (Max. data entry) – (Min. data entry)

Larson/Farber 4th ed.


Example finding the range
Example: Finding the Range

A corporation hired 10 graduates. The starting salaries for each graduate are shown. Find the range of the starting salaries.

Starting salaries (1000s of dollars)

41 38 39 45 47 41 44 41 37 42

Larson/Farber 4th ed.


Solution finding the range

minimum

maximum

Solution: Finding the Range

  • Ordering the data helps to find the least and greatest salaries.

    37 38 39 41 41 41 42 44 45 47

  • Range = (Max. salary) – (Min. salary)

    = 47 – 37 = 10

    The range of starting salaries is 10 or $10,000.

Larson/Farber 4th ed.


Deviation variance and standard deviation
Deviation, Variance, and Standard Deviation

Deviation

  • The difference between the data entry, x, and the mean of the data set.

  • Population data set:

    • Deviation of x = x – μ

  • Sample data set:

    • Deviation of x = x – x

Larson/Farber 4th ed.


Example finding the deviation
Example: Finding the Deviation

A corporation hired 10 graduates. The starting salaries for each graduate are shown. Find the deviation of the starting salaries.

Starting salaries (1000s of dollars)

41 38 39 45 47 41 44 41 37 42

  • Solution:

  • First determine the mean starting salary.

Larson/Farber 4th ed.


Solution finding the deviation
Solution: Finding the Deviation

Σ(x – μ) = 0

Σx = 415

Larson/Farber 4th ed.

  • Determine the deviation for each data entry.


Deviation variance and standard deviation1
Deviation, Variance, and Standard Deviation

Population Variance

Population Standard Deviation

Sum of squares, SSx

Larson/Farber 4th ed.


Finding the population variance standard deviation
Finding the Population Variance & Standard Deviation

In Words In Symbols

  • Find the mean of the population data set.

  • Find deviation of each entry.

  • Square each deviation.

  • Add to get the sum of squares.

x – μ

(x – μ)2

SSx = Σ(x – μ)2

Larson/Farber 4th ed.


Finding the population variance standard deviation1
Finding the Population Variance & Standard Deviation

In Words In Symbols

  • Divide by N to get the population variance.

  • Find the square root to get the population standard deviation.

Larson/Farber 4th ed.


Example finding the population standard deviation
Example: Finding the Population Standard Deviation

A corporation hired 10 graduates. The starting salaries for each graduate are shown. Find the population variance and standard deviation of the starting salaries.

Starting salaries (1000s of dollars)

41 38 39 45 47 41 44 41 37 42

Recall μ = 41.5.

Larson/Farber 4th ed.


Solution finding the population standard deviation
Solution: Finding the Population Standard Deviation

Σ(x – μ) = 0

SSx = 88.5

Larson/Farber 4th ed.

Determine SSx

N = 10


Solution finding the population standard deviation1
Solution: Finding the Population Standard Deviation

Population Variance

Population Standard Deviation

The population standard deviation is about 3.0, or $3000.

Larson/Farber 4th ed.


Deviation variance and standard deviation2
Deviation, Variance, and Standard Deviation

Sample Variance

Sample Standard Deviation

Larson/Farber 4th ed.


Finding the sample variance standard deviation
Finding the Sample Variance & Standard Deviation

In Words In Symbols

  • Find the mean of the sample data set.

  • Find deviation of each entry.

  • Square each deviation.

  • Add to get the sum of squares.

Larson/Farber 4th ed.


Finding the sample variance standard deviation1
Finding the Sample Variance & Standard Deviation

In Words In Symbols

  • Divide by n – 1 to get the sample variance.

  • Find the square root to get the sample standard deviation.

Larson/Farber 4th ed.


Example finding the sample standard deviation
Example: Finding the Sample Standard Deviation

The starting salaries are for the Chicago branches of a corporation. The corporation has several other branches, and you plan to use the starting salaries of the Chicago branches to estimate the starting salaries for the larger population. Find the sample standard deviation of the starting salaries.

Starting salaries (1000s of dollars)

41 38 39 45 47 41 44 41 37 42

Larson/Farber 4th ed.


Solution finding the sample standard deviation
Solution: Finding the Sample Standard Deviation

Σ(x – μ) = 0

SSx = 88.5

Larson/Farber 4th ed.

Determine SSx

n = 10


Solution finding the sample standard deviation1
Solution: Finding the Sample Standard Deviation

Sample Variance

Sample Standard Deviation

The sample standard deviation is about 3.1, or $3100.

Larson/Farber 4th ed.


Example using technology to find the standard deviation
Example: Using Technology to Find the Standard Deviation

Sample office rental rates (in dollars per square foot per year) for Miami’s central business district are shown in the table. Use a calculator or a computer to find the mean rental rate and the sample standard deviation. (Adapted from: Cushman & Wakefield Inc.)

