Seminar Eight Individual Z-Scores and Z-Score Patterns Caitlin Crawford September 20, 2007.

Slides:



Advertisements
Similar presentations
Completing the Square and the Quadratic Formula
Advertisements

Describing Quantitative Variables
DESCRIBING DISTRIBUTION NUMERICALLY
Histograms! Histograms group data that is close together into “classes” and shows how many or what percentage of the data fall into each “class”. It.
T-3 Histograms. Histogram Basics A histogram is a special type of bar graph that measures the frequency of data Horizontal axis: represents values in.
Discrete Random Variables
Agricultural and Biological Statistics
EXPLORING DATA WITH GRAPHS AND NUMERICAL SUMMARIES
2- 1 Chapter Two McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.
Histograms. Definition of a Histogram A Histogram displays a range of values of a variable that have been broken into groups or intervals. Histograms.
Histogram Most common graph of the distribution of one quantitative variable.
Measures of Variability or Dispersion Range - high and lows. –Limitations: Based on only two extreme observations Interquartile range - measures variablility.
Statistics for Decision Making Descriptive Statistics QM Fall 2003 Instructor: John Seydel, Ph.D.
QM Spring 2002 Statistics for Decision Making Descriptive Statistics.
Variability Measures of spread of scores range: highest - lowest standard deviation: average difference from mean variance: average squared difference.
B a c kn e x t h o m e Classification of Variables Discrete Numerical Variable A variable that produces a response that comes from a counting process.
CHAPTER 1: Picturing Distributions with Graphs
Descriptive Statistics  Summarizing, Simplifying  Useful for comprehending data, and thus making meaningful interpretations, particularly in medium to.
Descriptive Statistics
2.1: Frequency Distributions and Their Graphs. Is a table that shows classes or intervals of data entries with a count of the number of entries in each.
Objective To understand measures of central tendency and use them to analyze data.
Descriptive Statistics  Summarizing, Simplifying  Useful for comprehending data, and thus making meaningful interpretations, particularly in medium to.
2- 1 Chapter Two McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc., All Rights Reserved.
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation Chapter 3.
Sect. 2-1 Frequency Distributions and Their graphs
1 DATA DESCRIPTION. 2 Units l Unit: entity we are studying, subject if human being l Each unit/subject has certain parameters, e.g., a student (subject)
Variable  An item of data  Examples: –gender –test scores –weight  Value varies from one observation to another.
Copyright (c) 2004 Brooks/Cole, a division of Thomson Learning, Inc. Chapter 1 Overview and Descriptive Statistics.
© 2008 Brooks/Cole, a division of Thomson Learning, Inc. 1 Chapter 4 Numerical Methods for Describing Data.
Table of Contents 1. Standard Deviation
Chapter 2 Describing Data.
Chapter 3 Numerically Summarizing Data 3.2 Measures of Dispersion.
Skewness & Kurtosis: Reference
EXPLORING DATA LESSON 1 – 1 Day 2 Displaying Distributions with Graphs Displaying quantitative variables.
MDM4U Chapter 3 Review Normal Distribution Mr. Lieff.
GOAL: DISPLAY DATA IN FREQUENCY DISTRIBUTIONS AND HISTOGRAMS Section 1-8: Frequency Distributions and Histograms.
Educ 200C Wed. Oct 3, Variation What is it? What does it look like in a data set?
1 Chapter 4 Numerical Methods for Describing Data.
Descriptive Statistics Review – Chapter 14. Data  Data – collection of numerical information  Frequency distribution – set of data with frequencies.
©The McGraw-Hill Companies, Inc. 2008McGraw-Hill/Irwin Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation Chapter 2.
Statistical analysis and graphical representation In Psychology, the data we have collected (raw data) does not really tell us anything therefore we need.
Descriptive Statistics for one Variable. Variables and measurements A variable is a characteristic of an individual or object in which the researcher.
Descriptive Statistics Unit 6. Variable Any characteristic (data) recorded for the subjects of a study ex. blood pressure, nesting orientation, phytoplankton.
Chapter ( 2 ) Strategies for understanding the meanings of Data : Learning outcomes Understand how data can be appropriately organized and displayed Understand.
Chapter 3 Review MDM 4U Mr. Lieff. 3.1 Graphical Displays be able to effectively use a histogram name and be able to interpret the various types of distributions.
A histogram is a special type of bar graph used to display numerical data that has been organized into intervals. The heights of the bars show the number.
Measures of Variation. Range, Variance, & Standard Deviation.
S D.. In probability and statistics, the standard deviation is the most common measure of statistical dispersion. Simply put, standard deviation measures.
Chapter 1 Lesson 7 Variance and Standard Deviation.
Graphing options for Quantitative Data
Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation Chapter 2.
CHAPTER 1 Exploring Data
Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation Chapter 2.
Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation Chapter 2.
DAY 3 Sections 1.2 and 1.3.
Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation Chapter 2.
Displaying Distributions with Graphs
Displaying and Summarizing Quantitative Data
Sexual Activity and the Lifespan of Male Fruitflies
POPULATION VS. SAMPLE Population: a collection of ALL outcomes, responses, measurements or counts that are of interest. Sample: a subset of a population.
Basic Practice of Statistics - 3rd Edition
Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation Chapter 2.
Basic Practice of Statistics - 3rd Edition
Descriptive Statistics
Descriptive Statistics
Displaying Quantitative Data
Descriptive Statistics
Histograms.
Frequency Distributions
Describing Data: Frequency Tables, Frequency Distributions, and Graphic Presentation Chapter 2.
Presentation transcript:

