STAT E100 Section Week 4 - Sampling. Review  Knowing how to read SPSS Output  Email addresses  Sample vs. Population  Organizing the terms in your.

Slides:



Advertisements
Similar presentations
Explaining the parts of an experiment
Advertisements

+ Sampling and Surveys Inference for Sampling The purpose of a sample is to give us information about alarger population. The process of drawing conclusions.
Designing Experiments
Sampling. Basic Terms Research units – subjects, participants Population of interest (all humans?) Accessible population – those you can actually try.
Section 1.3 Experimental Design © 2012 Pearson Education, Inc. All rights reserved. 1 of 61.
Section 1.3 Experimental Design.
Experimental Design Statistics Introduction Remember, population and sample Samples –1523 randomly chosen voters –6 Black capped chickadees –The.
Correlational Research
1.4 -Design of Experiments Objective: To understand the various types of experimental designs and techniques.
1. Identify the variable(s) of interest (the focus) and the population of the study. 2. Develop a detailed plan for collecting data. Make sure sample.
Chapter 12 Sample Surveys
The Practice of Statistics
Math 161 Spring 2008 Lecture 2 Chapter 2 Samples, Good and Bad
STRATIFIED SAMPLING DEFINITION Strata: groups of members that share common characteristics Stratified sampling: the population is divided into subpopulations.
Chapter 13 Experiments and Observational Studies.
Chapter 1 Getting Started
Chapter 4 Gathering data
SAMPLING:REQUIREMENTS OF A GOOD SAMPLE
Chapter 7: surveys.
Producing Data: Sampling BPS - 5th Ed.Chapter 81.
CHAPTER 8 Producing Data: Sampling BPS - 5TH ED.CHAPTER 8 1.
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.
1 Stat 1510 Statistical Thinking & Concepts Producing Data: Sampling.
Research Strategies, Part 2
Experimental Design 1 Section 1.3. Section 1.3 Objectives 2 Discuss how to design a statistical study Discuss data collection techniques Discuss how to.
Chapter 4 Designing Studies
 Collecting Quantitative  Data  By: Zainab Aidroos.
1-3 Data Collection and Sampling Techniques Surveys are the most common method of collecting data. Three methods of surveying are: 1) Telephone surveys.
Aim: What is a sample design? Chapter 3.2 Sampling Design.
Chapter 21 Samples, Good and Bad. Chapter 22 Thought Question 1 Popular magazines often contain surveys that ask their readers to answer questions about.
Producing Data Designing Samples Experiments Deliberately change a variable in order to observe response Here you are actually INFLUENCING the response.
Individuals are selected so that all individuals are equally likely to be selected Example: 1. Generate a list of student ID numbers for all students.
Copyright © 2015, 2012, and 2009 Pearson Education, Inc. 1 Chapter Introduction to Statistics 1.
Chapter 41 Sample Surveys in the Real World. Chapter 42 Thought Question 1 (from Seeing Through Statistics, 2nd Edition, by Jessica M. Utts, p. 14) Nicotine.
MDM4U - Collecting Samples Chapter 5.2,5.3. Why Sampling? sampling is done because a census is too expensive or time consuming the challenge is being.
Agresti/Franklin Statistics, 1 of 56  Section 4.3 What Are Good Ways and Poor Ways to Experiment?
Deciding what and how to measure
Chapter 1 Getting Started 1.1 What is Statistics?.
Study Session Experimental Design. 1. Which of the following is true regarding the difference between an observational study and and an experiment? a)
BPS - 5th Ed. Chapter 81 Producing Data: Sampling.
1. Identify the variable(s) of interest (the focus) and the population of the study. 2. Develop a detailed plan for collecting data. Make sure sample.
FPP Chapter 19 Surveys. General Idea Parameter Statistic Inference Sample Population.
Experiments Main role of randomization: Assign treatments to the experimental units. Sampling Main role of randomization: Random selection of the sample.
Business and Economic Statistics: Stratified and Clustered Sampling
Section 1-3 Data Collection and Sampling Techniques.
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.
CHAPTER 3 REVIEW Please note this is not meant to be a complete review. Read the chapter and review the vocabulary along with the concepts presented.
Chapter 21 Samples, Good and Bad. Chapter 22 Thought Question 1 Popular magazines often contain surveys that ask their readers to answer questions about.
Definition Word Search. Find definitions in the following places 1.Need a Schedule Change? 2.Where would you go to play hoops? 3.Where would you go to.
Section 1.3 Experimental Design.
1 STAT 500 – Statistics for Managers STAT 500 Statistics for Managers.
Chapter 12 Vocabulary. Matching: any attempt to force a sample to resemble specified attributed of the population Population Parameter: a numerically.
Chapter 2 Lesson 2.2b Collecting Data Sensibly 2.2: Sampling.
Statistics Definitions Part 2. Representative Sample For a sample to be representative of a population, it must possess the same characteristics as the.
Sample Design AP Statistics. Quick definitions Response Variable / Dependent Variable (the output) Explanatory Variables /Independent Variables (input)
Chapter 4: Designing Studies... Sampling. Convenience Sample Voluntary Response Sample Simple Random Sample Stratified Random Sample Cluster Sample Convenience.
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.
Section 1.3 Objectives Discuss how to design a statistical study Discuss data collection techniques Discuss how to design an experiment Discuss sampling.
1.3 Experimental Design. What is the goal of every statistical Study?  Collect data  Use data to make a decision If the process to collect data is flawed,
Bell Ringer Using any and all available resources, in your own words define the following: 1. Convenience 2. Random 3. Stratified 4. Systematic 5. Cluster.
Topic 2: Types of Statistical Studies
Other Sampling Methods
Sampling: Stratified vs Cluster
DS1 – Statistics and Society, Data Collection and Sampling
Principles of Experiment
Other Sampling Methods
MATH 2311 Section 6.1.
Basic Practice of Statistics - 5th Edition Producing Data: Sampling
Presentation transcript:

