Chapter 5 Sampling and Surveys. Section 5.3 Sample Surveys in the Real World.

Slides:

Advertisements

Similar presentations

+ Sampling and Surveys Inference for Sampling The purpose of a sample is to give us information about alarger population. The process of drawing conclusions.

Advertisements

Sampling Methods.

* Students will be able to identify populations and samples. * Students will be able to analyze surveys to see if there is bias. * Students will be able.

CHAPTER 8: Producing Data: Sampling

Chapter 5 Producing Data

AP Statistics Chapter 5 Notes.

Chapter 12 Sample Surveys

CHAPTER 4 Designing Studies

Section 5.1. Observational Study vs. Experiment  In an observational study, we observe individuals and measure variables of interest but do not attempt.

Sampling Methods.

Sample Surveys Ch. 12. The Big Ideas 1.Examine a Part of the Whole 2.Randomize 3.It’s the Sample Size.

Chapter 5 Section 3 Part 1.  Often when we hear of a sample we do not know the truth behind the sampling process.  The whole truth about opinion polls.

Ch 4 - Designing Studies.

BPS - 5th Ed. Chapter 81 Producing Data: Sampling.

Chapter 4 Designing Studies

Sample Surveys.  The first idea is to draw a sample. ◦ We’d like to know about an entire population of individuals, but examining all of them is usually.

Population We are almost always interested in knowledge about a population. We would have little interest in samples if we could always ask everyone.

Chapter 12 Notes Surveys, Sampling, & Bias Examine a Part of the Whole: We’d like to know about an entire population of individuals, but examining all.

The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 4 Designing Studies 4.1 Samples and Surveys.

CHAPTER 8: Producing Data: Sampling

Section 5.1 Designing Samples Malboeuf AP Statistics, Section 5.1, Part 1 3 Observational vs. Experiment An observational study observes individuals.

CHAPTER 8: Producing Data Sampling ESSENTIAL STATISTICS Second Edition David S. Moore, William I. Notz, and Michael A. Fligner Lecture Presentation.

Statistics Section 2-3 Day 1 - Sampling in the Real World.

Designing Samples Chapter 5 – Producing Data YMS – 5.1.

AP Review #4: Sampling & Experimental Design. Sampling Techniques Simple Random Sample – Each combination of individuals has an equal chance of being.

Lecture # 6:Designing samples or sample survey Important vocabulary Experimental Unit: An individual person,animal object on which the variables of interest.

C HAPTER 5: P RODUCING D ATA Section 5.1 – Designing Samples.

Copyright © 2007 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Slide

Section 5.1 Designing Samples AP Statistics

AP STATISTICS LESSON AP STATISTICS LESSON DESIGNING DATA.

AP STATISTICS Section 5.1 Designing Samples. Objective: To be able to identify and use different sampling techniques. Observational Study: individuals.

Part III – Gathering Data

SECTION 4.1. INFERENCE The purpose of a sample is to give us information about a larger population. The process of drawing conclusions about a population.

Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.

I can identify the difference between the population and a sample I can name and describe sampling designs I can name and describe types of bias I can.

 An observational study observes individuals and measures variable of interest but does not attempt to influence the responses.  Often fails due to.

The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 4 Designing Studies 4.1 Samples and Surveys.

Chapter 3 Surveys and Sampling © 2010 Pearson Education 1.

Inference for Sampling. The purpose of a sample is to give usinformation about a larger population. The process of drawing conclusions abouta population.

5.3: SAMPLING. Errors in Sampling Sampling Errors- Errors caused by the act of taking a sample. Makes sample results inaccurate. Random Sampling Error.

Chapter 7 Data for Decisions. Population vs Sample A Population in a statistical study is the entire group of individuals about which we want information.

1. What is one method of data collection? 2. What is a truly random way to survey/sample people?

Chapter 4: Designing Studies

Status for AP Congrats! We are done with Part I of the Topic Outline for AP Statistics! (20%-30%) of the AP Test can be expected to cover topics from chapter.

The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 4 Designing Studies 4.1 Samples and Surveys.

Designing Studies In order to produce data that will truly answer the questions about a large group, the way a study is designed is important. 1)Decide.

1 Chapter 11 Understanding Randomness. 2 Why Random? What is it about chance outcomes being random that makes random selection seem fair? Two things:

SWBAT: Explain how undercoverage, nonresponse, and question wording can lead to bias in a sample survey. Do Now: An airline that wants to assess customer.

