X: is the random variable that counts the number of successes in n trials. It has a binomial distribution. n: is the size of the sample. : is the proportion.

Slides:



Advertisements
Similar presentations
Confidence Intervals Chapter 19. Rate your confidence Name Mr. Holloways age within 10 years? within 5 years? within 1 year? Shooting a basketball.
Advertisements

Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide
Binomial Distributions Section 8.1. The 4 Commandments of Binomial Distributions There are n trials. There are n trials. Each trial results in a success.
Chapter 7: Sampling Distributions
Confidence Intervals with Proportions
 These 100 seniors make up one possible sample. All seniors in Howard County make up the population.  The sample mean ( ) is and the sample standard.
CHAPTER 13: Binomial Distributions
AP Statistics Section 9.2 Sample Proportions
Sampling Distributions for Proportions Allow us to work with the proportion of successes rather than the actual number of successes in binomial experiments.
Normal and Sampling Distributions A normal distribution is uniquely determined by its mean, , and variance,  2 The random variable Z = (X-  /  is.
WARM – UP 1.Phrase a survey or experimental question in such a way that you would obtain a Proportional Response. 2.Phrase a survey or experimental question.
AP Statistics Chapter 9 Notes.
In this chapter we will consider two very specific random variables where the random event that produces them will be selecting a random sample and analyzing.
AP STATISTICS LESSON 8 – 1 ( DAY 2 ) THE BINOMIAL DISTRIBUTION (BINOMIAL FORMULAS)
Notes – Chapter 17 Binomial & Geometric Distributions.
Binomial Distributions Calculating the Probability of Success.
The Binomial and Geometric Distribution
Chapter 9.2: Sample Proportion Mr. Lynch AP Statistics.
Sampling Distributions of Proportions. Sampling Distribution Is the distribution of possible values of a statistic from all possible samples of the same.
Your mail-order company advertises that it ships 90% of its orders within three working days. You select an SRS of 100 of the 5000 orders received in.
Bernoulli Trials Two Possible Outcomes –Success, with probability p –Failure, with probability q = 1  p Trials are independent.
Section 5.2 The Sampling Distribution of the Sample Mean.
Lecture 11 Dustin Lueker. 2  The larger the sample size, the smaller the sampling variability  Increasing the sample size to 25… 10 samples of size.
Section 6-5 The Central Limit Theorem. THE CENTRAL LIMIT THEOREM Given: 1.The random variable x has a distribution (which may or may not be normal) with.
Confidence Intervals with Proportions Using the Calculator Notes: Page 166.
A.P. STATISTICS LESSON SAMPLE PROPORTIONS. ESSENTIAL QUESTION: What are the tests used in order to use normal calculations for a sample? Objectives:
9.2: Sample Proportions. Introduction What proportion of U.S. teens know that 1492 was the year in which Columbus “discovered” America? A Gallop Poll.
The Sampling Distribution of
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Section 5-5 Poisson Probability Distributions.
Ch 12 – Inference for Proportions YMS 12.1
Confidence Interval for p, Using z Procedure. Conditions for inference about proportion Center: the mean is ƥ. That is, the sample proportion ƥ is an.
Inference on Proportions. Assumptions: SRS Normal distribution np > 10 & n(1-p) > 10 Population is at least 10n.
Lecture 11 Dustin Lueker. 2  The larger the sample size, the smaller the sampling variability  Increasing the sample size to 25… 10 samples of size.
Lesson The Normal Approximation to the Binomial Probability Distribution.
A statistic from a random sample or randomized experiment is a random variable. The probability distribution of this random variable is called its sampling.
Collect 9.1 Coop. Asmnt. &… ____________ bias and _______________ variability.
The Practice of Statistics Third Edition Chapter 9: Sampling Distributions Copyright © 2008 by W. H. Freeman & Company Daniel S. Yates.
7.2 Sample Proportions Objectives SWBAT: FIND the mean and standard deviation of the sampling distribution of a sample proportion. CHECK the 10% condition.
Statistics 17 Probability Models. Bernoulli Trials The basis for the probability models we will examine in this chapter is the Bernoulli trial. We have.
Sampling Distributions of Proportions. Toss a penny 20 times and record the number of heads. Calculate the proportion of heads & mark it on the dot plot.
7.4 and 7.5 Obj: Assess normality of a distribution and find the normal approximation to a binomial distribution.
Section 6.2 Binomial Distribution
Ch5.4 Central Limit Theorem
CHAPTER 14: Binomial Distributions*
CHAPTER 9 Sampling Distributions
CHAPTER 6 Random Variables
Section 9.2 – Sample Proportions
Sampling Distributions for a Proportion
CHAPTER 7 Sampling Distributions
Advanced Placement Statistics
The Normal Probability Distribution Summary
Distribution of the Sample Proportion
MATH 2311 Section 4.4.
Chapter 17 Probability Models.
CHAPTER 7 Sampling Distributions
Sampling Distributions
The Practice of Statistics
The estimate of the proportion (“p-hat”) based on the sample can be a variety of values, and we don’t expect to get the same value every time, but the.
CHAPTER 7 Sampling Distributions
CHAPTER 7 Sampling Distributions
CHAPTER 7 Sampling Distributions
CHAPTER 7 Sampling Distributions
Bernoulli Trials Two Possible Outcomes Trials are independent.
CHAPTER 7 Sampling Distributions
CHAPTER 7 Sampling Distributions
Day 46 Agenda: DG minutes.
The Binomial Distributions
Sample Proportions Section 9.2.
Sample Proportions Section 9.2
Presentation transcript:

X: is the random variable that counts the number of successes in n trials. It has a binomial distribution. n: is the size of the sample. : is the proportion of successes in the sample IT DOES NOT HAVE A BINOMIAL DISTRIBUTION!

So where did these formulas come from? Remember we started with : X was a random variable from a binomial distribution. 1) What are the 4 criteria for a binomial distribution? 2)What are the formulas for finding the mean and standard deviation for a binomial distribution.

Develop the formula for mean and standard deviation for asampling distribution Remember the population must be ten times as large as the sample size as a general rule of thumb of the standard deviation calculated this was is invalid.

The shape of the sampling distribution can be approximated with normal calculations as long as Do you recall why??????

p =.1, (1-p)=.9, n=15 p=.01 (1-p) =.99 n=15 np = 1.5 n(1-p) = 13.5 np =.15 n(1-p) = p =.001, (1-p) =.999 n = 15 np =.015 n(1-p)=

p =.7 (1-p) =.3 np = 10.5 (1-p)n= 4.5 n=15 mean = 10.5 SD= p =.3 (1-p) =.7 np = mean= 4.5 n= 15 n(1-p) = 10.5 SD= p =.9 (1-p) =.1 np = 13.5 (1-p)n= 1.5 n = 15, mean 13.5, SD =

Example Your mal order company advertises that it ships 90% of its orders within three working days. You select an SRS of 100 of the 5000 orders received that week for an audit. The audit reveals that 86 of these orders were shipped on time. What is the probability that the proportion in an SRS of 100 orders is as small as the proportion in your sample or smaller?

Checklist: 1) State the probability we are trying to find. 2) State the mean of this sample distribution. 3) State the standard deviation of the sampling distribution of Dont to forget to verify your assumption. 4) Can normal calculations be used?