6.3 Confidence Intervals for Population Proportions

Slides:



Advertisements
Similar presentations
Chapter 6 Confidence Intervals.
Advertisements

HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Section 8.4.
Sections 7-1 and 7-2 Review and Preview and Estimating a Population Proportion.
Introduction to Confidence Intervals using Population Parameters Chapter 10.1 & 10.3.
QBM117 - Business Statistics Estimating the population proportion.
Chapter 6 Confidence Intervals.
7-2 Estimating a Population Proportion
6.1 Confidence Intervals for the Mean (Large Samples)
6.4 Confidence Intervals for Variance and Standard Deviation Statistics Mrs. Spitz Spring 2009.
Confidence Intervals for the Mean (σ Unknown) (Small Samples)
Chapter 7 Confidence Intervals and Sample Sizes
Confidence Intervals Chapter 6. § 6.1 Confidence Intervals for the Mean (Large Samples)
Chapter 6 Confidence Intervals.
Chapter 6 Confidence Intervals 1 Larson/Farber 4th ed.
6 Chapter Confidence Intervals © 2012 Pearson Education, Inc.
6 Chapter Confidence Intervals © 2012 Pearson Education, Inc.
Sections 6-1 and 6-2 Overview Estimating a Population Proportion.
Chapter 7 Estimation. Section 7.3 Estimating p in the Binomial Distribution.
Confidence Intervals Chapter 6. § 6.1 Confidence Intervals for the Mean (Large Samples)
Confidence Intervals 1 Chapter 6. Chapter Outline Confidence Intervals for the Mean (Large Samples) 6.2 Confidence Intervals for the Mean (Small.
Section 6.3 Confidence Intervals for Population Proportions Larson/Farber 4th ed.
Confidence Intervals Elementary Statistics Larson Farber Chapter 6.
Confidence Intervals for the Mean (Large Samples) Larson/Farber 4th ed 1 Section 6.1.
Elementary Statistics
Confidence Intervals Review
Confidence Intervals for the Mean (σ known) (Large Samples)
8 Chapter Estimation © 2012 Pearson Education, Inc.
Copyright © 2013, 2010 and 2007 Pearson Education, Inc. Chapter Estimating the Value of a Population Parameter 9.
Review of the Binomial Distribution Completely determined by the number of trials (n) and the probability of success (p) in a single trial. q = 1 – p If.
Confidence Intervals for Population Proportions
Copyright © 2010, 2007, 2004 Pearson Education, Inc. Chapter 7 Estimates and Sample Sizes 7-1 Review and Preview 7-2 Estimating a Population Proportion.
Estimating a Population Proportion
Confidence Intervals for Population Proportions
Unit 6 Confidence Intervals If you arrive late (or leave early) please do not announce it to everyone as we get side tracked, instead send me an .
Sections 7-1 and 7-2 Review and Preview and Estimating a Population Proportion.
Section 6.3 Confidence Intervals for Population Proportions Larson/Farber 4th ed1.
Copyright © 2015, 2012, and 2009 Pearson Education, Inc. 1 Section 6.1 Confidence Intervals for the Mean (  Known)
Introduction to Confidence Intervals using Population Parameters Chapter 10.1 & 10.3.
Confidence Intervals for the Mean (Small Samples) 1 Larson/Farber 4th ed.
Section 6.1 Confidence Intervals for the Mean (Large Samples) Larson/Farber 4th ed.
Confidence Intervals Chapter 6. § 6.3 Confidence Intervals for Population Proportions.
Understanding Basic Statistics
Section 6.1 Confidence Intervals for the Mean(Large Samples)
Confidence Intervals Chapter 6. § 6.1 Confidence Intervals for the Mean (Large Samples)
Copyright © 2015, 2012, and 2009 Pearson Education, Inc. 1 Section 6.2 Confidence Intervals for the Mean (  Unknown)
Section 6.2 Confidence Intervals for the Mean (Small Samples) Larson/Farber 4th ed.
Chapter Estimation 1 of 83 8 © 2012 Pearson Education, Inc. All rights reserved.
Chapter Outline 6.1 Confidence Intervals for the Mean (Large Samples) 6.2 Confidence Intervals for the Mean (Small Samples) 6.3 Confidence Intervals for.
1 Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Example: In a recent poll, 70% of 1501 randomly selected adults said they believed.
Copyright © 2015, 2012, and 2009 Pearson Education, Inc. 1 Chapter Confidence Intervals 6.
Section 6.3 Confidence Intervals for Population Proportions © 2012 Pearson Education, Inc. All rights reserved. 1 of 83.
Chapter Confidence Intervals 1 of 31 6  2012 Pearson Education, Inc. All rights reserved.
Section 6.2 Confidence Intervals for the Mean (Small Samples) © 2012 Pearson Education, Inc. All rights reserved. 1 of 83.
Chapter 6 Confidence Intervals 1 Larson/Farber 4th ed.
Section 6.1 Confidence Intervals for the Mean (Large Samples) © 2012 Pearson Education, Inc. All rights reserved. 1 of 83.
6.1 Confidence Intervals for the Mean (Large Samples) Prob & Stats Mrs. O’Toole.
Chapter 6 Confidence Intervals.
Chapter 6 Confidence Intervals.
6.3 Confidence Intervals for Population Proportions
Section 6-3 –Confidence Intervals for Population Proportions
Estimating a Population Proportion
Elementary Statistics: Picturing The World
Chapter 6 Confidence Intervals.
Chapter 6 Confidence Intervals.
Chapter 6 Confidence Intervals.
Section 3: Estimating p in a binomial distribution
Confidence Intervals with Proportions
Confidence Intervals for the Mean (Large Samples)
Chapter 6 Confidence Intervals.
Presentation transcript:

