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Slides Prepared by JOHN S. LOUCKS St. Edward’s University. Chapter 3 Descriptive Statistics: Numerical Methods, Part A. Measures of Location Measures of Variability. . . %. x. Measures of Location. Mean Median Mode Percentiles Quartiles. Example: Apartment Rents.

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Slides Prepared by JOHN S. LOUCKS St. Edward’s University

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Slides prepared by john s loucks st edward s university

Slides Prepared by

JOHN S. LOUCKS

St. Edward’s University


Chapter 3 descriptive statistics numerical methods part a

Chapter 3 Descriptive Statistics: Numerical Methods, Part A

  • Measures of Location

  • Measures of Variability

%

x


Measures of location

Measures of Location

  • Mean

  • Median

  • Mode

  • Percentiles

  • Quartiles


Example apartment rents

Example: Apartment Rents

Given below is a sample of monthly rent values ($)

for one-bedroom apartments. The data is a sample of 70

apartments in a particular city. The data are presented

in ascending order.


Slides prepared by john s loucks st edward s university

Mean

  • The mean of a data set is the average of all the data values.

  • If the data are from a sample, the mean is denoted by

    .

  • If the data are from a population, the mean is denoted by m (mu).


Example apartment rents1

Example: Apartment Rents

  • Mean


Median

Median

  • The median is the measure of location most often reported for annual income and property value data.

  • A few extremely large incomes or property values can inflate the mean.


Median1

Median

  • The median of a data set is the value in the middle when the data items are arranged in ascending order.

  • For an odd number of observations, the median is the middle value.

  • For an even number of observations, the median is the average of the two middle values.


Example apartment rents2

Example: Apartment Rents

  • Median

    Median = 50th percentile

    i = (p/100)n = (50/100)70 = 35.5 Averaging the 35th and 36th data values:

    Median = (475 + 475)/2 = 475


Slides prepared by john s loucks st edward s university

Mode

  • The mode of a data set is the value that occurs with greatest frequency.

  • The greatest frequency can occur at two or more different values.

  • If the data have exactly two modes, the data are bimodal.

  • If the data have more than two modes, the data are multimodal.


Example apartment rents3

Example: Apartment Rents

  • Mode

    450 occurred most frequently (7 times)

    Mode = 450


Using excel to compute the mean median and mode

Using Excel to Computethe Mean, Median, and Mode

  • Formula Worksheet

Note: Rows 7-71 are not shown.


Using excel to compute the mean median and mode1

Using Excel to Computethe Mean, Median, and Mode

  • Value Worksheet

Note: Rows 7-71 are not shown.


Percentiles

Percentiles

  • A percentile provides information about how the data are spread over the interval from the smallest value to the largest value.

  • Admission test scores for colleges and universities are frequently reported in terms of percentiles.


Percentiles1

Percentiles

  • The pth percentile of a data set is a value such that at least p percent of the items take on this value or less and at least (100 - p) percent of the items take on this value or more.

    • Arrange the data in ascending order.

    • Compute index i, the position of the pth percentile.

      i = (p/100)n

    • If i is not an integer, round up. The pth percentile is the value in the ith position.

    • If i is an integer, the pth percentile is the average of the values in positions i and i+1.


Example apartment rents4

Example: Apartment Rents

  • 90th Percentile

    i = (p/100)n = (90/100)70 = 63

    Averaging the 63rd and 64th data values:

    90th Percentile = (580 + 590)/2 = 585


Quartiles

Quartiles

  • Quartiles are specific percentiles

  • First Quartile = 25th Percentile

  • Second Quartile = 50th Percentile = Median

  • Third Quartile = 75th Percentile


Example apartment rents5

Example: Apartment Rents

  • Third Quartile

    Third quartile = 75th percentile

    i = (p/100)n = (75/100)70 = 52.5 = 53

    Third quartile = 525


Using excel to compute percentiles and quartiles

Using Excel to ComputePercentiles and Quartiles

  • Unsorted Monthly Rent ($)

Note: Rows 7-71 are not shown.


Using excel to compute percentiles and quartiles1

Using Excel to ComputePercentiles and Quartiles

  • Sorting Data

    Step 1 Select any cell containing data in column B

    Step 2 Select the Data pull-down menu

    Step 3 Choose the Sort option

    Step 4 When the Sort dialog box appears:

    In the Sort by box, make sure that Monthly Rent ($) appears and that Ascending is selected

    In the My list has box, make sure that Header row is selected

    Click OK


Using excel to compute percentiles and quartiles2

Using Excel to ComputePercentiles and Quartiles

  • Sorted Monthly Rent ($)

Note: Rows 7-71 are not shown.


