Finding Z – scores & Normal Distribution Using the Standard Normal Distribution Week 9 Chapter’s 5.1, 5.2, 5.3.

Slides:



Advertisements
Similar presentations
Quantitative Methods Topic 5 Probability Distributions
Advertisements

Chapter 2: The Normal Distributions
The Standard Normal Distribution.
5 Normal Probability Distributions
Lecture 4 PY 427 Statistics 1 Fall 2006 Kin Ching Kong, Ph.D
Normal Distribution A random variable X having a probability density function given by the formula is said to have a Normal Distribution with parameters.
Chapter 6 The Normal Distribution Normal Distributions Bell Curve Area under entire curve = 1 or 100% Mean = Median – This means the curve is symmetric.
T HE ‘N ORMAL ’ D ISTRIBUTION. O BJECTIVES Review the Normal Distribution Properties of the Standard Normal Distribution Review the Central Limit Theorem.
Lesson 7 - QR Quiz Review.
Quantitative Analysis (Statistics Week 8)
Standardizing Data and Normal Model(C6 BVD) C6: Z-scores and Normal Model.
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.
Basic Statistics Measures of Central Tendency.
Tutorial: Understanding the normal curve. Gauss Next mouse click.
The Normal Curve. Introduction The normal curve Will need to understand it to understand inferential statistics It is a theoretical model Most actual.
1 STANDARD DEVIATION & THE NORMAL MODEL What is a normal distribution? The normal distribution is pattern for the distribution of a set of data which follows.
5.1 Normal Probability Distributions Normal distribution A continuous probability distribution for a continuous random variable, x. The most important.
5 Normal Probability Distributions
Normal Probability Distributions
Normal and Standard Normal Distributions June 29, 2004.
For Explaining Psychological Statistics, 4th ed. by B. Cohen
The Normal Distribution
2-5 : Normal Distribution
CHAPTER 6 Statistical Analysis of Experimental Data
CHAPTER 3: The Normal Distributions Lecture PowerPoint Slides The Basic Practice of Statistics 6 th Edition Moore / Notz / Fligner.
Normal Distribution Z-scores put to use!
Normal Probability Distributions Chapter 5. § 5.1 Introduction to Normal Distributions and the Standard Distribution.
1 Normal Distributions Heibatollah Baghi, and Mastee Badii.
© Copyright McGraw-Hill CHAPTER 6 The Normal Distribution.
Normal Distributions.
Looking at Data - Distributions Density Curves and Normal Distributions IPS Chapter 1.3 © 2009 W.H. Freeman and Company.
Normal Distribution. Objectives The student will be able to:  identify properties of normal distribution  apply mean, standard deviation, and z -scores.
The Normal Distribution The “Bell Curve” The “Normal Curve”
Stat 1510: Statistical Thinking and Concepts 1 Density Curves and Normal Distribution.
Chapter 12 – Probability and Statistics 12.7 – The Normal Distribution.
NOTES The Normal Distribution. In earlier courses, you have explored data in the following ways: By plotting data (histogram, stemplot, bar graph, etc.)
CHAPTER 3: The Normal Distributions ESSENTIAL STATISTICS Second Edition David S. Moore, William I. Notz, and Michael A. Fligner Lecture Presentation.
Essential Statistics Chapter 31 The Normal Distributions.
Normal Probability Distributions Chapter 5. § 5.1 Introduction to Normal Distributions and the Standard Distribution.
© 2010 Pearson Prentice Hall. All rights reserved. CHAPTER 12 Statistics.
Chapter 6 The Normal Distribution. 2 Chapter 6 The Normal Distribution Major Points Distributions and area Distributions and area The normal distribution.
Essential Statistics Chapter 31 The Normal Distributions.
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.
The Normal Distribution
IPS Chapter 1 © 2012 W.H. Freeman and Company  1.1: Displaying distributions with graphs  1.2: Describing distributions with numbers  1.3: Density Curves.
Introduction to the Normal Distribution (Dr. Monticino)
Chapter 6 The Normal Distribution.  The Normal Distribution  The Standard Normal Distribution  Applications of Normal Distributions  Sampling Distributions.
1 The Standard Deviation as a Ruler  A student got a 67/75 on the first exam and a 64/75 on the second exam. She was disappointed that she did not score.
Normal Probability Distributions. Intro to Normal Distributions & the STANDARD Normal Distribution.
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.
THE NORMAL DISTRIBUTION
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.
The Normal Distributions.  1. Always plot your data ◦ Usually a histogram or stemplot  2. Look for the overall pattern ◦ Shape, center, spread, deviations.
Normal Distributions Overview. 2 Introduction So far we two types of tools for describing distributions…graphical and numerical. We also have a strategy.
Continuous random variables
Normal Probability Distributions
Normal Probability Distributions Chapter 5. § 5.1 Introduction to Normal Distributions and the Standard Distribution.
Transforming Data.
Normal Probability Distributions
Elementary Statistics: Picturing The World
The Normal Probability Distribution
Normal Probability Distributions
EQ: How do we approximate a distribution of data?
Normal Distribution Z-distribution.
Some may be used more than once or not at all.
Do Now In BIG CLEAR numbers, please write your height in inches on the index card.
Section 13.6 The Normal Curve
Chapter 5 Normal Probability Distributions.
Presentation transcript:

Finding Z – scores & Normal Distribution Using the Standard Normal Distribution Week 9 Chapter’s 5.1, 5.2, 5.3

Normal Distribution Normal Distribution - is a very important statistical data distribution pattern occurring in many natural phenomena, such as height, blood pressure, grades, IQ, baby birth weights, etc. Normal Curve - when graphing the normal distribution as a histogram, it will create a bell- shaped curve known as a normal curve. It is based on Probability! You’ll see!

