WARM – UP The campaign manager for a local candidate for city manager wants to determine if his candidate will win. He collected an SRS of 250 voters and.

Slides:



Advertisements
Similar presentations
How many movies do you watch? Does the CLT apply to means?  The Central Limit Theorem states that the more samples you take, the more Normal your.
Advertisements

Note 10 of 5E Statistics with Economics and Business Applications Chapter 7 Estimation of Means and Proportions Large-Sample Estimation.
Sampling Distributions (§ )
Chap 9-1 Statistics for Business and Economics, 6e © 2007 Pearson Education, Inc. Chapter 9 Estimation: Additional Topics Statistics for Business and Economics.
Chapter 7 Estimation: Single Population
WARM – UP Quiz Review An insurance company checks police records on 582 accidents selected at random. Teenagers were involved in 91 of them. a.) Find.
1/49 EF 507 QUANTITATIVE METHODS FOR ECONOMICS AND FINANCE FALL 2008 Chapter 9 Estimation: Additional Topics.
Review of normal distribution. Exercise Solution.
10.3 Estimating a Population Proportion
Chapter 7 Estimation: Single Population
ESTIMATING with confidence. Confidence INterval A confidence interval gives an estimated range of values which is likely to include an unknown population.
Many times in statistical analysis, we do not know the TRUE mean of a population of interest. This is why we use sampling to be able to generalize the.
Chapter 8: Confidence Intervals
Confidence Intervals (Chapter 8) Confidence Intervals for numerical data: –Standard deviation known –Standard deviation unknown Confidence Intervals for.
Many times in statistical analysis, we do not know the TRUE mean of a population of interest. This is why we use sampling to be able to generalize the.
Basic Business Statistics, 11e © 2009 Prentice-Hall, Inc. Chap 8-1 Confidence Interval Estimation.
Population All members of a set which have a given characteristic. Population Data Data associated with a certain population. Population Parameter A measure.
PROBABILITY (6MTCOAE205) Chapter 6 Estimation. Confidence Intervals Contents of this chapter: Confidence Intervals for the Population Mean, μ when Population.
Normal Distributions Z Transformations Central Limit Theorem Standard Normal Distribution Z Distribution Table Confidence Intervals Levels of Significance.
Statistical Inference: Making conclusions about the population from sample data.
General Confidence Intervals Section Starter A shipment of engine pistons are supposed to have diameters which vary according to N(4 in,
STA291 Statistical Methods Lecture 18. Last time… Confidence intervals for proportions. Suppose we survey likely voters and ask if they plan to vote for.
Section 6.3 Confidence Intervals for Population Proportions Larson/Farber 4th ed1.
STA291 Statistical Methods Lecture 17. Bias versus Efficiency 2 AB CD.
Confidence Intervals Target Goal: I can use normal calculations to construct confidence intervals. I can interpret a confidence interval in context. 8.1b.
Chapter 10: Confidence Intervals
Section Estimating a Proportion with Confidence Objectives: 1.To find a confidence interval graphically 2.Understand a confidence interval as consisting.
What is a Confidence Interval?. Sampling Distribution of the Sample Mean The statistic estimates the population mean We want the sampling distribution.
Confidence Interval for a population mean Section 10.1.
Review Normal Distributions –Draw a picture. –Convert to standard normal (if necessary) –Use the binomial tables to look up the value. –In the case of.
Confidence Interval Estimation For statistical inference in decision making: Chapter 9.
Vocab Normal, Standard Normal, Uniform, t Point Estimate Sampling distribution of the means Confidence Interval Confidence Level / α.
INFERENCE Farrokh Alemi Ph.D.. Point Estimates Point Estimates Vary.
10.1 – Estimating with Confidence. Recall: The Law of Large Numbers says the sample mean from a large SRS will be close to the unknown population mean.
Topic 12 Sampling Distributions. Sample Proportions is determined by: = successes / size of sample = X/n If you take as SRS with size n with population.
Lesson 7 Confidence Intervals: The basics. Recall is the mean of the sample and s is the standard deviation of the sample. Where μ is the mean of the.
And distribution of sample means
Inference: Conclusion with Confidence
CHAPTER 8 Estimating with Confidence
Chapter 6 Confidence Intervals.
Chapter 6 Confidence Intervals.
Confidence Intervals with proportions a. k. a
Statistical Estimation
Inference: Conclusion with Confidence
WARM - UP Find the P-Value for t ≥ 3.05 with a sample of 19.
Chapter 8: Estimating With Confidence
Ch. 8 Estimating with Confidence
Chapter 8: Estimating with Confidence
Unit 8: Estimating with Confidence
Estimating p in the Binomial Distribution
CHAPTER 20: Inference About a Population Proportion
Introduction to Inference
WARM UP 1. A national investigation reveals that 24% of year olds get traffic tickets. You collect a random sample of year olds.
WARM - UP 1. How do you interpret a Confidence Interval?
Confidence Intervals for a Population Mean, Standard Deviation Known
Chapter 8: Estimating with Confidence
WARM UP ONE SAMPLE T-Interval
EXAMPLE: The weight of a can of Coca Cola is supposed to have mean = 12 oz with std. dev.= 0.82 oz. The product is declared underweight if it weighs.
Chapter 6 Confidence Intervals.
WARM – UP Quiz Review An insurance company checks police records on 582 accidents selected at random. Teenagers were involved in 91 of them. a.) Find.
WARM - UP The following represents snowfall amounts for 8 random winters in Detroit. 78” 130” 140” 120” 108” 120” 156” 101” 1. Fill in all four.
Confidence Interval for a Population mean ( known)
Confidence Intervals with Proportions
Estimating p in the Binomial Distribution
Chapter 8: Estimating With Confidence
Sampling Distributions (§ )
8.2 Estimating a Population Proportion
Chapter 8: Confidence Intervals
Chapter 7 Estimation: Single Population
How Confident Are You?.
Presentation transcript:

