Stratified Sampling Lecture 8 Section 2.6 Wed, Jan 28, 2004.

Slides:



Advertisements
Similar presentations
Stratified Sampling Module 3 Session 6.
Advertisements

Categories of Sampling Techniques n Statistical ( Probability ) Sampling: –Simple Random Sampling –Stratified Random Sampling –Cluster Random Sampling.
Chapter 17 Additional Topics in Sampling
Chapter 8 Selecting Research Participants. DEFINING A POPULATION BY A RANDOM NUMBERS TABLE  TABLE 8.1  Partial Page of a Random Numbers Table  ____________________________________________________________________________.
5.10: Stratification after Selection of Sample – Post Stratification n Situations can arise in which we cannot place sampling units into their correct.
STRATIFIED SAMPLING DEFINITION Strata: groups of members that share common characteristics Stratified sampling: the population is divided into subpopulations.
Stratified Random Sampling. A stratified random sample is obtained by separating the population elements into non-overlapping groups, called strata Select.
Sampling Moazzam Ali.
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.
Data Collection Methods. In a population there is a parameter of interest whose value is unknown. We use a sample estimator to estimate the value of this.
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.
Other Sampling Methods Lecture 8 Sections 2.6 – 2.7 Tue, Jan 29, 2008.
CHAPTER 12 DETERMINING THE SAMPLE PLAN. Important Topics of This Chapter Differences between population and sample. Sampling frame and frame error. Developing.
LECTURE 3 SAMPLING THEORY EPSY 640 Texas A&M University.
Chapter 10– Estimating Voter Preferences Statistics is the science of making decisions in the face of uncertainty. We use information gathered from a sample.
Bias and Variability Lecture 38 Section 8.3 Wed, Mar 31, 2004.
Sampling Methods. Probability Sampling Techniques Simple Random Sampling Cluster Sampling Stratified Sampling Systematic Sampling Copyright © 2012 Pearson.
Math 145 September 20, Review Methods of Acquiring Data: 1. Census – obtaining information from each individual in the population. 2. Sampling –
Experiments Main role of randomization: Assign treatments to the experimental units. Sampling Main role of randomization: Random selection of the sample.
Poverty Estimation in Small Areas Agne Bikauskaite European Conference on Quality in Official Statistics (Q2014) Vienna, 3-5 June 2014.
Elementary Statistics (Math 145) September 8, 2010.
Chapter 1: The Nature of Statistics 1.4 Other Sampling Designs.
Sampling Distributions
Math 341 January 23, Outline 1. Recap 2. Other Sampling Designs 3. Graphical methods.
Chapter Eleven Sampling: Design and Procedures Copyright © 2010 Pearson Education, Inc
1 Chapter 2: Sampling and Surveys. 2 Random Sampling Exercise Choose a sample of n=5 from our class, noting the proportion of females in your sample.
Copyright © 2008 Pearson Education, Inc.. Slide 1-2 Chapter 1 The Nature of Statistics Section 1.3 Other Sampling Designs.
Systematic Sampling Lecture 9 – Part 1 Sections 2.8 Wed, Jan 30, 2008.
Math 145 January 29, Outline 1. Recap 2. Sampling Designs 3. Graphical methods.
Chapter 12 Vocabulary. Matching: any attempt to force a sample to resemble specified attributed of the population Population Parameter: a numerically.
Lecture 4 Forestry 3218 Avery and Burkhart, Chapter 3 Shiver and Borders, Chapter 5 Forest Mensuration II Lecture 4 Stratified Random Sampling.
Statistics Definitions Part 2. Representative Sample For a sample to be representative of a population, it must possess the same characteristics as the.
Chapter 1 Getting Started What is Statistics?. Individuals vs. Variables Individuals People or objects included in the study Variables Characteristic.
1. 2 DRAWING SIMPLE RANDOM SAMPLING 1.Use random # table 2.Assign each element a # 3.Use random # table to select elements in a sample.
Elementary Statistics (Math 145) June 19, Statistics is the science of collecting, analyzing, interpreting, and presenting data. is the science.
Bias and Variability Lecture 27 Section 8.3 Wed, Nov 3, 2004.
Math 145 June 19, Outline 1. Recap 2. Sampling Designs 3. Graphical methods.
Ing. Martina Majorová, FEM SUA Statistics Lecture 4 – Data sampling & Data sorting.
Discrete Math Section 17.5 Recognized types of sampling procedures and estimate population characteristics based on samples The purpose of sampling is.
Other Sampling Methods Lecture 7 Sections 2.6 – 2.8 Tue, Jan 31, 2006.
Other Sampling Methods
Math 145 May 27, 2009.
Section 4.2 Random Sampling.
Math 145 June 25, 2013.
Other Sampling Methods
Math 145 January 23, 2007.
Sampling: Stratified vs Cluster
Turn in the Margin of Error worksheet.
Statistics Section 1.2 Identify different methods for selecting a sample Simulate a random process Review: quantitative and qualitative variables, population.
Sampling Distribution
Sampling Distribution
Other Sampling Methods
Other types of samples…
Selecting Research Participants
Math 145.
Other Sampling Methods
STAT 145.
Math 145 January 28, 2015.
The Language of Sampling
Section 2.2: Sampling.
STAT 245.
Sampling Distribution of a Sample Proportion
Math 145 September 6, 2005.
Math 145 September 5, 2007.
Math 145 September 3, 2008.
Math 145 May 23, 2016.
CS639: Data Management for Data Science
EQ: What is a “random sample”?
Understanding Observational Studies
Other Sampling Methods
Presentation transcript:

Stratified Sampling Lecture 8 Section 2.6 Wed, Jan 28, 2004

Stratified Random Sampling Stratified random sample – A sample selected by Stratified random sample – A sample selected by First, dividing the population into mutually exclusive groups, or strata, First, dividing the population into mutually exclusive groups, or strata, Then, taking a simple random sample from each stratum. Then, taking a simple random sample from each stratum.

Why Stratified Samples? We may be genuinely interested in the differences between the strata. We may be genuinely interested in the differences between the strata. By taking samples from each stratum, we can measure those differences. By taking samples from each stratum, we can measure those differences. For example, pollsters studying elections routinely stratify their samples by gender and ethnic group. For example, pollsters studying elections routinely stratify their samples by gender and ethnic group.

Why Stratified Samples? It is often the case that the variability within a stratum is much less than the variability between strata. It is often the case that the variability within a stratum is much less than the variability between strata. If that is so, then we can get a much better estimate of the population parameter than if we took one random sample from the entire population. If that is so, then we can get a much better estimate of the population parameter than if we took one random sample from the entire population.

Let’s Do It! Let’s do it! 2.7 – Stratified Random Sampling. Let’s do it! 2.7 – Stratified Random Sampling. Substitute “freshman” for “female” and “upperclassman” for “male.” Substitute “freshman” for “female” and “upperclassman” for “male.” Substitute “average number calls to parents per month” for “average number of haircuts per year.” Substitute “average number calls to parents per month” for “average number of haircuts per year.”

Assignment Page 112: Exercises 25 – 34. Page 112: Exercises 25 – 34.