Something to think about. What happens, however, when we have a sample with less than 30 items?
|
|
|
- Cory Sherman
- 6 years ago
- Views:
Transcription
1 One-Sample t-test
2 Remember In the last chapter, we learned to use a statistic from a large sample of data to test a hypothesis about a population parameter. In our case, using a z-test, we tested a hypothesis about a population mean using the mean of one sample drawn from that population. We agreed that by "large sample" we mean any sample that has 30 or more data values.
3 Something to think about What happens, however, when we have a sample with less than 30 items?
4 Answer: Here, we cannot use the one-sample z-test. But what we will is its counterpart, the onesample t-test.
5 The History of t-test
6 William Gossett He is a chemist, who worked for Guinness in the early 1900s.
7 William Gossett His job involved testing samples of ale to ensure quality.
8 William Gossett He was determined to develop a statistical tool that would allow him to use smaller and still be able to test hypothesis about a population parameter.
9 The t Distribution Gossett, while experimenting with possible solutions, noticed something interesting about the mound-shaped distribution of data values when the sample size was less than 30.
10 The t Distribution Each time he decreased the sample size by one, and plotted the means of repeated samples of the same size, the shape of the distribution flattened out.
11 The t Distribution
12 The t Distribution From the figure, we can conclude that the fewer the number of data values you have, the more spread out on both ends (i.e., platykurtosis) our distribution is.
13 The t Distribution Gossett further discovered that the empirical rule applied to this distribution and, if you compensate for the number of data values less than 30, you can test a hypothesis by comparing a computed value of t to a critical value of t.
14 The One-Sample t-test This is a statistical tool use when testing a hypothesis of a sample that has less than 30 members/items.
15 Example "Persons living in urban environments have anxiety levels significantly different from the national average."
16 Example Let's say we have a dataset with 15 values to test this hypothesis and the national average anxiety level is 30. Also, we have a test that is used to measure anxiety and the scores from it range from 0 (no anxiety) to 80 (high anxiety).
17 Data
18 Determining the Computed Value of t
19 Formula for Computed Value of t
20 Determining the Critical Value of t
21 The Area Under the Normal Curve Table We will determine our critical value of t using a table developed especially for that purpose the table showing the area under the curve for t values.
22 Degrees of Freedom (df) This is the number of values in the dataset which are collected that are "free to vary" when trying to estimate any given value. We will denote this using minuscule letters df.
23 Understanding the Degrees of Freedom (df) Suppose we have a one-sample t-test where we know the population mean is 10. I might ask you to tell me five numbers that, when summed, would give an average of 10. You might start out by saying "6, 8, 10, 12,..." but then I would have to interrupt you by saying, "That is enough."
24 To sum it up If we know the mean and all of the values in the dataset except one, we can easily determine the missing value. In this case, four of our values in the dataset can vary, but the fifth one cannot.
25 Formula for Computing the Degrees of Freedom (df):
26 Question: Using the formula for finding df, what is the df in Example 13.1?
27 Danger in Computing Degrees of Freedom
28 Danger: The degrees of freedom is computed in different ways. It will depend on the number of items in your dataset and the number of levels of the independent variable.
29 Danger: The degrees of freedom is computed in different ways. It will depend on the number of items in your dataset and the number of levels of the independent variable.
30 Challenge: Compare the Critical Values of t Table to that of Areas Under the Normal Curve Table.
31 Using Critical Values of t Table
32 Example In order to use the t table, let us suppose we have a scenario with 12 degrees of freedom and want the critical value for alpha.05. What is the critical value of t?
33 Example We might have 29 degrees of freedom and a critical value of t when alpha is.025. What us the critical value of t?
34 Going Back to Example "Persons living in urban environments have anxiety levels significantly different from the national average."
35 Question: What have you noticed about the type of hypothesis we have? Then, what do you think should we do with our alpha value? So, what is now our alpha value and what is now our critical value?
36 Task: Plotting Our Critical Value of t
37 Analyzing the Result By comparing our computed value of t and critical value of t and looking at the figure, what should be our decision?
