Chapter 8. Problem 8-6 Problem 8-15 µ=60 σ=12 2496 48 72.

Slides:



Advertisements
Similar presentations
Distribution of Sample Means, the Central Limit Theorem If we take a new sample, the sample mean varies. Thus the sample mean has a distribution, called.
Advertisements

Chapter Six Sampling Distributions McGraw-Hill/Irwin Copyright © 2004 by The McGraw-Hill Companies, Inc. All rights reserved.
Chapter 8 – Normal Probability Distribution A probability distribution in which the random variable is continuous is a continuous probability distribution.
Statistics Lecture 15. Percentile for Normal Distributions The 100p th percentile of the N( ,  2 ) distribution is  +  (p)  Where  (p) is.
Lesson #16 Standardizing a Normal Distribution.  X ~ N( ,  2 )   X -   Z = ~ N( ,  )
Lesson #17 Sampling Distributions. The mean of a sampling distribution is called the expected value of the statistic. The standard deviation of a sampling.
T T07-01 Sample Size Effect – Normal Distribution Purpose Allows the analyst to analyze the effect that sample size has on a sampling distribution.
Chapter 8 Sampling Distributions
Population Proportion The fraction of values in a population which have a specific attribute p = Population proportion X = Number of items having the attribute.
1 Confidence Intervals for Means. 2 When the sample size n< 30 case1-1. the underlying distribution is normal with known variance case1-2. the underlying.
Lesson 12-1 Algebra Check Skills You’ll Need 12-4
The Binomial and Geometric Distribution
Using Normal Distribution to Approximate a Discrete Distribution.
Chapter Six Normal Curves and Sampling Probability Distributions.
Normal Curves and Sampling Distributions Chapter 7.
Chapter 10 – Sampling Distributions Math 22 Introductory Statistics.
McGraw-Hill/IrwinCopyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 7 Sampling Distributions.
July, 2000Guang Jin Statistics in Applied Science and Technology Chapter 7 - Sampling Distribution of Means.
Chapter 7: Introduction to Sampling Distributions Section 2: The Central Limit Theorem.
Estimation Chapter 8. Estimating µ When σ Is Known.
1 Chapter 5. Section 5-5. Triola, Elementary Statistics, Eighth Edition. Copyright Addison Wesley Longman M ARIO F. T RIOLA E IGHTH E DITION E LEMENTARY.
Using the Tables for the standard normal distribution.
INTRODUCTORY MATHEMATICAL ANALYSIS For Business, Economics, and the Life and Social Sciences  2011 Pearson Education, Inc. Chapter 16 Continuous Random.
Chapter 6 The Normal Distribution Section 6-3 The Standard Normal Distribution.
Chapter 6, part C. III. Normal Approximation of Binomial Probabilities When n is very large, computing a binomial gets difficult, especially with smaller.
12.6 – Probability Distributions. Properties of Probability Distributions.
1 Copyright © 2015 Elsevier Inc. All rights reserved. Chapter 4 Sampling Distributions.
Chapter 12 Inference for Proportions AP Statistics 12.2 – Comparing Two Population Proportions.
Ch5.4 Central Limit Theorem
Chapter 5 Normal Probability Distributions.
The Recursive Property of the Binomial Distribution
Example of Poisson Distribution-Wars by Year
Sec. 7-5: Central Limit Theorem
CHAPTER 7 Sampling Distributions
Chapter 5 Normal Probability Distributions.
Section 2: Estimating with Small Samples
Elementary Statistics: Picturing The World
Using the Tables for the standard normal distribution
Peanuts (a) Since averages are less variable than individual measurements, I would expect the sample mean of 10 jars to be closer, on average, to the.
Chapter 9 – Sampling Distributions
Introduction to Probability & Statistics The Central Limit Theorem
Review of Chapters 7,8 and 9 Be comfortable with all homework assignments Check out stop to think questions in each chapter Review the summary of formulae.
Probability Distribution – Example #2 - homework
Lecture Slides Elementary Statistics Twelfth Edition
Lial/Hungerford/Holcomb: Mathematics with Applications 10e
Year-3 The standard deviation plus or minus 3 for 99.2% for year three will cover a standard deviation from to To calculate the normal.
Two-way analysis of variance (ANOVA)
Chapter 3: Averages and Variation
Population Proportion
Peanuts (a) Since averages are less variable than individual measurements, I would expect the sample mean of 10 jars to be closer, on average, to the.
Sampling Distributions
Normal Probability Distributions
CHAPTER 15 SUMMARY Chapter Specifics
CHAPTER 7 Sampling Distributions
Exam 2 - Review Chapters
CHAPTER 7 Sampling Distributions
Section 12.2 Comparing Two Proportions
CHAPTER 7 Sampling Distributions
Chapter 12 Inference for Proportions
ASV Chapters 1 - Sample Spaces and Probabilities
CHAPTER 7 Sampling Distributions
CHAPTER 7 Sampling Distributions
Normal Probability Distributions
C.2.10 Sample Questions.
Sample Means Section 9.3.
C.2.8 Sample Questions.
C.2.8 Sample Questions.
Chapter 5 Normal Probability Distributions.
Continuous Probability Distributions Solved Problems
7.4 Hypothesis Testing for Proportions
Presentation transcript:

Chapter 8

Problem 8-6

Problem 8-15 µ=60 σ=

Problem 8-15(contd.)

Problem 8-15(contd.)      x x x z   4 60   x x  

Problems 8-16 Since n=40,the sampling distribution of means will approximate a normal distribution

Problem 8-16(Contd.)

Problem

Problem minutes  n a x )320(.       x z xpb x x 

Problem 8-18(Contd.) )350320(.       x z xpc x 

Problem 8-18 contd..

=110,000 = 40,000/ 50 a. = / n = 40,000/ 50 = 5657 b. Normal distribution Problem 8-34

c ,000 X =110, Z P(X> 112,000)= =.3632 Problem 8-34 cont’d

d , Problem 8-34 cont’d P( X> 100,000)= =.9616 Z

e , ,000 X Problem 8-34 cont’d P(100,000<X< 112,000)= =.5984 Z

Problem Z )1.25(       xp n x z x 