We’ve been limited to date being given to us. But we can collect it ourselves using specific sampling techniques. Chapter 12: Sample Surveys.

Chapter 4: Designing Studies... Sampling. Convenience Sample Voluntary Response Sample Simple Random Sample Stratified Random Sample Cluster Sample Convenience.

Plan for Today: Chapter 1: Where Do Data Come From? Chapter 2: Samples, Good and Bad Chapter 3: What Do Samples Tell US? Chapter 4: Sample Surveys in the.

Errors in Sampling Sampling Errors- Errors caused by the act of taking a sample. Makes sample results inaccurate. Random Sampling Error Errors caused by.

5.1: Designing Samples. Important Distinction Observational Study – observe individuals and measure variables but do not attempt to influence the responses.

Introduction/ Section 5.1 Designing Samples.  We know how to describe data in various ways ◦ Visually, Numerically, etc  Now, we’ll focus on producing.

MATH Section 6.1. Sampling: Terms: Population – each element (or person) from the set of observations that can be made Sample – a subset of the.

Chapter 5: Producing Data 5.1 – Designing Samples "An approximate answer to the right question is worth a good deal more than the exact answer to an approximate.

AP Statistics C5 D1 HW: p.285 #19-24 Quiz in 2 class days Obj: to choose a simple random sample Do Now: What is the difference between a sample and a population?

Section 5.1 Designing Samples

CHAPTER 4 Designing Studies

Sampling and Surveys How do we collect data? 8/20/2012.

Producing Data Chapter 5.

Unit 5 Notebook Pages 31 -.

WARM – UP Use LINE 5 of the random digit table. 30. The World Series.

Section 5.1 Designing Samples

Inference for Sampling

What do Samples Tell Us Variability and Bias.

10/18/ B Samples and Surveys.

EQ: What is a “random sample”?

Presentation transcript:

Chapter 5 Sampling and Surveys

Section 5.3 Sample Surveys in the Real World

Typical Pew Opinion Poll of 1000 people... Never answered phone 938 Answered but refused 678 Not eligible: no person aged at least 18,or language barrier 221 Incomplete interview 42 Complete interview 1000 Total called 2879

How sample surveys go wrong Errors in sampling Sampling errors - caused by the act of taking a sample Random sampling error - deviation between the sample statistic and the population parameter caused by chance in selecting a random sample (margin of error only includes this type of error) Nonsampling errors -not related to the act of selecting a sample

Random sampling error Can be controlled by choosing size of sample Bad Samples Voluntary response, convenient sample These methods can be avoided

Sampling Frame List from which we can draw a sample, ideally every individual in the population Undercoverage Occurs when some groups in the population are left out of the process of choosing the sample Example: Using telephone directories as a frame misses everyone with an unlisted number

Nonsampling errors Ca n plague even a census Include processing errors (mechanical task errors) Response error (lies, incorrect answer, lack of understanding, faulty memory) Nonresponse (person selected can't be reached or refuses to answer) - this is the most serious problem facing sample surveys!

What the margin of error doesn't say Announced margin of error covers only random sampling error!

Wording Questions Wording ALWAYS influences the answers! Questions can be slanted to favor one response over others This is another source of sampling error....

Sample design in the real world Goal: take an SRS from the population and use a statistic from your sample to estimate a population parameter Reality: it is very difficult to actually get an SRS from the population of interest!

Refining the process Stratified Random Sample Divide the sampling frame into distinct groups called strata (grade level, gender, lunch bell) Take a separate SRS in each stratum and combine these to make up the complete sample

Refining the process Systematic Sample Number each individual in the population Choose every nth (5th, or 10th, or 23rd) person

Refining the process Quota Sample Divide the population into smaller homogeneous groups based on some characteristic (gender, age, etc.) Choose proportionally from each group to reflect the same characteristic in the population

Good samples are probability samples Chosen by chance Must know what samples are possible and what chance each possible sample has SRS, Stratified Random Samples, Systematic Samples, and Quota Samples are all probability samples

Before you believe a poll, ask: Wh o carried out the survey? What was the population? How was the sample selected? How large was the sample? What was the response rate? How were the subjects contacted? When was the survey conducted? What were the exact questions asked?