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Section 2.4 Measures of Variation Larson/Farber 4th ed.

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Section 2.4. Measures of Variation. Larson/Farber 4th ed. 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 - PowerPoint PPT Presentation

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Page 1: Section 2.4

Section 2.4

Measures of Variation

Larson/Farber 4th ed.

Page 2: Section 2.4

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.

Page 3: Section 2.4

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.

Page 4: Section 2.4

Example: Finding the Range

A sample of annual salaries (in thousands of dollars) for private school teachers. Find the range of the salaries.

21.8 18.4 20.3 17.6 19.7 18.3 19.4 20.8

Larson/Farber 4th ed.

Page 5: Section 2.4

Solution: Finding the Range

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

17.6 18.3 18.4 19.4 19.7 20.3 20.8 21.8

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

= 21.8 – 17.6 = 4.2

The range of starting salaries is 4.2 or $4,200.

Larson/Farber 4th ed.

minimum maximum

Page 6: Section 2.4

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.

Page 7: Section 2.4

Example: Finding the Deviation

A sample of annual salaries (in thousands of dollars) for private school teachers. Find the range of the salaries.

21.8 18.4 20.3 17.6 19.7 18.3 19.4 20.8

Larson/Farber 4th ed.

Solution:• First determine the mean annual salary.

Page 8: Section 2.4

Solution: Finding the Deviation

Larson/Farber 4th ed.

• Determine the deviation for each data entry.

Salary, x Deviation: x – μ

19.54

17.6 17.6 - 19.54 = -1.94

18.3 18.3 - 19.54 = -1.24

18.4 18.4 - 19.54 = -1.14

19.4 19.4 - 19.54 = -0.14

19.7 19.7 - 19.54 = 0.16

20.3 20.3 - 19.54 = 0.76

20.8 20.8 - 19.54 = 1.26

21.8 21.8 - 19.54 = 2.26

Σx = 156.3 0.00

Σ(x – μ) = 0

Page 9: Section 2.4

Finding the Sample Variance & Standard Deviation

In Words In Symbols

Larson/Farber 4th ed.

1. Find the mean of the sample data set.

2. Find deviation of each entry.

3. Square each deviation.

4. Add to get the sum of squares.

Page 10: Section 2.4

Finding the Sample Variance & Standard Deviation

Larson/Farber 4th ed.

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

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

In Words In Symbols

Page 11: Section 2.4

Finding the Population Variance & Standard Deviation

In Words In Symbols

Larson/Farber 4th ed.

1. Find the mean of the population data set.

2. Find deviation of each entry.

3. Square each deviation.

4. Add to get the sum of squares.

x – μ

(x – μ)2

SSx = Σ(x – μ)2

Page 12: Section 2.4

Finding the Population Variance & Standard Deviation

Larson/Farber 4th ed.

5. Divide by N to get the population variance.

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

In Words In Symbols

Page 13: Section 2.4

Compare Variance

Population Sample

Page 14: Section 2.4

Example: Finding the Standard Deviation

A sample of annual salaries (in thousands of dollars) for private school teachers. Find the range of the salaries.

21.8 18.4 20.3 17.6 19.7 18.3 19.4 20.8

Larson/Farber 4th ed.

Page 15: Section 2.4

Solution: Finding the Standard Deviation

Larson/Farber 4th ed.

• Determine SSx

• n = 8Salary, x Deviation: x – μ

19.54

1 17.6 17.6 - 19.54 = -1.94 3.75

2 18.3 18.3 - 19.54 = -1.24 1.53

3 18.4 18.4 - 19.54 = -1.14 1.29

4 19.4 19.4 - 19.54 = -0.14 0.02

5 19.7 19.7 - 19.54 = 0.16 0.03

6 20.3 20.3 - 19.54 = 0.76 0.58

7 20.8 20.8 - 19.54 = 1.26 1.59

8 21.8 21.8 - 19.54 = 2.26 5.12

Σx = 156.3 13.92

Page 16: Section 2.4

Solution: Finding the Sample Variance

Larson/Farber 4th ed.

Sample Variance

The sample variance is 1.99 or roughly 2 or 1,990.

Population Variance

Page 17: Section 2.4

Solution: Finding the Sample Standard Deviation

Larson/Farber 4th ed.

Sample Standard Deviation

The sample standard deviation is about 1.41 or 1410.

Page 18: Section 2.4

Interpreting Standard Deviation

• Do Problem #26

Larson/Farber 4th ed.

Page 19: Section 2.4

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:

Larson/Farber 4th ed.

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

• About 95% of the data lie within two standard deviations of the mean.

• About 99.7% of the data lie within three standard deviations of the mean.

Page 20: Section 2.4

Interpreting Standard Deviation: Empirical Rule (68 – 95 – 99.7 Rule)

Larson/Farber 4th ed.

68% within 1 standard deviation

34% 34%

99.7% within 3 standard deviations

2.35% 2.35%

95% within 2 standard deviations

13.5% 13.5%

Page 21: Section 2.4

Example: Using the Empirical Rule

The mean value of land and buildings per acre from a sample of farms is $2400, with a standard deviation of $450. Between what values do about 95% of the data lie? What percent of the values are between $2400 and $3300?

Larson/Farber 4th ed.

2400 + 2(450) = 3300

2400 - 2(450) = 1500

Page 22: Section 2.4

Solution: Using the Empirical Rule

Larson/Farber 4th ed.

$1050 $1500 $1950 $2400 $2850 $3300 $3750

34%

13.5%

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

34% + 13.5% = 47.5% of land values are between $2400 and $3300.

Page 23: Section 2.4

Chebychev’s Theorem

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

Larson/Farber 4th ed.

• 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.

Page 24: Section 2.4

Example: Using Chebychev’s Theorem

The mean time in a women’s 400-meter dash is 57.07 seconds, with a standard deviation of 1.05. Using Chebychev’s Theorem for k = 2, 4, 6.

Larson/Farber 4th ed.

57.07 - 2(1.05) = 54.97

57.07 + 2(1.05) = 59.17

75% of the women came in between 54.97 and 59.17 seconds.

Page 25: Section 2.4

Standard Deviation for Grouped Data

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.

Larson/Farber 4th ed.

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

Page 26: Section 2.4

Example: Finding the Standard Deviation for Grouped Data

Larson/Farber 4th ed.

Do #40 on page 97

Page 27: Section 2.4

Section 2.4 Summary

• 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• Homework 2.4 EOO

Larson/Farber 4th ed.