Other Sampling Methods

Slides:

Advertisements

Similar presentations

Introduction Simple Random Sampling Stratified Random Sampling

Advertisements

Sampling A population is the total collection of units or elements you want to analyze. Whether the units you are talking about are residents of Nebraska,

Types of Sampling. Some Vocabulary  Homogeneous groups: All members of the group have a characteristic that is the same.  Heterogeneous groups: all.

Categories of Sampling Techniques n Statistical ( Probability ) Sampling: –Simple Random Sampling –Stratified Random Sampling –Cluster Random Sampling.

Sampling ADV 3500 Fall 2007 Chunsik Lee. A sample is some part of a larger body specifically selected to represent the whole. Sampling is the process.

STRATIFIED SAMPLING DEFINITION Strata: groups of members that share common characteristics Stratified sampling: the population is divided into subpopulations.

Sampling Moazzam Ali.

Sullivan – Fundamentals of Statistics – 2 nd Edition – Chapter 1 Section 3 – Slide 1 of 28 Chapter 1 Section 3 Other Effective Sampling Methods.

Planning Research Part 1 Method, Participants, Instruments & Ethics Kathy-ann Hernandez, Ph. D. Spring 2007.

Under the Guidance of Dr. ADITHYA KUMARI H. Associate Professor DOS in Library and Information Science University of Mysore Mysore By Poornima Research.

Other Sampling Methods Lecture 8 Sections 2.6 – 2.7 Tue, Jan 29, 2008.

LECTURE 3 SAMPLING THEORY EPSY 640 Texas A&M University.

Sampling Methods.

Chapter 10– Estimating Voter Preferences Statistics is the science of making decisions in the face of uncertainty. We use information gathered from a sample.

MDM4U – Mathematics of Data Management

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

BUS216 Spring  Simple Random Sample  Systematic Random Sampling  Stratified Random Sampling  Cluster Sampling.

Elementary Statistics (Math 145) September 8, 2010.

Chapter 1: The Nature of Statistics 1.4 Other Sampling Designs.

Math 341 January 23, Outline 1. Recap 2. Other Sampling Designs 3. Graphical methods.

Copyright © 2008 Pearson Education, Inc.. Slide 1-2 Chapter 1 The Nature of Statistics Section 1.3 Other Sampling Designs.

Independent Samples: Comparing Proportions Lecture 37 Section 11.5 Tue, Nov 6, 2007.

Sampling HMS 320 Spring Why sample? Why not survey or collect data from the whole population?

Math 145 January 29, Outline 1. Recap 2. Sampling Designs 3. Graphical methods.

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

Statistics Definitions Part 2. Representative Sample For a sample to be representative of a population, it must possess the same characteristics as the.

Sullivan – Statistics: Informed Decisions Using Data – 2 nd Edition – Chapter 1 Section 3 – Slide 1 of 28 Chapter 1 Section 3 Other Effective Sampling.

Sampling Sampling Distributions. Sample is subset of population used to infer something about the population. Probability – know the likelihood of selection.

Other Sampling Methods Lecture 7 Sections 2.6 – 2.8 Tue, Jan 31, 2006.

Sampling Sections 1.2 & 1.3. Objectives Distinguish between an observational study and an experiment Learn and be able to obtain and distinguish between.

Other Sampling Methods

Math 145 May 27, 2009.

Section 4.2 Random Sampling.

Arrangements or patterns for producing data are called designs

Math 145 June 25, 2013.

Other Sampling Methods

Statistics – Chapter 1 Data Collection

Math 145 January 23, 2007.

Types of Sampling.

Statistics Section 1.2 Identify different methods for selecting a sample Simulate a random process Review: quantitative and qualitative variables, population.

Who do I ask, what do I ask them, what does that tell me?

Arrangements or patterns for producing data are called designs

جمعیت –نمونه –روشهای نمونه گیری دکتر محسن عسکرشاهی دکترای آمار زيستی

The Language of Sampling

1.2 Sampling LEARNING GOAL

Observational Studies, Experiments, and Simple Random Sampling

Other Sampling Methods

Selecting Research Participants

Math 145 January 28, 2015.

Random Samples Random digit table

Sampling Methods.

Simple Random Sampling

§2.3: Sampling Methods.

Independent Samples: Comparing Proportions

Who are the Subjects? Intro to Sampling

Lecture 10 Sections 4.2 – 4.3 Objectives: Obtaining Data

Math 145 September 6, 2005.

Math 145 September 3, 2008.

Math 145 May 23, 2016.

Section 9.2: Sample Proportions

CS639: Data Management for Data Science

EQ: What is a “random sample”?

Surveys How to create one.

Sampling Methods and the Central Limit Theorem

Other Sampling Methods

Presentation transcript:

Other Sampling Methods Lecture 8 Sections 2.6 Tue, Sep 4, 2007

Stratified Random Sampling Stratified random sample

Stratified Random Sampling Normally the members within each stratum share a common characteristic that they do not share with members of the other strata. That is, each stratum is homogeneous. Male vs. female. Resident vs. non-resident.

Stratified Random Sampling The population

Stratified Random Sampling The strata The population

Stratified Random Sampling One stratum The population

Stratified Random Sampling One stratum Another stratum The population

Stratified Random Sampling A simple random sample from this stratum The population

Stratified Random Sampling A simple random sample from this stratum A simple random sample from this stratum The population

Stratified Random Sampling Simple random samples from all strata The population

Stratified Random Sampling The stratified random sample The population

Example Let the population be Andrea, Barry, Chantal, Dean, Erin, Felix, Gabrielle, and Humberto. Choose a stratified sample of size n = 4, where the strata are the two sexes. Is the sample representative with regard to sex?

Why Stratified Samples? If we know the proportion of the population that each group comprises, then we increase our chances of getting a representative sample by using a stratified sample.

Strata vs. Populations We may be genuinely interested in the differences among the strata. For example, pollsters studying elections routinely categorize their samples by gender, and ethnic group, party affiliation, etc. However, in that case, the strata are better viewed as distinct populations.