Larson/Farber 4th ed.


Solution using technology to find the standard deviation
Solution: Using Technology to Find the Standard Deviation

Sample Mean

Sample Standard Deviation

Larson/Farber 4th ed.


Interpreting standard deviation
Interpreting Standard Deviation

  • Standard deviation is a measure of the typical amount an entry deviates from the mean.

  • The more the entries are spread out, the greater the standard deviation.

Larson/Farber 4th ed.


Interpreting standard deviation empirical rule 68 95 99 7 rule
Interpreting Standard Deviation: Empirical Rule (68 – 95 – 99.7 Rule)

For data with a (symmetric) bell-shaped distribution, the standard deviation has the following characteristics:

  • About 68%of the data lie within one standard deviation of the mean.

  • About95%of the data lie within two standard deviations of the mean.

  • About99.7%of the data lie within three standard deviations of the mean.

Larson/Farber 4th ed.


Interpreting standard deviation empirical rule 68 95 99 7 rule1
Interpreting Standard Deviation: Empirical Rule (68 – 95 – 99.7 Rule)

99.7% within 3 standard deviations

95% within 2 standard deviations

68% within 1 standard deviation

34%

34%

2.35%

2.35%

13.5%

13.5%

Larson/Farber 4th ed.


Example using the empirical rule
Example: Using the Empirical Rule – 99.7 Rule)

In a survey conducted by the National Center for Health Statistics, the sample mean height of women in the United States (ages 20-29) was 64 inches, with a sample standard deviation of 2.71 inches. Estimate the percent of the women whose heights are between 64 inches and 69.42 inches.

Larson/Farber 4th ed.


Solution using the empirical rule
Solution: Using the Empirical Rule – 99.7 Rule)

  • Because the distribution is bell-shaped, you can use the Empirical Rule.

34%

13.5%

55.87

58.58

61.29

64

66.71

69.42

72.13

34% + 13.5% = 47.5% of women are between 64 and 69.42 inches tall.

Larson/Farber 4th ed.


Chebychev s theorem
Chebychev’s Theorem – 99.7 Rule)

  • The portion of any data set lying within k standard deviations (k > 1) of the mean is at least:

  • k = 2: In any data set, at least

of the data lie within 2 standard deviations of the mean.

  • k = 3: In any data set, at least

of the data lie within 3 standard deviations of the mean.

Larson/Farber 4th ed.


Example using chebychev s theorem
Example: Using Chebychev’s Theorem – 99.7 Rule)

The age distribution for Florida is shown in the histogram. Apply Chebychev’s Theorem to the data using k = 2. What can you conclude?

Larson/Farber 4th ed.


Solution using chebychev s theorem
Solution: Using Chebychev’s Theorem – 99.7 Rule)

k = 2: μ – 2σ = 39.2 – 2(24.8) = -10.4 (use 0 since age can’t be negative)

μ + 2σ = 39.2 + 2(24.8) = 88.8

At least 75% of the population of Florida is between 0 and 88.8 years old.

Larson/Farber 4th ed.


Standard deviation for grouped data
Standard Deviation for Grouped Data – 99.7 Rule)

Sample standard deviation for a frequency distribution

  • When a frequency distribution has classes, estimate the sample mean and standard deviation by using the midpoint of each class.

where n= Σf (the number of entries in the data set)

Larson/Farber 4th ed.


Example finding the standard deviation for grouped data
Example: Finding the Standard Deviation for Grouped Data – 99.7 Rule)

Larson/Farber 4th ed.

You collect a random sample of the number of children per household in a region. Find the sample mean and the sample standard deviation of the data set.


Solution finding the standard deviation for grouped data
Solution: Finding the Standard Deviation for Grouped Data – 99.7 Rule)

  • First construct a frequency distribution.

  • Find the mean of the frequency distribution.

The sample mean is about 1.8 children.

Σf = 50

Σ(xf )= 91

Larson/Farber 4th ed.


Solution finding the standard deviation for grouped data1
Solution: Finding the Standard Deviation for Grouped Data – 99.7 Rule)

  • Determine the sum of squares.

Larson/Farber 4th ed.


Solution finding the standard deviation for grouped data2
Solution: Finding the Standard Deviation for Grouped Data – 99.7 Rule)

  • Find the sample standard deviation.

The standard deviation is about 1.7 children.

Larson/Farber 4th ed.


Section 2 4 summary
Section 2.4 Summary – 99.7 Rule)

  • Determined the range of a data set

  • Determined the variance and standard deviation of a population and of a sample

  • Used the Empirical Rule and Chebychev’s Theorem to interpret standard deviation

  • Approximated the sample standard deviation for grouped data

Larson/Farber 4th ed.


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