STAT E100 Section Week 4 - Sampling

Review  Knowing how to read SPSS Output  addresses  Sample vs. Population  Organizing the terms in your own thoughts

Review Ŷ = X value of extravert

Key Concepts:  Correlation ≠ Causation

Key Concepts:  Types of Association (causation vs. non-causal from confounding/lurking)  Design of Experiments and Survey Methods  Randomization (CRD vs. block randomized)  Random Sampling (SRS vs. stratified vs. cluster vs. multi-stage)

Key Concepts:  In stratified sampling, the population is divided into homogeneous groups called strata, using an attribute of the samples. Then members from each stratum are selected, and the number of samples taken from those strata is proportional to the presence of the strata within the population.  In cluster sampling, the population is grouped into clusters, predominantly based on location, and then a cluster is selected at random.  In cluster sampling, a cluster is selected at random, whereas in stratified sampling members are selected at random.  In stratified sampling, each group used (strata) include homogenous members while, in cluster sampling, a cluster is heterogeneous. sampling/#ixzz2fwcoHvwu

SAMPLE QUESTION #1 1) Causation vs. Association For each example, list whether we you believe there is causation, or some confounding/lurking variable (please list any possible lurking variables, and draw the relationship graph): a) Smokers have higher rates of lung cancer. b) Smokers tend to have lower rates of asthma. c) Couples that live together before being married are more likely to get divorced later. d) Dog owners live longer. Questions for thought: What is y? What is x?

SAMPLE QUESTION #2 2) Randomization In order to determine whether or not Tylenol reduces the severity of headaches, an investigator wants to create a clinical trial answer this question. She has 12 people signed up for the study, listed below. Using a random digit generator to assign the participants to either placebo or Tylenol: SubjectTreatmentSubjectTreatmentSubjectTreatment Alex Erica Isaac Billy Fred Jess Carol Gary Kelly Dave Helen Laura

SAMPLE QUESTION #2 2) Randomization In order to determine whether or not Tylenol reduces the severity of headaches, an investigator wants to create a clinical trial answer this question. She has 12 people signed up for the study, listed below. Using a random digit generator to assign the participants to either placebo or Tylenol: SubjectTreatmentSubjectTreatmentSubjectTreatment Alex 10Erica Isaac Billy 09Fred Jess Carol 73Gary Kelly Dave 25Helen Laura

3) Sample Survey In 1987, Shere Hite authored a book entitled Women and Love: A Cultural Revolution in Progress ( which reported some very captivating survey results on women's intimacy and love relationships. She reported the following: 84% of women are “not satisfied emotionally with their relationships” (p. 804) 70% of all women “married five or more years are having sex outside of their marriages (p. 856) 95% of women “report forms of emotional and psychological harassment from men with whom they are in love relationships” (p. 810) 84% of women report forms of condescension from the men in their love relationships (p. 809) Hite collected her sample by sending surveys to 100,000 women via snail-mail. She mailed the questionnaires to addresses collected from mailing lists of groups of women professionals, counseling centers, church societies and senior citizen groups. She received about 4,500 surveys in response. Obviously, this is not an example of great survey sampling. For Hite's data collection techniques, give an example of each of the following: Selection Bias Response BiasNon-Response Bias SAMPLE QUESTION #3

3) Sample Survey In 1987, Shere Hite authored a book entitled Women and Love: A Cultural Revolution in Progress ( which reported some very captivating survey results on women's intimacy and love relationships. She reported the following: 84% of women are “not satisfied emotionally with their relationships” (p. 804) 70% of all women “married five or more years are having sex outside of their marriages (p. 856) 95% of women “report forms of emotional and psychological harassment from men with whom they are in love relationships” (p. 810) 84% of women report forms of condescension from the men in their love relationships (p. 809) Hite collected her sample by sending surveys to 100,000 women via snail-mail. She mailed the questionnaires to addresses collected from mailing lists of groups of women professionals, counseling centers, church societies and senior citizen groups. She received about 4,500 surveys in response. Obviously, this is not an example of great survey sampling. For Hite's data collection techniques, give an example of each of the following: Selection Bias Response BiasNon-Response Bias SAMPLE QUESTION #3 Sample does not represent entire populationOnly those who feel the strongest willHow were the questions worded? What about women from universities?respond.