6-2: STANDARD NORMAL AND UNIFORM DISTRIBUTIONS. IMPORTANT CHANGE Last chapter, we dealt with discrete probability distributions. This chapter we will.

Slides:



Advertisements
Similar presentations
Overview The Standard Normal Distribution
Advertisements

Chapter – 5.4: The Normal Model
6-3 Applications of Normal Distributions This section presents methods for working with normal distributions that are not standard. That is, the mean is.
1 Examples. 2 Say a variable has mean 36,500 and standard deviation What is the probability of getting the value 37,700 or less? Using the z table.
Slide 1 Copyright © 2004 Pearson Education, Inc.  Continuous random variable  Normal distribution Overview Figure 5-1 Formula 5-1 LAPTOP3: f(x) = 
Definitions Uniform Distribution is a probability distribution in which the continuous random variable values are spread evenly over the range of possibilities;
Continuous Probability Distributions In this chapter, we’ll be looking at continuous probability distributions. A density curve (or probability distribution.
1 Business 90: Business Statistics Professor David Mease Sec 03, T R 7:30-8:45AM BBC 204 Lecture 19 = More of Chapter “The Normal Distribution and Other.
6-2 The Standard Normal Distribution
14.4 The Normal Distribution
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Chapter 6 Normal Probability Distributions
Slide 1 Copyright © 2004 Pearson Education, Inc..
Statistics Normal Probability Distributions Chapter 6 Example Problems.
Slide Slide 1 Chapter 6 Normal Probability Distributions 6-1 Overview 6-2 The Standard Normal Distribution 6-3 Applications of Normal Distributions 6-4.
Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.
The Normal Distribution The “Bell Curve” The “Normal Curve”
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. 1 PROBABILITIES FOR CONTINUOUS RANDOM VARIABLES THE NORMAL DISTRIBUTION CHAPTER 8_B.
Chapter 6 Probability. Introduction We usually start a study asking questions about the population. But we conduct the research using a sample. The role.
Standard Normal Distribution
1 Chapter 5. Section 5-1 and 5-2. Triola, Elementary Statistics, Eighth Edition. Copyright Addison Wesley Longman M ARIO F. T RIOLA E IGHTH E DITION.
QBM117 Business Statistics Probability and Probability Distributions Continuous Probability Distributions 1.
The distribution of heights of adult American men is approximately normal with mean 69 inches and standard deviation 2.5 inches. Use the rule.
Continuous Distributions. The distributions that we have looked at so far have involved DISCRETE Data The distributions that we have looked at so far.
1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Chapter 6. Continuous Random Variables Reminder: Continuous random variable.
Probabilistic & Statistical Techniques Eng. Tamer Eshtawi First Semester Eng. Tamer Eshtawi First Semester
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Section 6-1 Review and Preview.
6-2: STANDARD NORMAL AND UNIFORM DISTRIBUTIONS. IMPORTANT CHANGE Last chapter, we dealt with discrete probability distributions. This chapter we will.
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.
Continuous Random Variables Continuous Random Variables Chapter 6.
McGraw-Hill/IrwinCopyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Continuous Random Variables Chapter 6.
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 6 Normal Probability Distributions 6-1 Review and Preview 6-2 The Standard Normal.
Chapter 6 Normal Probability Distribution Lecture 1 Sections: 6.1 – 6.2.
Modular 11 Ch 7.1 to 7.2 Part I. Ch 7.1 Uniform and Normal Distribution Recall: Discrete random variable probability distribution For a continued random.
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.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 6 Probability Distributions Section 6.2 Probabilities for Bell-Shaped Distributions.
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.
Overview probability distributions
1 Chapter 5. Section 5-1 and 5-2. Triola, Elementary Statistics, Eighth Edition. Copyright Addison Wesley Longman M ARIO F. T RIOLA E IGHTH E DITION.
Slide Slide 1 Lecture 6&7 CHS 221 Biostatistics Dr. Wajed Hatamleh.
1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Chapter 6 Continuous Random Variables.
Chapter 6 The Normal Distribution.  The Normal Distribution  The Standard Normal Distribution  Applications of Normal Distributions  Sampling Distributions.
Introduction to Statistics for the Social Sciences SBS200, COMM200, GEOG200, PA200, POL200, or SOC200 Lecture Section 001, Fall 2015 Room 150 Harvill.
Slide Slide 1 Suppose we are interested in the probability that z is less than P(z < 1.42) = z*z*
Section 6-1 Overview. Chapter focus is on: Continuous random variables Normal distributions Overview Figure 6-1 Formula 6-1 f(x) =  2  x-x-  )2)2.
Section 5.1 Discrete Probability. Probability Distributions x P(x)1/4 01/83/8 x12345 P(x)
Copyright © 1998, Triola, Elementary Statistics Addison Wesley Longman 1 Nonstandard Normal Distributions: Finding Probabilities Section 5-3 M A R I O.
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.
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.
Slide 1 Copyright © 2004 Pearson Education, Inc. Chapter 6 Normal Probability Distributions 6-1 Overview 6-2 The Standard Normal Distribution 6-3 Applications.
BNAD 276: Statistical Inference in Management Winter, Green sheet Seating Chart.
Copyright ©2011 Brooks/Cole, Cengage Learning Continuous Random Variables Class 36 1.
The Normal Distributions.  1. Always plot your data ◦ Usually a histogram or stemplot  2. Look for the overall pattern ◦ Shape, center, spread, deviations.
THINK ABOUT IT!!!!!!! If a satellite crashes at a random point on earth, what is the probability it will crash on land, if there are 54,225,000 square.
Distributions Chapter 5
Lecture Slides Elementary Statistics Twelfth Edition
Review and Preview and The Standard Normal Distribution
Chapter 5 Normal Probability Distributions.
Chapter 6. Continuous Random Variables
THE STANDARD NORMAL DISTRIBUTION
The Normal Probability Distribution
Section 8.4 – Continuous Probability Models
Elementary Statistics
The Standard Normal Distribution
Section 6-1 Review and Preview.
Chapter 5 Normal Probability Distributions.
Chapter 5 Normal Probability Distributions.
Normal Probability Distribution Lecture 1 Sections: 6.1 – 6.2
Presentation transcript:

