Descriptive Statistics Chapter 2. § 2.5 Measures of Position.

Slides:



Advertisements
Similar presentations
Statistics: 2.5 – Measures of Position
Advertisements

C. D. Toliver AP Statistics
Chapter 2 Exploring Data with Graphs and Numerical Summaries
Measures of Position - Quartiles
Descriptive Statistics
Chapter 13 Statistics © 2008 Pearson Addison-Wesley. All rights reserved.
Numerical Representation of Data Part 3 – Measure of Position
Section 2.5 Measures of Position.
BOX PLOTS/QUARTILES. QUARTILES: 3 points in a set of data that separate the set into 4 equal parts. Lower Quartile: Q1 (The median for the lower half.
Box and Whisker Plots and Quartiles Sixth Grade. Five Statistical Summary When describing a set of data we have seen that we can use measures such as.
Section 2.5 Measures of Position Larson/Farber 4th ed.
Descriptive Statistics
Section 2.5 Measures of Position.
Section 2.5 Measures of Position Larson/Farber 4th ed. 1.
Chapter 6 1. Chebychev’s Theorem The portion of any data set lying within k standard deviations (k > 1) of the mean is at least: 2 k = 2: In any data.
6-9 Data Distributions Objective Create and interpret box-and-whisker plots.
What is variability in data? Measuring how much the group as a whole deviates from the center. Gives you an indication of what is the spread of the data.
Section 3.3 Measures of Relative Position HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2008 by Hawkes Learning Systems/Quant Systems,
Chapter 1: Exploring Data Lesson 4: Quartiles, Percentiles, and Box Plots Mrs. Parziale.
Descriptive Statistics Chapter 2. § 2.5 Measures of Position.
Copyright © 2015, 2012, and 2009 Pearson Education, Inc. 1 Chapter Descriptive Statistics 2.
Quantitative data. mean median mode range  average add all of the numbers and divide by the number of numbers you have  the middle number when the numbers.
Percentiles For any whole number P (between 1 and 99), the Pth percentile of a distribution is a value such that P% of the data fall at or below it. The.
Chapter 2 Section 5 Notes Coach Bridges
Box and Whisker Plots Measures of Central Tendency.
Descriptive Statistics Chapter 2. § 2.5 Measures of Position.
Summary Statistics: Measures of Location and Dispersion.
Measures of Position. Determine the quartiles of a data set Determine the interquartile range of a data set Create a box-and-whisker plot Interpret.
Descriptive Statistics Chapter 2. § 2.5 Measures of Position.
Using Measures of Position (rather than value) to Describe Spread? 1.
Chapter 4 Histograms Stem-and-Leaf Dot Plots Measures of Central Tendency Measures of Variation Measures of Position.
Box Plots March 20, th grade. What is a box plot? Box plots are used to represent data that is measured and divided into four equal parts. These.
Foundations of Math I: Unit 3 - Statistics Arithmetic average Median: Middle of the data listed in ascending order (use if there is an outlier) Mode: Most.
Unit 4: Probability Day 4: Measures of Central Tendency and Box and Whisker Plots.
Introductory Statistics Lesson 2.5 A Objective: SSBAT find the first, second and third quartiles of a data set. SSBAT find the interquartile range of a.
Section 2.5 Measures of Position.
Unit 3: Averages and Variations Part 3 Statistics Mr. Evans.
5-Number Summary A 5-Number Summary is composed of the minimum, the lower quartile (Q1), the median (Q2), the upper quartile (Q3), and the maximum. These.
Warm Up Find the median of the following data set. Car accidents on Main and First street during the past 7 years
Chapter 4 Measures of Central Tendency Measures of Variation Measures of Position Dot Plots Stem-and-Leaf Histograms.
Chapter 1 Lesson 4 Quartiles, Percentiles, and Box Plots.
Probability & Statistics Box Plots. Describing Distributions Numerically Five Number Summary and Box Plots (Box & Whisker Plots )
Chapter 4 Histograms Stem-and-Leaf Dot Plots Measures of Central Tendency Measures of Variation Measures of Position.
a graphical presentation of the five-number summary of data
Chapter 2 Descriptive Statistics.
Find the lower and upper quartiles for the data set.
Measures of Position Section 2-6
Unit 2 Section 2.5.
10-3 Data Distributions Warm Up Lesson Presentation Lesson Quiz
Box and Whisker Plots Algebra 2.
Percentiles and Box-and- Whisker Plots
Numerical Measures: Skewness and Location
Measures of Position Quartiles Interquartile Range
Measures of Variation.
Chapter 2 Descriptive Statistics.
BOX-and-WHISKER PLOT (Box Plot)
The absolute value of each deviation.
Range between the quartiles. Q3 – Q1
Descriptive Statistics
Measures of Central Tendency
Box-And-Whisker Plots
Section 2.4 Measures of Variation.
Statistics and Data (Algebraic)
Box-and-Whisker Plots
Box-And-Whisker Plots
Box and Whisker Plots.
Box and Whisker Plots and the 5 number summary
BOX-and-WHISKER PLOT (Box Plot)
Statistics Vocab Notes
Box Plot Lesson 11-4.
Presentation transcript:

Descriptive Statistics Chapter 2

§ 2.5 Measures of Position

Larson & Farber, Elementary Statistics: Picturing the World, 3e 3 Quartiles The three quartiles, Q 1, Q 2, and Q 3, approximately divide an ordered data set into four equal parts. Median Q3Q3 Q2Q2 Q1Q1 Q 1 is the median of the data below Q 2. Q 3 is the median of the data above Q 2.

Larson & Farber, Elementary Statistics: Picturing the World, 3e 4 Finding Quartiles Example : The quiz scores for 15 students is listed below. Find the first, second and third quartiles of the scores Order the data Lower halfUpper half Q2Q2 Q1Q1 Q3Q3 About one fourth of the students scores 37 or less; about one half score 43 or less; and about three fourths score 48 or less.

Larson & Farber, Elementary Statistics: Picturing the World, 3e 5 Interquartile Range The interquartile range (IQR) of a data set is the difference between the third and first quartiles. Interquartile range (IQR) = Q 3 – Q 1. Example : The quartiles for 15 quiz scores are listed below. Find the interquartile range. (IQR) = Q 3 – Q 1 Q 2 = 43Q 3 = 48Q 1 = 37 = 48 – 37 = 11 The quiz scores in the middle portion of the data set vary by at most 11 points.

Larson & Farber, Elementary Statistics: Picturing the World, 3e 6 Box and Whisker Plot A box - and - whisker plot is an exploratory data analysis tool that highlights the important features of a data set. The five - number summary is used to draw the graph. The minimum entry Q 1 Q 2 (median) Q 3 The maximum entry Example : Use the data from the 15 quiz scores to draw a box - and - whisker plot. Continued

Larson & Farber, Elementary Statistics: Picturing the World, 3e 7 Box and Whisker Plot Five - number summary The minimum entry Q 1 Q 2 (median) Q 3 The maximum entry Quiz Scores

Larson & Farber, Elementary Statistics: Picturing the World, 3e 8 Percentiles and Deciles Fractiles are numbers that partition, or divide, an ordered data set. Percentiles divide an ordered data set into 100 parts. There are 99 percentiles : P 1, P 2, P 3 …P 99. Deciles divide an ordered data set into 10 parts. There are 9 deciles : D 1, D 2, D 3 …D 9. A test score at the 80th percentile (P 8 ), indicates that the test score is greater than 80% of all other test scores and less than or equal to 20% of the scores.

Larson & Farber, Elementary Statistics: Picturing the World, 3e 9 Standard Scores The standard score or z - score, represents the number of standard deviations that a data value, x, falls from the mean, μ. Example : The test scores for all statistics finals at Union College have a mean of 78 and standard deviation of 7. Find the z - score for a.) a test score of 85, b.) a test score of 70, c.) a test score of 78. Continued.

Larson & Farber, Elementary Statistics: Picturing the World, 3e 10 Standard Scores Example continued : a.) μ = 78, σ = 7, x = 85 This score is 1 standard deviation higher than the mean. b.) μ = 78, σ = 7, x = 70 This score is 1.14 standard deviations lower than the mean. c.) μ = 78, σ = 7, x = 78 This score is the same as the mean.

Larson & Farber, Elementary Statistics: Picturing the World, 3e 11 Relative Z-Scores Example: John received a 75 on a test whose class mean was 73.2 with a standard deviation of 4.5. Samantha received a 68.6 on a test whose class mean was 65 with a standard deviation of 3.9. Which student had the better test score? John’s z - scoreSamantha’s z - score John’s score was 0.4 standard deviations higher than the mean, while Samantha’s score was 0.92 standard deviations higher than the mean. Samantha’s test score was better than John’s.