Using excel to compute percentiles and quartiles3

Using Excel to ComputePercentiles and Quartiles

  • Formula Worksheet for 90th Percentile’s Index

Note: Rows 7-71 are not shown.


Using excel to compute percentiles and quartiles4

Using Excel to ComputePercentiles and Quartiles

  • Value Worksheet for 90th Percentile’s Index

Note: Rows 7-71 are not shown.


Using excel to compute percentiles and quartiles5

Using Excel to ComputePercentiles and Quartiles

  • Value Worksheet for 3rd Quartile’s Index

Note: Rows 7-71 are not shown.


Measures of variability

Measures of Variability

  • It is often desirable to consider measures of variability (dispersion), as well as measures of location.

  • For example, in choosing supplier A or supplier B we might consider not only the average delivery time for each, but also the variability in delivery time for each.


Measures of variability1

Measures of Variability

  • Range

  • Interquartile Range

  • Variance

  • Standard Deviation

  • Coefficient of Variation


Range

Range

  • The range of a data set is the difference between the largest and smallest data values.

  • It is the simplest measure of variability.

  • It is very sensitive to the smallest and largest data values.


Example apartment rents6

Example: Apartment Rents

  • Range

    Range = largest value - smallest value

    Range = 615 - 425 = 190


Interquartile range

Interquartile Range

  • The interquartile range of a data set is the difference between the third quartile and the first quartile.

  • It is the range for the middle 50% of the data.

  • It overcomes the sensitivity to extreme data values.


Example apartment rents7

Example: Apartment Rents

  • Interquartile Range

    3rd Quartile (Q3) = 525

    1st Quartile (Q1) = 445

    Interquartile Range = Q3 - Q1 = 525 - 445 = 80


Variance

Variance

  • The variance is a measure of variability that utilizes all the data.

  • It is based on the difference between the value of each observation (xi) and the mean (x for a sample, m for a population).


Variance1

Variance

  • The variance is the average of the squared differences between each data value and the mean.

  • If the data set is a sample, the variance is denoted by s2.

  • If the data set is a population, the variance is denoted by  2.


Standard deviation

Standard Deviation

  • The standard deviation of a data set is the positive square root of the variance.

  • It is measured in the same units as the data, making it more easily comparable, than the variance, to the mean.

  • If the data set is a sample, the standard deviation is denoted s.

  • If the data set is a population, the standard deviation is denoted  (sigma).


Coefficient of variation

Coefficient of Variation

  • The coefficient of variation indicates how large the standard deviation is in relation to the mean.

  • If the data set is a sample, the coefficient of variation is computed as follows:

  • If the data set is a population, the coefficient of variation is computed as follows:


Example apartment rents8

Example: Apartment Rents

  • Variance

  • Standard Deviation

  • Coefficient of Variation


Using excel to compute the sample variance standard deviation and coefficient of variation

Using Excel to Compute the Sample Variance, Standard Deviation, and Coefficient of Variation

  • Formula Worksheet

Note: Rows 8-71 are not shown.


Using excel to compute the sample variance standard deviation and coefficient of variation1

Using Excel to Compute the Sample Variance, Standard Deviation, and Coefficient of Variation

  • Value Worksheet

Note: Rows 8-71 are not shown.


Using excel s descriptive statistics tool

Using Excel’sDescriptive Statistics Tool

Step 1 Select the Tools pull-down menu

Step 2 Choose the Data Analysis option

Step 3 Choose Descriptive Statistics from the list of

Analysis Tools

… continued


Using excel s descriptive statistics tool1

Using Excel’sDescriptive Statistics Tool

Step 4 When the Descriptive Statistics dialog box appears:

Enter B1:B71 in the Input Range boxSelect Grouped By Columns

Select Labels in First Row

Select Output Range

Enter D1 in the Output Range box

Select Summary Statistics

Click OK


Using excel s descriptive statistics tool2

Using Excel’sDescriptive Statistics Tool

  • Value Worksheet (Partial)

Note: Rows 9-71 are not shown.


Using excel s descriptive statistics tool3

Using Excel’sDescriptive Statistics Tool

  • Value Worksheet (Partial)

Note: Rows 1-8 and 17-71 are not shown.


End of chapter 3 part a

End of Chapter 3, Part A


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