3.4 - 1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics...
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![Page 1: 3.4 - 1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.](https://reader035.fdocuments.net/reader035/viewer/2022062300/56649d825503460f94a67dc7/html5/thumbnails/1.jpg)
3.4 - 1Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Lecture Slides
Elementary Statistics Eleventh Edition
and the Triola Statistics Series
by Mario F. Triola
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3.4 - 2Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Chapter 3Statistics for Describing,
Exploring, and Comparing Data
3-1 Review and Preview
3-2 Measures of Center
3-3 Measures of Variation
3-4 Measures of Relative Standing and Boxplots
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3.4 - 3Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Section 3-4Measures of Relative
Standing and Boxplots
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3.4 - 4Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Key Concept
This section introduces measures of relative standing, which are numbers showing the location of data values relative to the other values within a data set. They can be used to compare values from different data sets, or to compare values within the same data set. The most important concept is the z score. We will also discuss percentiles and quartiles, as well as a new statistical graph called the boxplot.
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3.4 - 5Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Basics of z Scores, Percentiles, Quartiles, and
Boxplots
Part 1
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3.4 - 6Copyright © 2010, 2007, 2004 Pearson Education, Inc.
z Score (or standardized value)
the number of standard deviations that a given value x is above or
below the mean
Z score
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3.4 - 7Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Sample Population
x – µz =
Round z scores to 2 decimal places
Measures of Position z Score
z = x – xs
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3.4 - 8Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Interpreting Z Scores
Whenever a value is less than the mean, its corresponding z score is negative
Ordinary values: –2 ≤ z score ≤ 2
Unusual Values: z score < –2 or z score > 2
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3.4 - 9Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Percentiles
are measures of location. There are 99 percentiles denoted P1, P2, . . . P99, which divide a set of data into 100 groups with about 1% of the values in each group.
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3.4 - 10Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Finding the Percentile of a Data Value
Percentile of value x = • 100
Do problems 17-28 on page 125
number of values less than x
total number of values
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3.4 - 11Copyright © 2010, 2007, 2004 Pearson Education, Inc.
n total number of values in the data set
k percentile being used
L locator that gives the position of a value
Pk kth percentile
L = • nk100
Notation
Converting from the kth Percentile to the Corresponding Data Value
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3.4 - 12Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Converting from the kth Percentile to the
Corresponding Data Value
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3.4 - 13Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Quartiles
Q1 (First Quartile) separates the bottom 25% of sorted values from the top 75%.
Q2 (Second Quartile) same as the median; separates the bottom 50% of sorted values from the top 50%.
Q3 (Third Quartile) separates the bottom 75% of sorted values from the top 25%.
Are measures of location, denoted Q1, Q2, and Q3, which divide a set of data into four groups with about 25% of the values in each group.
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3.4 - 14Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Q1, Q2, Q3 divide ranked scores into four equal parts
Quartiles
25% 25% 25% 25%
Q3Q2Q1(minimum) (maximum)
(median)
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3.4 - 15Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Interquartile Range (or IQR): Q3 – Q1
10 - 90 Percentile Range: P90 – P10
Semi-interquartile Range:2
Q3 – Q1
Midquartile:2
Q3 + Q1
Some Other Statistics
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3.4 - 16Copyright © 2005 Pearson Education, Inc.Slide 6-16
Why Variation Matters6-B
Big Bank (three line wait times):4.1 5.2 5.6 6.2 6.7 7.2 7.7 7.7 8.5 9.3 11.0
Best Bank (one line wait times):6.6 6.7 6.7 6.9 7.1 7.2 7.3 7.4 7.7 7.8 7.8
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3.4 - 17Copyright © 2005 Pearson Education, Inc.Slide 6-17
Five Number Summaries & Box Plots
6-B
lower quartile = 5.6
high value (max) = 7.8upper quartile = 7.7
median = 7.2lower quartile = 6.7
low value (min) = 6.6
Best BankBig Bank
high value (max) = 11.0
low value (min) = 4.1
upper quartile = 8.5median = 7.2
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3.4 - 18Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Boxplots - Normal Distribution
Normal Distribution:Heights from a Simple Random Sample of Women
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3.4 - 19Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Boxplots - Skewed Distribution
Skewed Distribution:Salaries (in thousands of dollars) of NCAA Football Coaches
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3.4 - 20Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Outliers andModified Boxplots
Part 2
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3.4 - 21Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Outliers
An outlier is a value that lies very far away from the vast majority of the other
values in a data set.
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3.4 - 22Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Important Principles
An outlier can have a dramatic effect on the mean.
An outlier can have a dramatic effect on the standard deviation.
An outlier can have a dramatic effect on the scale of the histogram so that the true nature of the distribution is totally obscured.
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3.4 - 23Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Outliers for Modified Boxplots
For purposes of constructing modified boxplots, we can consider outliers to be data values meeting specific criteria.
In modified boxplots, a data value is an outlier if it is . . .
Data > Q3 + 1.5 IQR
Data < Q1 - 1.5 IQRor
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3.4 - 24Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Modified Boxplots
Boxplots described earlier are called skeletal (or regular) boxplots.
Some statistical packages provide modified boxplots which represent outliers as special points.
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3.4 - 25Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Modified Boxplot Construction
A special symbol (such as an asterisk) is used to identify outliers.
The solid horizontal line extends only as far as the minimum data value that is not an outlier and the maximum data value that is not an outlier.
A modified boxplot is constructed with these specifications:
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3.4 - 26Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Modified Boxplots - Example
Pulse rates of females listed in Data Set 1 in Appendix B.
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3.4 - 27Copyright © 2010, 2007, 2004 Pearson Education, Inc.
RecapIn this section we have discussed: z Scores z Scores and unusual values
Quartiles
Percentiles
Converting a percentile to corresponding data values
Other statistics
Effects of outliers
5-number summary Boxplots and modified boxplots
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3.4 - 28Copyright © 2010, 2007, 2004 Pearson Education, Inc.
Putting It All TogetherAlways consider certain key factors: Context of the data Source of the data
Measures of Center
Sampling Method
Measures of Variation
Outliers
Practical Implications
Changing patterns over time Conclusions
Distribution