Normal Distribution Curve:

What is this curve all about? The shape of the curve is bell-shaped The graph falls off evenly on either side of the mean. (symmetrical) 50% of the distribution lies on the left of the mean 50% lies to the right of the mean. (above) The spread of the normal distribution is controlled by the standard deviation. The mean and the median are the same in a normal distribution. (and even the mode)

Features of Standard Normal Curve Mean is the center 68% of the area is within one S.D. 95% of area is within two S.D.’s 99% of area is within 3 S.D.’s As each tail increases/decreases, the graph approaches zero (y axis), but never equals zero on each end. For each of these problems we will need pull-out table IV in the back of text

What is a Z – Score? Z-score’s allow us a method of converting, proportionally, a study sample to the whole population. Z-Score’s are the exact number of standard deviations that the given value is away from the mean of a NORMAL CURVE. Table IV always solves for the area to the left of the Z-Score!

Finding the area to the left of a Z (Ex. 1) – Find the area under the standard normal curve that lies to the left of Z=1.34.

Finding the area to the right of a Z (Ex. 2) - Find the area under the standard normal curve that lies to the right of Z =

Finding the area in-between two Z’s (Ex. 3) - Find the area under the standard normal curve that lies between Z=-2.04 and Z=1.25.

Formula: x = data value u = population mean

Practice examples: For each of the following examples, Look for the words "normally distributed" in a question before using Table IV to solve them. Don’t forget - Table IV always solves for the area to the left of the Z-Score!

Finding Probabilities The shaded area under the curve is equal to the probability of the specific event occurring. Ex (4) - A shoe manufacturer collected data regarding men's shoe sizes and found that the distribution of sizes exactly fits a normal curve. If the mean shoe size is 11 and the standard deviation is 1.5. (a)What is the probability of randomly selecting a man with a shoe size smaller than 9.5? (b)If I surveyed 40 men, how many would be expected to wear smaller than 9.5?

How did we get that answer: is a Z-score (# of S.D.’s from the mean) that refers to the area to the left of that position. Find it in Table IV =.1587 We want the area to the left of that curve, so, this is the answer. Table IV gives us the answer for area to the left of the curve. (b).1587(40) = 6.3 = 6 This is how many SD’s from the mean

Ex (5) – Gas mileage of vehicles follows a normal curve. A Ford Escape claims to get 25 mpg highway, with a standard deviation of 1.6 mpg. A Ford Escape is selected at random. (a) What is the probability that it will get more than 28 mpg? (b) If I sampled 250 Ford Escapes, how many would I expect to get more than 28 mpg?

How did we get that answer: is a Z-score (# of S.D.’s from the mean) that refers to the area to the left of that position =.9696 We want the area to the right of that curve, thus =.0304

Ex (6) – This past week gas prices followed a normal distribution curve and averaged $3.73 per gallon, with a standard deviation of 3 cents. What percentage of gas stations charge between $ 3.68 and $ 3.77?

Ex (7) – This week gas prices followed a normal distribution curve and averaged $3.71 per gallon, with a standard deviation of 3 cents. (a)What percent of stations charge at least $3.77? (b)What percent will charge less than $3.71? (c)What percent will charge less than $3.69? (d)What percent will charge in-between $3.67and $3.75 per gallon? (e)If I sampled 30 gas stations, how many would charge between $3.67and $3.75 per gallon?

NOW – Going back from probabilities to Z-Scores: Chapter 5.3 – Finding Z-scores from probabilities – Transforming a Z-score to an X-value Look up.9406 on Table 4 What Z-score corresponds to this area?

Finding Z-score’s of area to the left (Ex. 8) (a)Find the Z-score so that the area to the left is 10.75% (b) Find the Z-score that represents the 75 th percentile? (c) Find the Z-score so that the area to the left is.88 (d) Find the Z-score so that the area to the left is.9880

Transforming a Z-score to an x-value Try: 90 th percentile Look for the three ingredients to solve for x: Population mean, standard deviation, and you will need the Z-score that corresponds to the given percent (or probability)

(Ex. 9) – The national average on the math portion of the SAT is a 510 with a standard deviation of 130. SAT scores follow a normal curve. (a) What score represents the 90 th percentile? (b) What score will place you at the 35 th percentile? Finding Z-score’s of area to the left

Finding Z-score’s of area to the Right (Ex. 10) – Find the Z score so that the area under the standard normal curve to the right is.7881

Find the Z score of area to the Right (Ex. 11) – A batch of Northern Pike at a local fish hatchery has a mean length of a 8 inches just as they are released to the wild. Their lengths are normally distributed with a standard deviation of 1.25 inches. What is the shortest length that could still be considered part of the top 15% of lengths?

Find the Z score of area in-between two Z’s (Ex. 12) – Find the Z score that divides the middle 90% of the area under the standard normal curve.

Critical Two-tailed Z value: - Used to find the remaining percent on the outside of the area under the curve. -90% is equal to 1-.90= /2 =.05 = 5%

M&M Packaging Ex (13) – A bag of M&M’s contains 40 candies with a Standard deviation of 3 candies. The packaging machine is considered un-calibrated if it packages bags outside of 80%, centered about the mean. What interval must the candies be between for sale?

The Central Limit Theorem: As the sample sizes increases, the sampling distribution becomes more accurate in representation of the entire population. Thus, As additional observations are added to the sample, the difference of the Sample mean and the population mean approaches ZERO. ( No difference)