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Chapter 3 Numerically Summarizing Data - PowerPoint PPT Presentation

Chapter 3 Numerically Summarizing Data. Insert photo of cover. Section 3.2 Measures of Dispersion. Objectives Compute the range of a variable from raw data Compute the variance of a variable from raw data Compute the standard deviation of a variable from raw data

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Numerically Summarizing Data

Insert photo of cover

Objectives

• Compute the range of a variable from raw data

• Compute the variance of a variable from raw data

• Compute the standard deviation of a variable from raw data

• Use the Empirical Rule to describe data that are bell shaped

• Use Chebyshev’s Inequality to describe any data set

To order food at a McDonald’s Restaurant, one must choose from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

(a) What was the mean wait time?

(b) Draw a histogram of each restaurant’s wait time.

(c ) Which restaurant’s wait time appears more dispersed? Which line would you prefer to wait in? Why?

Wait Time at Wendy’s from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

1.50 0.79 1.01 1.66 0.94 0.67

2.53 1.20 1.46 0.89 0.95 0.90

1.88 2.94 1.40 1.33 1.20 0.84

3.99 1.90 1.00 1.54 0.99 0.35

0.90 1.23 0.92 1.09 1.72 2.00

Wait Time at McDonald’s

3.50 0.00 0.38 0.43 1.82 3.04

0.00 0.26 0.14 0.60 2.33 2.54

1.97 0.71 2.22 4.54 0.80 0.50

0.00 0.28 0.44 1.38 0.92 1.17

3.08 2.75 0.36 3.10 2.19 0.23

(a) The mean wait time in each line is 1.39 minutes. from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

(b) from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

Objective 1 from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

• Compute the range of a variable from raw data

The from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:range, R, of a variable is the difference between the largest data value and the smallest data values. That is

Range = R = Largest Data Value – Smallest Data Value

EXAMPLE from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:Finding the Range of a Set of Data

The following data represent the travel times (in minutes) to work for all seven employees of a start-up web development company.

23, 36, 23, 18, 5, 26, 43

Find the range.

Range = 43 – 5

= 38 minutes

Objective 2 from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

• Compute the variance of a variable from raw data

The from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:population variance of a variable is the sum of squared deviations about the population mean divided by the number of observations in the population, N.

That is it is the mean of the sum of the squared deviations about the population mean.

The from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:population variance is symbolically represented by σ2 (lower case Greek sigma squared).

Note: When using the above formula, do not round until the last computation. Use as many decimals as allowed by your calculator in order to avoid round off errors.

EXAMPLE from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:Computing a Population Variance

The following data represent the travel times (in minutes) to work for all seven employees of a start-up web development company.

23, 36, 23, 18, 5, 26, 43

Compute the population variance of this data. Recall that

minutes from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:2

The Computational Formula from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

EXAMPLE from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:Computing a Population VarianceUsing the Computational Formula

The following data represent the travel times (in minutes) to work for all seven employees of a start-up web development company.

23, 36, 23, 18, 5, 26, 43

Compute the population variance of this data using the computational formula.

23, 36, 23, 18, 5, 26, 43 from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

The from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:sample variance is computed by determining the sum of squared deviations about the sample mean and then dividing this result by n – 1.

Note: from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following: Whenever a statistic consistently overestimates or underestimates a parameter, it is called biased. To obtain an unbiased estimate of the population variance, we divide the sum of the squared deviations about the mean by n - 1.

EXAMPLE from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:Computing a Sample Variance

In Section 3.1, we obtained the following simple random sample for the travel time data: 5, 36, 26.

Compute the sample variance travel time.

square minutes

Objective 3 from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

• Compute the standard deviation of a variable from raw data

The from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:population standard deviation is denoted by

It is obtained by taking the square root of the population variance, so that

The sample standard deviation is denoted by

s

It is obtained by taking the square root of the sample variance, so that

EXAMPLE from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:Computing a Population Standard Deviation

The following data represent the travel times (in minutes) to work for all seven employees of a start-up web development company.

23, 36, 23, 18, 5, 26, 43

Compute the population standard deviation of this data.

Recall, from the last objective that σ2 = 129.0 minutes2.

Therefore,

EXAMPLE from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:Computing a Sample Standard Deviation

Recall the sample data 5, 26, 36 results in a sample variance of

square minutes

Use this result to determine the sample standard deviation.

EXAMPLE from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:Comparing Standard Deviations

Determine the standard deviation waiting time for Wendy’s and McDonald’s. Which is larger? Why?

Wait Time at Wendy’s from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

1.50 0.79 1.01 1.66 0.94 0.67

2.53 1.20 1.46 0.89 0.95 0.90

1.88 2.94 1.40 1.33 1.20 0.84

3.99 1.90 1.00 1.54 0.99 0.35

0.90 1.23 0.92 1.09 1.72 2.00

Wait Time at McDonald’s

3.50 0.00 0.38 0.43 1.82 3.04

0.00 0.26 0.14 0.60 2.33 2.54

1.97 0.71 2.22 4.54 0.80 0.50

0.00 0.28 0.44 1.38 0.92 1.17

3.08 2.75 0.36 3.10 2.19 0.23

EXAMPLE from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:Comparing Standard Deviations

Determine the standard deviation waiting time for Wendy’s and McDonald’s. Which is larger? Why?

Sample standard deviation for Wendy’s:

0.738 minutes

Sample standard deviation for McDonald’s:

1.265 minutes

Objective 4 from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

• Use the Empirical Rule to Describe Data That Are Bell Shaped

EXAMPLE from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:Using the Empirical Rule

The following data represent the serum HDL cholesterol of the 54 female patients of a family doctor.

41 48 43 38 35 37 44 44 44

62 75 77 58 82 39 85 55 54

67 69 69 70 65 72 74 74 74

60 60 60 61 62 63 64 64 64

54 54 55 56 56 56 57 58 59

45 47 47 48 48 50 52 52 53

(a) Compute the population mean and standard deviation. from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

(b) Draw a histogram to verify the data is bell-shaped.

(c) Determine the percentage of patients that have serum HDL within 3 standard deviations of the mean according to the Empirical Rule.

(d) Determine the percentage of patients that have serum HDL between 34 and 69.1 according to the Empirical Rule.

(e) Determine the actual percentage of patients that have serum HDL between 34 and 69.1.

(a) Using a TI83 plus graphing calculator, we find from multiple lines, while at Wendy’s Restaurant, one enters a single line. The following data represent the wait time (in minutes) in line for a simple random sample of 30 customers at each restaurant during the lunch hour. For each sample, answer the following:

(b)

22.3 34.0 45.7 57.4 69.1 80.8 92.5

(c) According to the Empirical Rule, 99.7% of the patients that have serum HDL within 3 standard deviations of the mean.

(d) 13.5% + 34% + 34% = 81.5% of patients will have a serum HDL between 34.0 and 69.1 according to the Empirical Rule.

(e) 45 out of the 54 or 83.3% of the patients have a serum HDL between 34.0 and 69.1.

Objective 5 69.1 80.8 92.5

• Use Chebyshev’s Inequality to Describe Any Set of Data

EXAMPLE 69.1 80.8 92.5Using Chebyshev’s Theorem

• Using the data from the previous example, use Chebyshev’s Theorem to

• determine the percentage of patients that have serum HDL within 3 standard deviations of the mean.

• (b) determine the actual percentage of patients that have serum HDL between 34 and 80.8.