Shape of Normal Curves. 68%-95%-99.7% Rule Areas under Normal Curve.

Slides:



Advertisements
Similar presentations
Chapter 5 Some Key Ingredients for Inferential Statistics: The Normal Curve, Probability, and Population Versus Sample.
Advertisements

Chapter 2: The Normal Distributions
Z-Scores are measurements of how far from the center (mean) a data value falls. Ex: A man who stands 71.5 inches tall is 1 standard deviation ABOVE the.
Normal and Standard Normal Distributions June 29, 2004.
THE STANDARD NORMAL Unit 5, Day 3. Learning Goals for Today I can state the difference between a Normal Distribution and a Standard Normal Distribution.
Calculations in the Bivariate Normal Distribution James H. Steiger.
Normal distribution. An example from class HEIGHTS OF MOTHERS CLASS LIMITS(in.)FREQUENCY
Module 7 Percent Area and the Normal Curve What it is History Uses 1.
Homework for 2.1 Day 1: 41, 43, 45, 47, 49, 51. 1) To use the rule to estimate the percent of observations from a Normal Distribution that.
The Normal Curve Z Scores, T Scores, and Skewness.
Z - SCORES standard score: allows comparison of scores from different distributions z-score: standard score measuring in units of standard deviations.
S519: Evaluation of Information Systems
The Normal Distributions
Unit 5 Data Analysis.
Quiz 5 Normal Probability Distribution.
Examples of continuous probability distributions: The normal and standard normal.
Continuous Probability Distributions
Density Curves and the Normal Distribution
The Normal Distribution James H. Steiger. Types of Probability Distributions There are two fundamental types of probability distributions Discrete Continuous.
Chapter 12 – Probability and Statistics 12.7 – The Normal Distribution.
Normal Distribution Section 2.2. Objectives  Introduce the Normal Distribution  Properties of the Standard Normal Distribution  Use Normal Distribution.
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.
The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 2 Modeling Distributions of Data 2.2 Density.
Normal Curves and Sampling Distributions Chapter 7.
Probability.  Provides a basis for thinking about the probability of possible outcomes  & can be used to determine how confident we can be in an effect.
© 2010 Pearson Prentice Hall. All rights reserved. CHAPTER 12 Statistics.
5.1 Introduction to Normal Distributions and the Standard Normal Distribution Important Concepts: –Normal Distribution –Standard Normal Distribution –Finding.
Meta-Study. Representation of the Sampling Distribution of Y̅
Produced by MEI on behalf of OCR © OCR 2013 Introduction to Quantitative Methods Statistical Problem Solving Normal distribution summary Notes for students.
Introduction to the Normal Distribution (Dr. Monticino)
Discrete and Continuous Random Variables. Yesterday we calculated the mean number of goals for a randomly selected team in a randomly selected game.
Modeling Distributions
Copyright ©2005 Brooks/Cole, a division of Thomson Learning, Inc. Bell-Shaped Curves and Other Shapes Chapter 8.
The Standard Normal Distribution Section Starter Weights of adult male Norwegian Elkhounds are N(42, 2) pounds. What weight would represent the.
STA Lecture 151 STA 291 Lecture 15 – Normal Distributions (Bell curve)
+ Unit 4 – Normal Distributions Week 9 Ms. Sanchez.
Normal Distribution S-ID.4 Use the mean and standard deviation of a data set to fit it to a normal distribution and to estimate population percentages.
Chapter 131 Normal Distributions. Chapter 132 Thought Question 2 What does it mean if a person’s SAT score falls at the 20th percentile for all people.
Inference for a population mean BPS chapter 16 © 2006 W.H. Freeman and Company.
Z-scores, normal distribution, and more.  The bell curve is a symmetric curve, with the center of the graph being the high point, and the two sides on.
11.10 NORMAL DISTRIBUTIONS SWBAT: USE A NORMAL DISTRIBUTION, IDENTIFY LEFT AND RIGHT SKEWS, AND APPLY STANDARD DEVIATIONS TO INTERPRET DATA FROM NORMAL.
Unit 2: Modeling Distributions of Data of Data. Homework Assignment For the A: 1, 3, 5, Odd, 25 – 30, 33, 35, 39 – 59 Odd and 54, 63, 65 – 67,
The Normal Distribution. Normal and Skewed Distributions.
15.5 The Normal Distribution. A frequency polygon can be replaced by a smooth curve A data set that is normally distributed is called a normal curve.
Construction Engineering 221 Probability and statistics Normal Distribution.
Section 2 Standard Units and Areas under the Standard Normal Distribution.
Standardized scores and the Normal Model
CHAPTER 2 Modeling Distributions of Data
The Normal Distribution
Normal Distribution.
Distributions and mathematical models
The Normal Curve and Sampling Error
Homework Log Fri 5/27 Lesson 11 – 10 Learning Objective:
Using the Empirical Rule
Lesson 11.1 Normal Distributions (Day 2)
Daniela Stan Raicu School of CTI, DePaul University
Using the Empirical Rule
Normal Distribution.
Daniela Stan Raicu School of CTI, DePaul University
12/1/2018 Normal Distributions
Warm Up – Tuesday The table to the left shows
Empirical Rule MM3D3.
Chapter 3 The Normal Distribution
Warmup Normal Distributions.
S.M .JOSHI COLLEGE ,HADAPSAR
Chapter 5 A Normal World.
CHAPTER 12 Statistics.
12-4 Normal Distribution.
Warm Up /1 Which of the following statements is true given the dot plot? The distribution is skewed left, so the mean is greater than the median.
Normal Distribution.
Presentation transcript:

Shape of Normal Curves

68%-95%-99.7% Rule

Areas under Normal Curve

Areas under Normal Curve(cont)

Example: Normal Distribution The brain weights of adult Swedish males are approximately normally distributed with mean μ = 1,400 g and standard deviation  = 100 g. (No real life population follows a normal distribution exactly!) a) What is the probability that an adult Swedish male has a brain weight of less then 1,500 g? b) What is the probability that an adult Swedish male has a brain weight between 1,475 g and 1,600 g?

Example: Normal Distribution (cont) μ = 1,400 g and  = 100 g a) What is the probability that an adult Swedish male has a brain weight of less then 1,500 g?

Example: Normal Distribution (cont) μ = 1,400 g and  = 100 g b) What is the probability that an adult Swedish male has a brain weight between 1,475 g and 1,600 g?

Area under the normal curve above 

Example: Normal Distribution The brain weights of adult Swedish males are approximately normally distributed with mean μ = 1,400 g and standard deviation  = 100 g. (No real life population follows a normal distribution exactly!) c) What is the 55 th percentile for the distribution of brain weights?

Example (ExDispersion.sas) Determine the percentage of data points within 1 SD? 2 SD?

Example: Normality (ExNormal.sas)

Example: QQPlots – Normal (ExQQplot.sas)

Example: QQPlots – Right Skewed

Example: QQPlots – Left Skewed

Example: QQPlots – Long Tail

Example: QQPlots – Tails?

Example 4.4.5: Nonnormal Data

Interpretation of Shapiro-Wilk Test P-ValueInterpretation < 0.001Very strong evidence for nonnormality < 0.01Strong evidence for nonnormality < 0.05Moderate evidence for nonnormality < 0.10Mild or weak evidence for nonnormality  0.10 No compelling evidence for nonnormality

Objective Measure: SAS Tests for Normality TestStatisticp Value Shapiro-WilkW Pr < W Kolmogorov-SmirnovD Pr > D> Cramer-von MisesW-Sq Pr > W-Sq> Anderson-DarlingA-Sq Pr > A-Sq>0.2500

Objective Measure: SAS Tests for Normality TestStatisticp Value NormalW Pr < W Right SkewedW Pr > W Left SkewedW Pr > W Long TailedW Pr > W Short TailedW Pr > W0.0317

Example: QQPlots x

Example 4.10: Continuity Correction Table 4.1 shows the distribution of litter size for a population of female mice with population mean 7.8 and SD 2.3. x

Example 4.10: Continuity Correction(cont) Table 4.1 shows the distribution of litter size for a population of female mice with population mean 7.8 and SD 2.3. x