Seminar Eight Individual Z-Scores and Z-Score Patterns Caitlin Crawford September 20, 2007

Calculating Z-Scores All female heights have mean 65 and standard deviation 2.5 All male heights have mean 70 and standard deviation 3 Formula: z=(x-µ)/σ In other words, the mean subtracted from your value, divided by the standard deviation

Constructing a Histogram A histogram display values of a quantitative variable with vertical bars showing the count of values in certain interval ranges. Steps: 1.Divide range of data into intervals of equal width 2.Find the count of observations in each interval. 3.Draw the histogram, using the horizontal axis for range of data and vertical axis for count

Commenting on Histogram Are there large negative or positive z-scores? What percentage of z-scores are less than 1, 2, or 3? - 68% of z-scores are between 1 and % of z-scores are between 2 and % of z-scores are between 3 and -3 Do our results conform to rule? Would results differ for a larger class?

Example Two How many minutes (to the nearest 10 minutes) did you spend doing homework yesterday?

Calculating Mean and Standard Deviation Steps for calculating by hand: 1.Find the mean (add up all the numbers and divide by how many there are) 2.Find the deviations from the mean 3.Find the squared deviations from the mean 4.“Average” the squared deviations, dividing their sum by the number of observations-1 5.Take the square root of the variance to find the standard deviation

Calculating Z-Scores Use a calculator to find your individual z-score Formula: z=(x-µ)/σ In other words, the mean subtracted from your value, divided by the standard deviation

Constructing a Histogram A histogram display values of a quantitative variable with vertical bars showing the count of values in certain interval ranges. Steps: 1.Divide range of data into intervals of equal width 2.Find the count of observations in each interval. 3.Draw the histogram, using the horizontal axis for range of data and vertical axis for count

Commenting on Histogram Are there large negative or positive z-scores? What percentage of z-scores are less than 1, 2, or 3? - 68% of z-scores are between 1 and % of z-scores are between 2 and % of z-scores are between 3 and -3 Do our results conform to rule? Would results differ for a larger class?

Example Three How many hours of sleep did you get last night? -Please round to the nearest half hour

Calculating Mean and Standard Deviation Steps for calculating by hand: 1.Find the mean (add up all the numbers and divide by how many there are) 2.Find the deviations from the mean 3.Find the squared deviations from the mean 4.“Average” the squared deviations, dividing their sum by the number of observations-1 5.Take the square root of the variance to find the standard deviation

Calculating Z-Scores Use a calculator to find your individual z-score Formula: z=(x-µ)/σ In other words, the mean subtracted from your value, divided by the standard deviation

Constructing a Histogram A histogram display values of a quantitative variable with vertical bars showing the count of values in certain interval ranges. Steps: 1.Divide range of data into intervals of equal width 2.Find the count of observations in each interval. 3.Draw the histogram, using the horizontal axis for range of data and vertical axis for count

Commenting on Histogram Are there large negative or positive z-scores? What percentage of z-scores are less than 1, 2, or 3? - 68% of z-scores are between 1 and % of z-scores are between 2 and % of z-scores are between 3 and -3 Do our results conform to rule? Would results differ for a larger class?

The End Thanks for your participation!