WARM – UP The campaign manager for a local candidate for city manager wants to determine if his candidate will win. He collected an SRS of 250 voters and then constructed a 95% Confidence interval from the sample proportion of 53% and margin of error of 3.2%. Interpret the margin of error, m. Calculate the two values of the interval ( ). Interpret the 95% Conf. Interval constructed in (b). ) The true proportion of votes the candidate will receive will be within 3.2% of the estimate of 53%. (0.53 ± 0.032) = (49.8%, 56.2%) We are 95% confident (sure) that the true proportion of votes the candidate will receive is between 49.8% and 56.2% of the votes.

QUIZ REVIEW Describe a Sampling Distribution for: a.) Proportions b.) Means Verify all three assumptions for: a.) Proportions (see Distribution Sheet) b.) Means 3. Find the probability for: a.) Proportions b.) Means Central Limit Theorem- Calculate margin of error: Calculate a confidence Interval.

Rogers was interested in determining the true proportion of residents opposed to a city dump being placed in the neighborhood. He collected an SRS of 200 residents and found 86% were opposed. Calculate and interpret the 95% Confidence Interval. 95% .835 .885 .910 .810 .785 .935 .86 I am 95% Confident that the true population proportion of residents opposed to the new dump is between 81.0% and 91.0%.

95% Confidence Interval = 90% Confidence Interval = Critical Value – is the number z* with probability p lying to the right under the standard normal. This is called the Upper p critical value. C% P P -z* z* where z* is the upper (1 – C)/2 critical value found by: z* = | INVNORM( (1 – C)/2 ) | or by Table What are the z* for: 95% Confidence Interval = 90% Confidence Interval = 99% Confidence Interval = z* = 1.960 z* = 1.645 z* = 2.576

company vehicles are fuel efficient? EXAMPLE: A large national company wants to keep costs down so it purchases fuel efficient vehicles. An SRS of 40 vehicles are selected and it is found that 28 of them are classified “Fuel Efficient”, what percent of the entire company vehicles are fuel efficient? 1. Estimate the population parameter with a 90% Confidence Interval and Interpret it. 2. Estimate the population parameter with a 99% Confidence Interval and Interpret it. We can be 90% confident that the true population proportion of fuel efficient vehicles in the company is between 58.1% and 81.9%.

company vehicles are fuel efficient? EXAMPLE: A large national company wants to keep costs down so it purchases fuel efficient vehicles. An SRS of 40 vehicles are selected and it is found that 28 of them are classified “Fuel Efficient”, what percent of the entire company vehicles are fuel efficient? 2. Estimate the population parameter with a 99% Confidence Interval and Interpret it. We can be 99% confident that the true population proportion of fuel efficient vehicles in the company is between 51.3% and 88.7%.

HW: PAGE 448: 22-25 a) b.) I am 90% confident that the true proportion of live births for women under 40 is between 0.188 & 0.286. c.) In Repeated Sampling, 90% of constructed intervals will capture the true proportion of live births. d.) No! 25% is in the interval.

HW: PAGE 448: 22-25

The proportion of married men in their 20’s has changed since the 1950’s. To estimate today’s proportion, a random sample of 60 men in their 20’s was taken to find: Construct a 95% Confidence interval to estimate the percent of married men in their 20’s. Construct a 99.7% Confidence interval to estimate the percent of married men in their 20’s.

CONFIDENCE INTERVALS Confidence Level – A level C confidence interval for a parameter is an interval computed from sample data by a method that in repeated sampling has probability C of producing an interval containing the true value of the parameter. True Parameter An 85% Confidence Level

Collected by an SRS - Stated Approximately Normal by: Large n & C.L.T. EXAMPLE: The weight of a bag of Potato Chips is supposed to have mean = 20.4 oz with std. dev.= 1.24 oz. The product is declared underweight if it weighs less than 18 oz which is stated on the bag. With a SRS sample of 34 bags find the probability that the Product will be underweight. Collected by an SRS - Stated Approximately Normal by: Large n & C.L.T.