14.4 The Normal Distribution

Slides:



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

Normal Distribution Sampling and Probability. Properties of a Normal Distribution Mean = median = mode There are the same number of scores below and.
Chapter 6: The Standard Deviation as a Ruler and the Normal Model
HS 67 - Intro Health Stat The Normal Distributions
Chapter 9: The Normal Distribution
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.
Standard Scores Standard scores, or “z- scores” measure the relation between each score and its distribution.
The Normal Distribution
Normal Distributions & z score
Chapter 7: Normal Curves & Probability
Standard Normal Distribution The Classic Bell-Shaped curve is symmetric, with mean = median = mode = midpoint.
Did you know ACT and SAT Score are normally distributed?
Normal Distribution Z-scores put to use!
z-Scores What is a z-Score? How Are z-Scores Useful? Distributions of z-Scores Standard Normal Curve.
Discrete and Continuous Random Variables Continuous random variable: A variable whose values are not restricted – The Normal Distribution Discrete.
12.3 – Measures of Dispersion
Chapter 11: Random Sampling and Sampling Distributions
Statistics Normal Probability Distributions Chapter 6 Example Problems.
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.
In this chapter, we will look at using the standard deviation as a measuring stick and some properties of data sets that are normally distributed.
The Normal Distribution The “Bell Curve” The “Normal Curve”
Probability & the Normal Distribution
The Mean of a Discrete Probability Distribution
Normal Distribution MATH 102 Contemporary Math S. Rook.
Chapter 9 – 1 Chapter 6: The Normal Distribution Properties of the Normal Distribution Shapes of Normal Distributions Standard (Z) Scores The Standard.
Copyright © 2011 Pearson Education, Inc. Putting Statistics to Work.
Chapter 13 Section 7 – Slide 1 Copyright © 2009 Pearson Education, Inc. AND.
Warm-Up If the variance of a set of data is 12.4, what is the standard deviation? If the standard deviation of a set of data is 5.7, what is the variance?
The Normal Distribution James H. Steiger. Types of Probability Distributions There are two fundamental types of probability distributions Discrete Continuous.
Chapter 5 The Normal Curve. In This Presentation  This presentation will introduce The Normal Curve Z scores The use of the Normal Curve table (Appendix.
Copyright © 2012 by Nelson Education Limited. Chapter 4 The Normal Curve 4-1.
Chapter 6.1 Normal Distributions. Distributions Normal Distribution A normal distribution is a continuous, bell-shaped distribution of a variable. Normal.
Chapter 6 Foundations of Educational Measurement Part 1 Jeffrey Oescher.
Normal Distributions.  Symmetric Distribution ◦ Any normal distribution is symmetric Negatively Skewed (Left-skewed) distribution When a majority of.
Thinking Mathematically Statistics: 12.5 Problem Solving with the Normal Distribution.
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.
© 2010 Pearson Prentice Hall. All rights reserved. CHAPTER 12 Statistics.
1 Lecture 3 Outline 1. Chebyshev’s Theorem 2. The Empirical Rule 3. Measures of Relative Standing 4. Examples.
AP STATISTICS Section 2.1: Measures of Relative Standing and Density Curves.
NORMAL DISTRIBUTION Chapter 3. DENSITY CURVES Example: here is a histogram of vocabulary scores of 947 seventh graders. BPS - 5TH ED. CHAPTER 3 2 The.
Dr. Fowler  AFM  Unit 8-4 The Normal Distribution
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.
Descriptive Statistics Review – Chapter 14. Data  Data – collection of numerical information  Frequency distribution – set of data with frequencies.
MATH 110 Sec 14-4 Lecture: The Normal Distribution The normal distribution describes many real-life data sets.
The Standard Normal Distribution Section Starter Weights of adult male Norwegian Elkhounds are N(42, 2) pounds. What weight would represent the.
Thinking Mathematically Statistics: 12.4 The Normal Distribution.
Chapter 9 – The Normal Distribution Math 22 Introductory Statistics.
Normal Distributions (aka Bell Curves, Gaussians) Spring 2010.
Lesson 2 - R Review of Chapter 2 Describing Location in a Distribution.
 A standardized value  A number of standard deviations a given value, x, is above or below the mean  z = (score (x) – mean)/s (standard deviation)
The Normal Distribution Name:________________________.
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.
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.
 The heights of 16-year-old males are normally distributed with mean 68 inches and a standard deviation 2 inches. Determine the z-score for: ◦ 70.
Characteristics of Normal Distribution symmetric with respect to the mean mean = median = mode 100% of the data fits under the curve.
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 5: THE NORMAL DISTRIBUTION Leon-Guerrero and Frankfort-Nachmias, Essentials of Statistics for a Diverse Society.
Section 1.1, Slide 1 Copyright © 2014, 2010, 2007 Pearson Education, Inc. Section 14.4, Slide 1 14 Descriptive Statistics What a Data Set Tells Us.
Chapter 12 Statistics 2012 Pearson Education, Inc.
The normal distribution
Standard deviation and the normal curve
Advanced Math Topics 7.2/7.3 The Normal Curve.
Descriptive Statistics
7-7 Statistics The Normal Curve.
The Normal Distribution
Chapter 5 A Normal World.
Section 13.6 The Normal Curve
Chapter 12 Statistics.
Presentation transcript:

