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

Slides:



Advertisements
Similar presentations
AP Statistics Section 5.1 B More on Sampling. Methods for sampling from large populations spread out over a wide area are usually more complex than an.
Advertisements

Chapter 7: Data for Decisions Lesson Plan
* 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.
Section 5.1. Observational Study vs. Experiment  In an observational study, we observe individuals and measure variables of interest but do not attempt.
If you have your Parent Letter signed, please return the bottom portion. Scissors are on my desk. Please get out materials for notes.
5.1 Designing Samples.  Differentiate between an observational study and an experiment  Learn different types of sampling techniques  Use a random.
Chapter 5 Data Production
BPS - 5th Ed. Chapter 81 Producing Data: Sampling.
AP Statistics Section 5.1 Designing Samples. In an observational study, we simply observe individuals and measure variables, but we do not attempt to.
AP Statistics Chapter 5. Class Survey 1. Are you male or female? 2. How many brothers or sisters do you have? 3. How tall are you in inches to the nearest.
Section 1 Part 1. Samples vs Population  Benefits of getting data from the entire population….  You can draw a conclusion about the entire population….more.
Pg Exploratory data analysis describes what data say by using graphs and numerical summaries. What if we want to ask a large group of individuals.
AP Statistics.  Observational study: We observe individuals and measure variables of interest but do not attempt to influence responses.  Experiment:
Aim: What is a sample design? Chapter 3.2 Sampling Design.
CHAPTER 8: Producing Data: Sampling
Section 2-1 Samples, Good and Bad. Remember: We select a sample in order to get information about some population (entire group of individuals about which.
Chapter 7: Data for Decisions Lesson Plan Sampling Bad Sampling Methods Simple Random Samples Cautions About Sample Surveys Experiments Thinking About.
Population vs. Sample The entire group of individuals that we want information about is called the population. A sample is a part of the population that.
Section 5.1 Designing Samples Malboeuf AP Statistics, Section 5.1, Part 1 3 Observational vs. Experiment An observational study observes individuals.
Section 5.1 Continued.  A simple random sample (SRS) of size n contains n individuals from the population chosen so that every set of n individuals has.
Data Collection: Sample Design. Terminology Observational Study – observes individuals and measures variables of interest but does not impose treatment.
CHAPTER 8: Producing Data Sampling ESSENTIAL STATISTICS Second Edition David S. Moore, William I. Notz, and Michael A. Fligner Lecture Presentation.
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.
Conducting A Study Designing Sample Designing Experiments Simulating Experiments Designing Sample Designing Experiments Simulating Experiments.
Lecture # 6:Designing samples or sample survey Important vocabulary Experimental Unit: An individual person,animal object on which the variables of interest.
A Survey is a study of one or more characteristics of a group. A Survey is a study of one or more characteristics of a group.
C HAPTER 5: P RODUCING D ATA Section 5.1 – Designing Samples.
Section 5.1 Designing Samples AP Statistics
BY: Nyshad Thatikonda Alex Tran Miguel Suarez. How to use this power point 1) Click on the box with the number. Best to click on the black part and not.
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
Lecture PowerPoint Slides Basic Practice of Statistics 7 th Edition.
Chapter 5 Sampling: good and bad methods AP Standards Producing Data: IIB4.
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.
Get out homework. Get out notes.. SECTION 5.1 CONTINUED Designing Samples.
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.
Chapter 5 Sampling and Surveys. Section 5.1 Samples, Good and Bad.
1. What is one method of data collection? 2. What is a truly random way to survey/sample people?
Chapter 5 Sampling and Surveys. Section 5.3 Sample Surveys in the Real World.
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.
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:
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.
Producing Date: Sampling Chapter 8. Group Task Your group is going to run a study on the effects of cell phones and students’ grades here at Spring- Ford.
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.
Chapter 5 Data Production
Statistical Reasoning – April 14, 2016
Section 5.1 Designing Samples
Chapter 5 Producing Data 5.1 Designing Samples
Section 5.1 Designing Samples
Producing Data Chapter 5.
WARM – UP Use LINE 5 of the random digit table. 30. The World Series.
Warm Up Imagine you want to conduct a survey of the students at Leland High School to find the most beloved and despised math teacher on campus. Among.
Chapter 5 Producing Data
Section 5.1 Designing Samples
Chapter 5: Producing Data
5.1 – Designing Samples.
Chapter 5: Producing Data
Chapter 5 Producing Data
Sample Design Section 4.1.
Chapter 3 producing data
Designing Samples Section 5.1.
Presentation transcript:

5.1: Designing Samples

Important Distinction Observational Study – observe individuals and measure variables but do not attempt to influence the responses. Experiment – deliberately impose some treatment on individuals in order to observe responses.

