How Can We Describe the Spread of Quantitative Data? 1.

Slides:



Advertisements
Similar presentations
DESCRIBING DISTRIBUTION NUMERICALLY
Advertisements

Describing Distributions With Numbers
EXPLORING DATA WITH GRAPHS AND NUMERICAL SUMMARIES
Lecture 4 Chapter 2. Numerical descriptors
Looking at data: distributions - Describing distributions with numbers IPS chapter 1.2 © 2006 W.H. Freeman and Company.
Measures of Dispersion or Measures of Variability
Chap 3-1 EF 507 QUANTITATIVE METHODS FOR ECONOMICS AND FINANCE FALL 2008 Chapter 3 Describing Data: Numerical.
MEASURES OF SPREAD – VARIABILITY- DIVERSITY- VARIATION-DISPERSION
Intro to Descriptive Statistics
Distribution Summaries Measures of central tendency Mean Median Mode Measures of spread Standard Deviation Interquartile Range (IQR)
BPS - 5th Ed. Chapter 21 Describing Distributions with Numbers.
Basic Practice of Statistics - 3rd Edition
July, 2000Guang Jin Statistics in Applied Science and Technology Chapter 4 Summarizing Data.
Chapter 2 Describing distributions with numbers. Chapter Outline 1. Measuring center: the mean 2. Measuring center: the median 3. Comparing the mean and.
Describing distributions with numbers
STATISTIC & INFORMATION THEORY (CSNB134) MODULE 2 NUMERICAL DATA REPRESENTATION.
1 Stat 1510 Statistical Thinking & Concepts Describing Distributions with Numbers.
1.3: Describing Quantitative Data with Numbers
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
Introduction - Standard Deviation. Journal Topic  A recent article says that teenagers send an average of 100 text messages per day. If I collected data.
Skewness & Kurtosis: Reference
Lecture 5 Dustin Lueker. 2 Mode - Most frequent value. Notation: Subscripted variables n = # of units in the sample N = # of units in the population x.
According to researchers, the average American guy is 31 years old, 5 feet 10 inches, 172 pounds, works 6.1 hours daily, and sleeps 7.7 hours. These numbers.
INVESTIGATION 1.
LECTURE CENTRAL TENDENCIES & DISPERSION POSTGRADUATE METHODOLOGY COURSE.
Chapter 3 Looking at Data: Distributions Chapter Three
Essential Statistics Chapter 21 Describing Distributions with Numbers.
How Can We Describe the Spread of Quantitative Data?
Review BPS chapter 1 Picturing Distributions with Graphs What is Statistics ? Individuals and variables Two types of data: categorical and quantitative.
Chapter 2 Describing Distributions with Numbers. Numerical Summaries u Center of the data –mean –median u Variation –range –quartiles (interquartile range)
BPS - 5th Ed. Chapter 21 Describing Distributions with Numbers.
Chapter 5: Measures of Dispersion. Dispersion or variation in statistics is the degree to which the responses or values obtained from the respondents.
Notes Unit 1 Chapters 2-5 Univariate Data. Statistics is the science of data. A set of data includes information about individuals. This information is.
Standard Deviation A Measure of Variation in a set of Data.
An article on peanut butter reported the following scores (quality ratings on a scale of 0 to 100) for various brands. Construct a comparative stem-and-leaf.
© 2008 McGraw-Hill Higher Education The Statistical Imagination Chapter 5. Measuring Dispersion or Spread in a Distribution of Scores.
Applied Quantitative Analysis and Practices LECTURE#07 By Dr. Osman Sadiq Paracha.
More Univariate Data Quantitative Graphs & Describing Distributions with Numbers.
Chapter 1: Exploring Data, cont. 1.2 Describing Distributions with Numbers Measuring Center: The Mean Most common measure of center Arithmetic average,
CHAPTER 2: Basic Summary Statistics
By Tatre Jantarakolica1 Fundamental Statistics and Economics for Evaluating Survey Data of Price Indices.
BPS - 5th Ed.Chapter 21 Describing Distributions with Numbers.
IPS Chapter 1 © 2012 W.H. Freeman and Company  1.1: Displaying distributions with graphs  1.2: Describing distributions with numbers  1.3: Density Curves.
© 2012 W.H. Freeman and Company Lecture 2 – Aug 29.
Chapter 5 Describing Distributions Numerically Describing a Quantitative Variable using Percentiles Percentile –A given percent of the observations are.
2.4 Measures of Variation The Range of a data set is simply: Range = (Max. entry) – (Min. entry)
Describe Quantitative Data with Numbers. Mean The most common measure of center is the ordinary arithmetic average, or mean.
Measures of Variation. Variation Variation describes how widely data values are spread out about the center of a distribution.
CHAPTER 1 Exploring Data
Stat 2411 Statistical Methods
CHAPTER 2: Describing Distributions with Numbers
CHAPTER 1 Exploring Data
The Practice of Statistics in the Life Sciences Fourth Edition
Lecture 2 Chapter 3. Displaying and Summarizing Quantitative Data
Numerical Descriptive Measures
1.2 Describing Distributions with Numbers
Chapter 2 Exploring Data with Graphs and Numerical Summaries
Data Analysis and Statistical Software I Quarter: Spring 2003
Honors Statistics Day 4 Objective: Students will be able to understand and calculate variances and standard deviations. As well as determine how to describe.
AP Statistics Day 5 Objective: Students will be able to understand and calculate variances and standard deviations.
Basic Practice of Statistics - 3rd Edition
Chapter 1 Warm Up .
Histograms and Measures of Center vs. Spread
Essential Statistics Describing Distributions with Numbers
Basic Practice of Statistics - 3rd Edition
CHAPTER 2: Basic Summary Statistics
The Five-Number Summary
Basic Practice of Statistics - 3rd Edition
Describing Distributions with Numbers
Numerical Descriptive Measures
Presentation transcript:

How Can We Describe the Spread of Quantitative Data? 1

 One way to measure the spread is to calculate the range. The range is the difference between the largest and smallest values in the data set; Range = max  min  The range is strongly affected by outliers 2

3  Each data value has an associated deviation from the mean,  A deviation is positive if it falls above the mean and negative if it falls below the mean  The sum of the deviations is always zero

4

 Gives a measure of variation by summarizing the deviations of each observation from the mean and calculating an adjusted average of these deviations 5

 Find the mean  Find the deviation of each value from the mean  Square the deviations  Sum the squared deviations  Divide the sum by n-1  Find the Square Root. 6

Metabolic rates of 7 men (cal./24hr.) :

ObservationsDeviationsSquared deviations  1600 = 192 (192) 2 = 36,  1600 = 66 (66) 2 = 4,  1600 = -238 (-238) 2 = 56,  1600 = 14 (14) 2 =  1600 = -140 (-140) 2 = 19,  1600 = 267 (267) 2 = 71,  1600 = -161 (-161) 2 = 25,921 sum = 0sum = 214,870 8

 s measures the spread of the data  s = 0 only when all observations have the same value, otherwise s > 0. As the spread of the data increases, s gets larger.  s has the same units of measurement as the original observations. The variance=s 2 has units that are squared  s is not resistant. Strong skewness or a few outliers can greatly increase s. 9

10