Chapter Two Describing Location in a Distribution.

Slides:



Advertisements
Similar presentations
Describing Location in a Distribution 2.1 Measures of Relative Standing and Density Curves YMS3e AP Stats at LSHS Mr. Molesky 2.1 Measures of Relative.
Advertisements

2.1 Describing Location in a Distribution. Measuring Position: Percentiles One way to describe the location of a value in a distribution is to tell what.
Standard Normal Calculations 2.2 b cont. Target Goal: I can standardize individual values and compare them using a common scale Hw: pg 105: 13 – 15, pg.
Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 3 Introduction – Slide 1 of 3 Topic 17 Standard Deviation, Z score, and Normal.
20, 22, 23, 24, 24, 25, 25, 27, 35 Are there any outliers? Draw a skeleton boxplot. Draw a modified boxplot.
Chapter 2: The Normal Distribution
12.4 – Measures of Position In some cases, the analysis of certain individual items in the data set is of more interest rather than the entire set. It.
Chapter 2: Modeling Distributions of Data
AP Statistics: Section 2.1 A. Measuring Relative Standing: z-scores A z-score describes a particular data value’s position in relation to the rest of.
Using the Empirical Rule. Normal Distributions These are special density curves. They have the same overall shape  Symmetric  Single-Peaked  Bell-Shaped.
INTRODUCTORY STATISTICS Chapter 2 DESCRIPTIVE STATISTICS PowerPoint Image Slideshow.
Describing Location in a Distribution. Measuring Position: Percentiles Here are the scores of 25 students in Mr. Pryor’s statistics class on their first.
Review Measures of central tendency
A z-score is directional. The absolute value of z tells you how many standard deviations the score is from the mean. The sign of z tells you whether.
Standard Normal Calculations. What you’ll learn  Properties of the standard normal dist n  How to transform scores into normal dist n scores  Determine.
Z Scores. Normal vs. Standard Normal Standard Normal Curve: Most normal curves are not standard normal curves They may be translated along the x axis.
Chapter 6 The Normal Curve. A Density Curve is a curve that: *is always on or above the horizontal axis *has an area of exactly 1 underneath it *describes.
Describing Location in a Distribution 2.1 Measures of Relative Standing and Density Curves 2.1 Measures of Relative Standing and Density Curves Text.
Think about this…. If Jenny gets an 86% on her first statistics test, should she be satisfied or disappointed? Could the scores of the other students in.
Thinking Mathematically Statistics: 12.5 Problem Solving with the Normal Distribution.
+ Chapter 2: Modeling Distributions of Data Section 2.1 Describing Location in a Distribution The Practice of Statistics, 4 th edition - For AP* STARNES,
Copyright © 2006 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide 6- 1.
 z – Score  Percentiles  Quartiles  A standardized value  A number of standard deviations a given value, x, is above or below the mean  z = (score.
Describing Location in a Distribution Chapter 2. 1.Explain what is meant by a standardized value. 2. Compute the z-score of an observation given the mean.
Density Curves Section 2.1. Strategy to explore data on a single variable Plot the data (histogram or stemplot) CUSS Calculate numerical summary to describe.
Using the Empirical Rule. Normal Distributions These are special density curves. They have the same overall shape  Symmetric  Single-Peaked  Bell-Shaped.
Measures of Relative Standing and Density Curves
Chapter 4 & 5 The Normal Curve & z Scores.
5, 8, 13, 17, 22, 24, 25, 27, 29, 30. 8, 10, 22, 24, 25, 25, 26, 27, 45, 72 Graph & Describe.
Chapter 3.3 Measures of Position. Standard Score  A comparison that uses the mean and standard deviation is called a standard score or a z-score  A.
+ Chapter 2: Modeling Distributions of Data Section 2.2 Normal Distributions The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE.
Dr. Fowler  AFM  Unit 8-4 The Normal Distribution
ECON 338/ENVR 305 CLICKER QUESTIONS Statistics – Question Set #2 (from Chapter2)
Organizing Data AP Stats Chapter 1. Organizing Data Categorical Categorical Dotplot (also used for quantitative) Dotplot (also used for quantitative)
Chapter 2 Modeling Distributions of Data Objectives SWBAT: 1)Find and interpret the percentile of an individual value within a distribution of data. 2)Find.
Describing Location in a Distribution 2.1 Measures of Relative Standing and Density Curves YMS3e.
Modeling Distributions of Data Describing location in a distribution Chapter 2.1.
Chapter 3 The Normal Distributions. Chapter outline 1. Density curves 2. Normal distributions 3. The rule 4. The standard normal distribution.
+ Chapter 2: Modeling Distributions of Data Section 2.1 Describing Location in a Distribution The Practice of Statistics, 4 th edition - For AP* STARNES,
SWBAT: Use percentiles to locate individual values within distributions of data. Interpret a cumulative relative frequency graph. Find the standardized.
+ Chapter 2: Modeling Distributions of Data Section 2.2 Normal Distributions The Practice of Statistics, 4 th edition - For AP* STARNES, YATES, MOORE.
Chapter 5 The Standard Deviation as a Ruler and the Normal Model.
Modeling Distributions
Case Closed The New SAT Chapter 2 AP Stats at LSHS Mr. Molesky The New SAT Chapter 2 AP Stats at LSHS Mr. Molesky.
Chapter 3 Modeling Distributions of Data Page 101.
Chapter 3.3 – 3.4 Applications of the Standard Deviation and Measures of Relative Standing.
Describing Location in a Distribution The pth percentile is the value with p percent of the observations LESS than it. (Alternate wording: p percent of.
Daniel S. Yates The Practice of Statistics Third Edition Chapter 2: Describing Location in a Distribution Copyright © 2008 by W. H. Freeman & Company.
 2.1 Measures of Relative Standing and Density Curves.
 By the end of this section, you should be able to: › Find and interpret the percentile of an individual value within a distribution of data. › Estimate.
Modeling Distributions of Data
CHAPTER 2 Modeling Distributions of Data
Chapter 6 The Normal Curve.
2.1 Describing Location in a Distribution
Using the Empirical Rule
Describing Location in a Distribution
Describing Location in a Distribution
Analyzing One-Variable Data
Describing Location in a Distribution
Standard Normal Calculations 2.2 b cont.
Descriptive Statistics
Measuring location: percentiles
The Normal Distribution
Chapter 2: Modeling Distributions of Data
Describing Location in a Distribution
CHAPTER 2 Modeling Distributions of Data
MBA 510 Lecture 2 Spring 2013 Dr. Tonya Balan 4/20/2019.
2.1 Measures of Relative Standing
The Practice of Statistics
Describing Location in a Distribution
Presentation transcript:

Chapter Two Describing Location in a Distribution

 P ,3  P ,7

 Standardized Score (z-score) – number of standard deviation from mean  Percentile – the pth percentile of a distribution is the data value with p percent of the observations below it. There is no 100 th percentile.

 Jenny scored an 86 on a statistics test that had a mean of 80 and a standard deviation of She also scored an 82 on a chemistry test that had a mean of 76 and a standard deviation of four. She was six points the mean in each case.  Calculate her z-score for each test.  Relative to other members of the classes, which test did she do better on?

 Jenny’s score is the 22 nd highest of 25 scores counting from the lowest to the highest. What percentile is her score?

 The landmarks of baseball achievement are T Cobb’s batting average of.420 in 1911, Ted William’s.406 in 1941, and George Brett’s.390 in These batting averages cannot be compared directly because the distribution of major league batting averages has changed over the years. The distributions are quite symmetric, except for outliers such as Cobb, Williams, and Brett. While the mean batting average has been held roughly constant by rule changes and the balance between hitting and pitching, the standard deviation has dropped over time. Here are the facts: Decade Mean Standard Deviation  1910s  1940s  1970S  Compute the standardized batting averages for Cobb, Williams, and Brett to compare how far each stood above his peers.

Number of Standard Deviations CalculationPercent of Data within this number of standard deviations of the mean 1standard deviation 2 standard deviations 3 standard deviations 4 standard deviations Make a Table Showing Results of Chebyshev’s Inequality