Producing Data Designing Samples Experiments Deliberately change a variable in order to observe response Here you are actually INFLUENCING the response.

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

Objectives Estimate population means and proportions and develop margin of error from simulations involving random sampling. Analyze surveys, experiments,

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.

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

POPULATION- the entire group of individuals that we want information about SAMPLE- the part of the population that we actually examine in order to gather.

Chapter 1 Getting Started

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

Random Sampling and Introduction to Experimental Design.

Intro Stats Lesson 1.3 B Objectives: SSBAT classify different ways to collect data. SSBAT distinguish between different sampling techniques. Standards:

The 6 Sample Survey Methods September 26, So far, we have discussed two BAD methods… 1. Voluntary Response Method People who respond usually have.

1-3 Data Collection and Sampling Techniques Surveys are the most common method of collecting data. Three methods of surveying are: 1) Telephone surveys.

AP Statistics.  Observational study: We observe individuals and measure variables of interest but do not attempt to influence responses.  Experiment:

GREAT Day!!!. Producing Data Population – Entire group of individuals or objects that we want information about. Defined in terms of what we want to know.

Part III Gathering Data.

Collection of Data Chapter 4. Three Types of Studies Survey Survey Observational Study Observational Study Controlled Experiment Controlled Experiment.

Chapter 5: Producing Data “An approximate answer to the right question is worth a good deal more than the exact answer to an approximate question.’ John.

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.

Population and sample. Population: are complete sets of people or objects or events that posses some common characteristic of interest to the researcher.

Other Probability Sampling Methods

Chapter 1 Getting Started 1.1 What is Statistics?.

Data Collection: Sample Design. Terminology Observational Study – observes individuals and measures variables of interest but does not impose treatment.

Designing Samples Chapter 5 – Producing Data YMS – 5.1.

Sampling Methods. Probability Sampling Techniques Simple Random Sampling Cluster Sampling Stratified Sampling Systematic Sampling Copyright © 2012 Pearson.

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

Experiments Main role of randomization: Assign treatments to the experimental units. Sampling Main role of randomization: Random selection of the sample.

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.

Sampling Methods and Cautions

Notes 1.3 (Part 1) An Overview of Statistics. What you will learn 1. How to design a statistical study 2. How to collect data by taking a census, using.

Lecture 1 Stat Applications, Types of Data And Statistical Inference.

1. When I give you the signal, you will have 10 seconds to look at a slide and make a guess as to the average number of m&m’s per pile. Do not use pencil.

SAMPLING TECHNIQUES LECTURE - 2 GE 608 Experimental Methods and Analysis Oct 28, 2015 Muharrum 14, 1437.

Collection of Data Jim Bohan

Chapter 5 Sampling: good and bad methods AP Standards Producing Data: IIB4.

Data Collection and Experimental Design. Data Collection Methods 1. Observational study 2. Experiment 3. Simulation 4. Survey.

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

Other Sampling Methods I can distinguish a SRS from a stratified random sample or cluster sample. I can give advantages and disadvantages of each sampling.

Sampling technique  It is a procedure where we select a group of subjects (a sample) for study from a larger group (a population)

Probability Sampling. Simple Random Sample (SRS) Stratified Random Sampling Cluster Sampling The only way to ensure a representative sample is to obtain.

Sampling Sampling – the process of obtaining a sample from a population Simple Random Sampling – sample selected at random from a population in which every.

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

The population in a statistical study is the entire group of individuals about which we want information The population is the group we want to study.

Chapter 12 Vocabulary. Matching: any attempt to force a sample to resemble specified attributed of the population Population Parameter: a numerically.

SWBAT: Describe and create stratified & cluster random samples. Do Now: The residual plots from five different least squares regression lines are shown.

SWBAT: Identify and select a Simple Random Sample (SRS) Do Now: Complete the survey and the questions to follow.

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.

Chapter 1 Getting Started What is Statistics?. Individuals vs. Variables Individuals People or objects included in the study Variables Characteristic.

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.

Copyright © 2014, 2011 Pearson Education, Inc. 1 Chapter 13 Samples and Surveys.

Sect. 1-3 Experimental Design Objective: SWBAT learn how to design a statistical Study, How to collect data by taking a census using a sampling, using.

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

Experimental Design Data Collection Sampling Techniques.

Collecting Data Backbone of Statistics. It’s all about the Vocabulary!  Population: the entire group that we are interested in  Sample: some.

Formulation of the Research Methods A. Selecting the Appropriate Design B. Selecting the Subjects C. Selecting Measurement Methods & Techniques D. Selecting.

Unit 2 Review. Developing a Thesis A thesis is a question or statement that the research will answer When writing a thesis, ask: Is it specific? Are the.

Chapter 5 Data Production

Probability and Statistics

Statistics! Unit 8 Day 1.

Producing Data Chapter 5.

Do now- Pick the best solution

Statistics Unit 8 Day 2.

EQ: What is a “random sample”?

Surveys How to create one.

Probability and Statistics

Presentation transcript:

Producing Data Designing Samples

Experiments Deliberately change a variable in order to observe response Here you are actually INFLUENCING the response Only plausible way to show cause & effect You CAN control lurking variables to help minimize their effect

SRS (Simple Random Sample) A random sample where each individual has an equal opportunity to be chosen and each sample has an equal opportunity of being produced Random # TableCalculator Assign each item a # Given a starting pt, look for (__) digit #’s within the appropriate interval randInt(lowest#,highest#, # desired)

Pick 3 Random Citizens randInt(1,12,3)

Alternative Sampling Methods Stratified Sampling Divide the population into categories (strata) and select a random sample from each category Cluster Sampling Divide the population into categories (clusters), randomly select one or more categories, and select EVERYONE within the chosen categories.

Pick 3 Random Citizens We’ll group them by age Here are the groupings!! randInt(1,4,1)

Pick 3 Random Citizens We’ll group them by location. Here are the groupings!! randInt(1,4,1) But this is a little different

Stratified Sampling The students have been asked by Governor Martin O’Malley to survey the state of Maryland to determine the level of participation by teenagers in the state’s public school system. Describe 2 ways to design a stratified sample for this study. 1)Split the state into Counties (Strata). Assign a number to each individual in each county and take a random sample of n people from each county. PROBLEMS??? 2) Split the state into Zip Codes (Strata). Assign a number to each individual in each zip and take a random sample of n people from each one. PROBLEMS??? How would you change these to be Cluster Sampling?

Try This One Too!! Describe how I would collect a random sample of 15 students from this class of 50. SRS?, Stratified? Cluster?

Talking about the “People” Be careful when making inferences from a sample to the population Biggest Problem/Misuse In Stats OVERGENERALIZATION Collecting Data from “relatively” small sample sizes and making inferences about a population The Bigger Your Sample – The More Accurate Your Inferences. Get a BIG Sample!! At least 15; try for 40 or more if possible.