6-1 The Normal Distribution. Do you know the Normal Distribution? Of course you do. Many of you have talked abut a Normal Curve. The other magic phrase.

Slides:

Advertisements

Similar presentations

Chapter 6 Normal Distributions Understandable Statistics Ninth Edition

Advertisements

Statistics S2 Year 13 Mathematics. 17/04/2015 Unit 1 – The Normal Distribution The normal distribution is one of the most important distributions in statistics.

Statistics 1: Introduction to Probability and Statistics Section 3-3.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 The Normal Distribution.

Discrete and Continuous Random Variables Continuous random variable: A variable whose values are not restricted – The Normal Distribution Discrete.

Normal Curves and Sampling Distributions

Review – Using Standard Deviation Here are eight test scores from a previous Stats 201 class: 35, 59, 70, 73, 75, 81, 84, 86. The mean and standard deviation.

Normal Distribution -6. Normal Distribution Probability distribution. It has the following important characteristics: (1) the curve has a single peak;

Normal Distributions and the Empirical Rule Learning Target: I can use percentiles and the Empirical rule to determine relative standing of data on the.

Understanding Basic Statistics Chapter Seven Normal Distributions.

Copyright © Cengage Learning. All rights reserved. Normal Curves and Sampling Distributions 7.

© 2008 Pearson Addison-Wesley. All rights reserved Chapter 1 Section 13-5 The Normal Distribution.

Normal Curves and Sampling Distributions Chapter 7.

Normal Distributions.  Symmetric Distribution ◦ Any normal distribution is symmetric Negatively Skewed (Left-skewed) distribution When a majority of.

Graphs of Normal Probability Distributions The graph of a normal distribution is called a normal curve. It takes on the shape of a bell and is referred.

The Normal Distribution Chapter 6. Outline 6-1Introduction 6-2Properties of a Normal Distribution 6-3The Standard Normal Distribution 6-4Applications.

AP Statistics Chapter 2 Notes. Measures of Relative Standing Percentiles The percent of data that lies at or below a particular value. e.g. standardized.

Chapter Six Normal Curves and Sampling Probability Distributions.

The Normal Distribution. The Area under the curve The area under the curve represents everything: 100%.

Normal Distribution. Normal Distribution: Symmetric: Mean = Median = Mode.

Standard Deviation and the Normally Distributed Data Set

Section 6.1 Introduction to the Normal Distribution Entirely rewritten by D.R.S., University of Cordele.

Statistics Chapter 6 / 7 Review. Random Variables and Their Probability Distributions Discrete random variables – can take on only a countable or finite.

Has a single peak at the center. Unimodal. Mean, median and the mode are equal and located in the center of the curve. Symmetrical about the mean. Somewhat.

Chapter 9 – The Normal Distribution Math 22 Introductory Statistics.

The Normal Distribution: Comparing Apples and Oranges.

Unit 4: Normal Distributions Part 1 Statistics Mr. Evans.

Copyright (C) 2002 Houghton Mifflin Company. All rights reserved. 1 Understandable Statistics S eventh Edition By Brase and Brase Prepared by: Lynn Smith.

Normal Distributions. Probability density function - the curved line The height of the curve --> density for a particular X Density = relative concentration.

MATH Section 4.2. The Normal Distribution A density curve that is symmetric, single peaked and bell shaped is called a normal distribution. The.

Stat 2411 Statistical Methods Chapter 4. Measure of Variation.

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.

CHAPTER 6 6-1:Normal Distribution Instructor: Alaa saud Note: This PowerPoint is only a summary and your main source should be the book.

7 Normal Curves and Sampling Distributions

Introduction to Normal Distributions

Continuous Probability Distributions

Normal Probability Distribution

Describing Location in a Distribution

Continuous Probability Distributions

Statistics 11/29 Objective: Students will be able to find standard deviation and variance. Standards: 1.02 Summarize and analyze univariate data to solve.

Chapter 12 Statistics 2012 Pearson Education, Inc.

Elementary Statistics: Picturing The World

ANATOMY OF THE EMPIRICAL RULE

NORMAL PROBABILITY DISTRIBUTIONS

The normal distribution

12/1/2018 Normal Distributions

Graphs of Normal Probability Distributions

Teacher Introductory Statistics Lesson 2.4 D

The Normal Distribution

2.1 Density Curves and the Normal Distributions

Normal Probability Distributions

7-7 Statistics The Normal Curve.

Chapter 6: Normal Distributions

Section 2.1 Density Curves & the Normal Distributions

10-5 The normal distribution

The Normal Distribution

Sec Introduction to Normal Distributions

The Normal Distribution

Graphs of Normal Probability Distributions

Section 13.6 The Normal Curve

Introduction to Normal Distributions

Normal Probability Distribution

Chapter 5 Normal Probability Distributions.

Density Curves and the Normal Distributions

Empirical Rule ( %) Empirical Rule For data with a (symmetric) bell-shaped distribution, the standard deviation has the following characteristics.

12-4 Normal Distribution.

Objective: To introduce the characteristics of normal distribution curve. Standard 5.10.

Introduction to Normal Distributions

Chapter 12 Statistics.

Presentation transcript:

6-1 The Normal Distribution

Do you know the Normal Distribution? Of course you do. Many of you have talked abut a Normal Curve. The other magic phrase is the Bell Shaped curve. What are the characteristics of a Bell Shaped Curve? 1. Smooth 2. Symmetrical about μ and peaks at μ 3. Has inflection points at μ ± σ 4. Never touches the x axis

The Empirical Rule For a distribution that is symmetrical and bell shaped (in particular is normal) - Approx. 68% of the data will be within 1 Standard Deviation on each side of μ - Approx. 95% of the data will be within 2 Standard Deviations on each side of μ - Approx. 99.7% of the data will be within 3 Standard Deviation on each side of μ Sounds like Chebyshev’s Theorem… (note that Chebyshev’s applies to ALL distributions where this empirical rule replies only to Normal Distributions

Control Chart Shows Sequential Data and its relationship to μ in terms of σ (location of dashed lines..) Can be thought of as a “warning device” should data start to veer beyond a certain point

Statistical Control A control chart of the data shows that the data, over time, is continuing to behave in generally the same manner…

Out of Control Signals 1. One point beyond 3σ (the probability of something being beyond that point is.3 percent) 2. Nine consecutive points on one side of the center line (μ) 3. Two of three consecutive points lie beyond 2σ on the same side of the center line.

To graph a normal distribution.. Press Y= Press Distr Select 1: normalpdf(x,μ,σ) Press Window and set the min and max values to μ ± 3σ Press Zoom and choose 0: Zoomfit

Resources