6-2: STANDARD NORMAL AND UNIFORM DISTRIBUTIONS

IMPORTANT CHANGE Last chapter, we dealt with discrete probability distributions. This chapter we will deal with continuous distributions. We are not focused on the probability of a specific data value, instead we care about ranges.

Topics  Normal Distributions in General  Probability as an Area  Uniform Distributions  Standard Normal Distribution  Calculating Probability  Calculating Z-Score

Normality is based on standard deviation and mean. There is a formula that can be used to describe the curve based on these parameters, however, we will not need to use it in this course. MEAN Normal Distribution: A continuous probability distribution that is symmetric and bell- shaped.

Probability as an Area  The graph representing a continuous distribution is also known as a density curve.  The total area under the curve must equal 1  Every point has a height of 0 or greater  Using this information, we can use area to represent probability.  This will start to make sense within the context of problems.

Uniform Distribution  A distribution is uniform if its probability remains the same for the entire range of possibilities. P(x) x

Example Ace Heating and Air Conditioning Service finds that the amount of time a repairman needs to fix a furnace is uniformly distributed between 1 and 5 hours. Find the probability that it takes more that 3.5 hours time Prob

You Try! A power company provides electricity with voltage levels that are uniformly distributed across Find the probability that a randomly selected voltage is greater than voltage Prob

Suggested Practice from p.261+  Uniform Distribution: 5-8  Find Probability from Left: 9, 17, 19  Find Probability from Right: 10, 21, 23  Find Probability in the Middle: 12, 25, 29  Find z Score from Left: 13, 50  Find z Score in Middle: 51  Find z Score from Right: 42, 43

Standard Normal Distribution  The standard normal distribution is a special case of the normal distribution in which the mean is 0 and the standard deviation is z Scores AREA

Area and z Scores  z Score: As it was before z-scores represent distance on the horizontal scale (# of standard deviations from mean).  Area: The region under the curve bounded by a specific parameter or parameters.

Calculating Probability  Just like the uniform distribution, the area under the curve represents probability.  Calculating area is much more difficult with a curve, so we will refer to table A-2 which does the calculations for us.  The table refers to the area under the curve up to the specific z Score from the LEFT  DRAW A PICTURE FOR EVERY PROBLEM!!!

Example  A company that makes thermometers realizes that their product is not completely accurate. When the temperature is actually 0°, it sometimes reads slightly above or slightly below 0°. They find that this range is normally distributed with a mean of 0° and standard deviation of 1°. Find the probability that the thermometer reads less than 1.27°

You try!  A new card game called 3’s has a normal distribution for earnings, with the mean winnings being $0, and a standard deviation of a $1. What is the probability of losing more than $1.50?

Question  What if they ask you to find area from the right?  Since the area is equal to 1, you can find the probability from the left (B) and the area from the right is A = 1 – B

You try!  Using the previous thermometer example, find the probability of randomly selecting one thermometer that reads above -1.23°

Example  Using the thermometer example, find the probability that the temperature is between -2.00° and 1.50°

Big Note!  If the area is bound between two numbers, find the probability from the left for both values, and subtract!  Remember area, like probability cannot be negative!

Suggested Practice from p.261+  Uniform Distribution: 5-7  Find Probability from Left: 9, 17  Find Probability from Right: 10, 21  Find Probability in the Middle: 12, 25  Find z Score from Left: 13, 50  Find z Score in Middle: 51  Find z Score from Right: 42, 43

Homework Quiz

Finding the z Score, Given Probability  From the left:  Find the given probability in the table and figure out which z Score corresponds with it.  Bounded on both sides:  Treat each end separate  From the right:  Find the z Score that goes with the complement

Example  Using the thermometer example from earlier in the section, find the temperature that would represent the 89 th percentile (the temperature separating the bottom 89% from the top 11%). 1.23

Big Note!  If the area you are looking for in the table cannot be found exactly, but you see 2 z Scores that produce areas slightly above and slightly below that value, then just take the z score closest to the value you are looking for.  Example: Look for the z score that produces an area of.800.

Example  Use the “quarterback sneak” example to find the yardage that would represent the 99 th percentile. 2.33

Example  Using the thermometer example, find the z Scores that separate the bottom 5% and the top 5% and 1.645

One last thing…

Example

Suggested Practice from p.261+  Uniform Distribution: 5-7  Find Probability from Left: 9, 17, 19  Find Probability from Right: 10, 21, 23  Find Probability in the Middle: 12, 25, 29  Find z Score from Left: 13, 14, 50  Find z Score in Middle: 51  Find z Score from Right: 15, 16, 42, 43

Homework (graded for correctness)  Complete worksheet!