14.4 The Normal Distribution Probability and Statistics

Normal Distribution or Normal Curve Most common distribution in real-life and in statistics Curve Shaped AKA: Bell-Curve

Properties of a Normal Distribution A normal curve is bell shaped. The highest point on the curve is at the mean of the distribution. (also median and mode) The mean, median, and mode of the distribution are the same. The total area under the curve is 1. The 68-95-99.7 Rule

The 68-95-99.7 Rule 68% of the data is within 1 standard deviation of the mean (highest point). This means there is 34% on each side. 95% of the data is within 2 standard deviations of the mean. This means that there is 47.5% on each side. 99.7% of the data is within 3 standard deviations of the mean. This means that there is 49.85% on each side.

The 68-95-99.7 Rule 34% 34% 2.35% 2.35% 13.5% 13.5% 68 % 95 % 99.7 % Nearly all (99.7%) of the values lie within 3 standard deviations of the mean (or between the mean minus 3 times the standard deviation and the mean plus 3 times the standard deviation).

EXAMPLE: Suppose a distribution of 1,000 scores represent scores on a standardized test. The mean of the distribution is 450 and the standard deviation is 25. How many scores do we expect to fall between 425 and 475? How many scores do we expect to fall above 500?

Part 1 If the mean is 450, then 425 and 475 represent one standard deviation below and one standard deviation above the mean. This falls with 68% of the data. So… 68% of 1000 is: .68 x 1000 = 680 So 680 scores are in the range of 425-475.

Part 2 500 represents 2 standard deviations above the mean. 95% of our data falls within that range. We want to find the values above 500. This would be represented by (1/2) of 5% or 2.5% of the data. So, 2.5% of 1000 scores = .025 x 1000 = 25 25 scores would be above 500.

Assignment: pg. 831 #6-16 even

14.4. Notes Part 2

What would be the z-score? Z-Scores Represents the number of standard deviations a data value is from the mean. Positive above mean, negative below mean In the last example, we said that 500 was 2 standard deviations above the mean (the mean was 450 and standard deviation 25)… What would be the z-score? Z = 2

Z-Scores The z-score table can be used for both positive and negative z-scores. The table tells you “A” - represents the area underneath the curve. (Remember that the area underneath the entire curve is 1 .. 100%). Area represents the percentage of scores within the specified range. For example, a z-score of 1 (1 standard deviation above the mean) shows an area of 0.34 34% of the data is 1 standard deviation above the mean…

Finding Areas under a Normal Curve Using your z-score table, find the percentage of data (area under the curve) that lie in the following regions for a standard normal distribution: *draw a diagram for each! A). Between z = 0 and z = 1.3 B). Between z = 1.5 and z = 2.1 C). Between z = 0 and z = - 1.83

A). Between z = 0 and z = 1.3 By the z-score table, I look at z = 1.3 The area of the region is .403 This means 40.3% of the data will fall within this range.

B). Between z = 1.5 and z = 2.1 Z= 1.5 43.3% (represents between z=0 and z=1.5) Z=2.1 48.2% (represents between z=0 and z=2.1) So between those scores (1.5 – 2.1) we need to subtract. 48.2-43.3 = 4.9% *SSS (same-side-subtract)

C). z = 0 and z = -1.83 Since the data is evenly distributed on both sides of the mean (z=0), just look up 1.83 on your chart. z = 1.83 same as z = -1.83, just on opposite sides of the mean… Z=1.83 46.6%

Assignment 14.4 Worksheet

Converting Raw Scores to Z-Scores Value Mean Standard Deviation

Examples: Suppose the mean of a normal distribution is 20 and its standard deviation is 3. *draw a diagram to represent each situation, and answer the question. a). Find the z-score that corresponds to a raw score of 25. b). Find the z-score that corresponds to a raw score of 16. c). Find the raw score that corresponds to a z score of 2.1

Suppose the mean of a normal distribution is 20 and its standard deviation is 3. a). Find the z-score that corresponds to a raw score of 25.

Suppose the mean of a normal distribution is 20 and its standard deviation is 3. b). Find the z-score that corresponds to a raw score of 16.

Suppose the mean of a normal distribution is 20 and its standard deviation is 3. c). Find the raw score that corresponds to a z score of 2.1 +20 +20 26.3 = x

Suppose the mean of a normal distribution is 25 and its standard deviation is 5. Find the percentage of values that fall between: **draw diagram for each.. 25 and 29 22 and 25 Under 17

Percentile If the mean salary for teachers is $55,000 with a standard deviation of $5000, to what percentile does your salary of $49,000 correspond? Your friend’s salary of $63,000?

The heights of 5th graders have a mean of 4’8’’ and standard deviation of 2’’. If there are 100 5th graders, how many will be: Over 5’ tall? Under 4’5’’ tall?

ASSIGNMENT: Pg. 831 #18-34 even, #44-54 even, 65, 66, 79, 80