6.3 Confidence Intervals for Population Proportions Statistics Mrs. Spitz Spring 2009

Objectives/Assignment How to find a sample proportion How to construct a confidence interval for a population proportion How to determine a minimum sample size when estimating a population proportion. Assignment: pp. 280-282 #1-27 all

Schedule for coming weeks: Today – Notes 6.3. Homework due BOC on Friday. Friday, 1/16/09 – Notes 6.4. Assignment due Tuesday on our return. Monday – 1/19/09 – No school Tuesday – 1/20/09 – Chapter Review Thursday-Chapter Review 6 DUE – Test – Chapter 6 Friday – 1/23/09 – 7.1 Hypothesis Testing

Sample Proportions Recall from section 4.2 that the probability of success in a single trial of a binomial experiment is p. This probability is a population proportion. In this section, you will learn how to estimate a population proportion, p using a confidence interval. As with confidence intervals for µ, you will start with a point estimate (6.1)

Definition: The point estimate for p, the population proportion of successes, is given by the proportion of successes in a sample and is denoted by: where x is the number of successes in the sample and n is the number in the sample. The point estimate for the number of failures is .The symbols and are read as “p hat” and “q hat”

Ex. 1: Finding a point estimate for p In a survey of 883 American adults, 380 said that their favorite sport is football. Find a point estimate for the population proportion of adults who say their favorite sport is football. SOLUTION: Using n =883 and x = 380

Insight In the first two sections, estimates were made for the quantitative data. In this section, sample proportions are used to make estimates for qualitative data.

Confidence Intervals for a Population P Constructing a confidence interval for a population proportion p is similar to constructing a confidence interval for a population mean. You start with a point estimate and calculate a maximum error of estimate.

Definition: A c-confidence interval for the population proportion p is where The probability that the confidence interval contains p is c.

Notes In section 5.5, you learned that a binomial can be approximated by the normal distribution if np  5 and nq  5. When and , the sampling distribution for is approximately normal with a mean of p = p and a standard error of

Guidelines: Constructing a Confidence Interval for a Population Proportion In words ID the sample stats, n and x Find the point estimate Verify the sampling distribution of p(hat) can be approximated by the normal distribution. Find the critical zc that corresponds to the given level of confidence, c. Find the maximum error of estimate, E. Find the left and the right endpoints and form the confidence interval. Is and is ? Use a standard normal table. Left endpoint: Right endpoint: Interval:

Ex. 2: Constructing a Confidence interval for p Construct a 95% confidence interval for the proportion of American adults who say that their favorite sport is football. SOLUTION: Form example 1, , So, . Using n = 883, you can verify that the sampling distribution of can be approximated by the normal distribution. and

Ex. 2: Constructing a Confidence interval for p Using zc = 1.96, the maximum error of estimate is: The 95% confidence interval is as follows: Left Endpoint Right Endpoint So, with 95% confidence, you can say that the proportion of adults who say that footbal is their favorite sport is between 39.7% and 46.3%.

Opinion Polls The confidence level of 95% used in Example 2 is typical of opinion polls. The result; however, is usually not stated as a confidence interval. Instead the result of Example 2 would usually be stated as 43% with a margin of error of 3.3%.”

Ex. 3: Constructing a Confidence Interval for p The graph shown below is from a survey of 935 adults. Construct a 99% confidence interval for the proportion of adults who think that airplanes are the safest mode of transportation.

Solution: So with 99% confidence, you can say that the proportion of adults who think that airplanes are the safest mode of transportation is between 40.8% and 49.2% From the graph So, Using these values and the values n = 935 and zc = 2.575, the maximum error of estimate is: The 99% confidence inteval is as follows: Left Endpoint Right Endpoint

Increasing Sample Size to Increase Precision One way to increase the precision of the confidence interval without decreasing the level of confidence is to increase the sample size.

Insight – why 0.5? The reason for using 0.5 as values for p hat and q hat when no preliminary estimate is available is that these values yield a maximum value for the product In other words, if you don’t estimate thevalues of p hat and q hat, you must pay the penalty of using a larger sample.

Ex. 4: Determining a Minimum Sample Size You are running a political campaign and wish to estimate with 95% confidence, the proportion of registered voters, who will vote for your candidate. What is the minimum sample size needed if you are to accurately within 3% of the population proportion?

SOLUTION Because you do not have a preliminary estimate for p, use and . Using zc = 1.96, and E = 0.03, you can solve for n. Because n is a decimal, round up to the nearest whole number. So, at least 1068 registered voters should be included in the sample.

Assignment due Friday BOC. Assignment: pp. 280-282 #1-22 all