Designing Samples Population – entire group of individuals we want information about. Sample – part of the population we actually examine. Samples are used due to constraints such as time, cost, and inconvenience.

Census vs. Sampling Census – contacting every individual in the entire population. Sampling – studying a part in order to gain information about the whole.

Sampling Methods Voluntary Response Sample – people who choose themselves by responding to a general appeal (question, etc.). Bias - those with strong (especially negative) opinions are most likely to respond. Remember Ann Landers? Write-in, Call-in, and online polls are not very reliable! Convenience Sample – choosing individuals who are easiest to reach. Bias – Mall samples are convenient. However, they are more likely to include teenagers, retirees, and wealthier segments of the population.

REAL ESTATE DEVELOPMENT PROJECT

What is BIAS? Bias occurs when a sampling method systematically favors certain outcomes. “Personal Choice” (by a responder to a VRS or the interviewer of a CS) produces bias. The statistician’s remedy? CHANCE!

I. Simple Random Samples Simple Random Sample (SRS) – every member of a population has an equal chance of being selected. Ex) Names in a hat (population) are drawn out with in a handful (sample). NOTE: larger random samples give more accurate results than smaller samples. Random Digits Table (Table B: Back of Book) Each entry is equally likely to be any of the 10 digits 0 through 9. Entries are independent of each other.

Using Table B DPS would like to interview a sample of 5 students to find ways to improve teacher quality. To avoid bias, DPS will use a SRS of size 5. Steps: Label: Give each student a numerical label. Two digits are needed in our class. For example, 01 to 26. Table B: Enter anywhere. Let’s try line 130.    Students 05, 16, 17, 20, 19 are selected  It’s good practice to start at a different row every time you use Table B

If only I had my Table B…

TI Alternative MATH, PRB, randInt(1,26), hit ENTER five times ENTER again if you get repeats MATH, PRB, randInt(1,26,5), ENTER Works well unless you get repeats

Other Sampling Methods Probability Sample – a sample chosen by chance The use of chance to select the sample is the ESSENTIAL principle of statistical sampling. Stratified Random Sample - First, divide the population into strata (groups of individuals) that are similar in some way. Next, choose a separate SRS in each stratum and combine to for the full sample. Ex) Divide a population of high schools into public, Catholic, and other private schools

…Continued Cluster Sampling – First, divide the population into groups, or clusters. Next, clusters are randomly selected. ALL individuals in the chosen clusters are selected for the sample. Ex) Do students feel they have enough time for AP Statistics free response questions?  Randomly select a few schools from a comprehensive list featuring every school that administers the AP exam.  Every student at the selected schools is asked about the time limits.  The students interviewed would constitute a cluster sample.

Take Caution… Undercoverage occurs when some groups are left out of the sample selection process. Household surveys miss the homeless, inmates, and students in dormitories. Telephone polls miss the 8% of homes without residential lines. Nonresponse occurs when a selected individual can’t be contacted or does not cooperate.

…More Caution Examples of Response Bias Respondents may lie if asked about illegal or unpopular behavior. In a recent poll, 72% said they voted when just 56% actually did vote. An interviewer’s race or gender may influence responses regarding racism or sexism. Faulty memories “Telescoping” Example – “Have you visited a dentist in the last 6 months?” will often elicit a “Yes” from someone who went 8 months ago.

…More Caution The Wording of Questions is the most important influence on the answers given to a sample survey. Ex) 1992 Opinion Poll by American Jewish Commission “Does it seem possible or does it seem impossible to you that the Nazi extermination of the Jews never happened?”  22% responded “possible” “Does it seem possible to you that the Nazi extermination of Jews never happened, or do you feel certain that it happened?”  1% responded “possible”

Before You Trust a Poll… Know the… Exact questions asked Rate of nonresponse Date and method of the survey