38 Decision: Since our computed value of t (i.e., 2.691) is not within the range of the critical values, we can reject the null hypothesis. By looking at our data results, it appears that the anxiety levels of people living in urban areas may be significantly higher than the national average.
39 Testing Hypothesis Using the p Value and Alpha Value
40 Table Inferential Statistics from a One-Sample Test
41 Question: How do we compute for the p value for nondirectional hypothesis?
42 Decision: We can see based on the Table 13.3 that our p value, labeled "Sig. (2- tailed)" is.018; this is less than our alpha value of.025. This verifies our decision we made when we compared the critical value of t to the computed value of t; we must reject our null hypothesis and support our research hypothesis.
43 Something to think about Although we have rejected the null hypothesis, some statisticians feel this isn't enough. At this point, we know the groups being compared are significantly different, but we know nothing about the degree to which they're different, right?
44 Effect Size Indices This is a statistical tool developed to help us better understand the magnitude of any significant difference which uncovered. It is also called as practical significance and Cohen's delta.
45 Practical Significance/ Cohen s Delta It helps us better understand the extent to which the independent variable affects the dependent variable.
46 Formula for Computing the Effect Size:
47 Danger in Computing the Effect Size Standard Error of the Mean is different from Standard Deviation of the Mean.
48 Question: Using the formula, what is our Cohen's delta?
49 Answer: This leaves us with an effect size of.695, but what does it mean?
50 Computed Effect Size It is the percentage of the standard deviation that the difference in the mean scores represents.
51 Cohen s Effect Size Interpretations
52 Small If the computed Cohen's delta is.2 or smaller.
53 Medium If the computed Cohen's delta is between.2 and.5.
54 Large If the computed Cohen's delta is greater than.5.
55 Therefore, The computed effect size of.695 is large effect size; the groups are significantly different, and the levels of the independent variable had a dramatic effect on the dependent variable. In short, there is a strong relationship between where the persons live and their level of anxiety.
56 Example "Men who use anabolic steroids will have significantly shorter life expectancies than men who do not."
57 Example In this case, suppose we know the average life expectancy for men is 70 years but we only have access to information on 12 men who used steroids of this type.
58 Example 13.2.
59 Task 1: Compute for the Computed Value of t using the formula
60 Task 2: Determine the alpha value.
61 Question: Do we need to divide our alpha value by 2? Why or why not?
62 Task 3: Plot our critical value on the "less than" side of the distribution.
63 Question: Based on the critical value of t and computed value of t, and by looking at our distribution, what decision can you make?
64 Decision: Our computed t value, , is less than the critical value of t (i.e., ). Because of that, we reject our null hypothesis and support our research hypothesis.
65 Task 4: Compute for the value of Cohen's delta.
66 Note: We are interested only in the absolute value, so we drop the negative sign and wind up with an effect size if.535.
67 Decision: Our previous decision is supported by a large effect size of.535; the independent variable does have a large effect on the dependent variable. Apparently, men who use anabolic steroids live significantly fewer years than their peers who do not.
68 Danger in Using the p Value
69 Note 1: If we are dealing with a nondirectional hypothesis (twotailed hypothesis) and if we divide the alpha value by 2, then we need to use the entire p value. By dividing our alpha value, we already allowed an equal probability of error on both sides of the distribution.
70 Note 2: If we are dealing with directional hypothesis (one-tailed hypothesis) and if we used the entire alpha value, then we need to divide our p value by 2. This is for the fact that we are just looking at one side or one direction of our hypothesis, which is either less than or greater than.
71 Danger in Using the p Value
72 Deepening Our Knowledge about One-Sample t-test Now that we know how to test a hypothesis by both comparing a computed value of t to a critical value of t and comparing a computed p value to a pre established alpha value, let's put this all together and use our sixstep model.
73 The Six-Step Statistical Model
74 Step 1: Identify the Problem
75 Characteristics of a Good Problem Statement The problem is interesting to the researcher.
76 Characteristics of a Good Problem Statement The scope of the problem is manageable by the researcher.
77 Characteristics of a Good Problem Statement The researcher has the knowledge, time, and resources needed to investigate the problem.
78 Characteristics of a Good Problem Statement The problem can be researched through the collection and analysis of numeric data.
79 Characteristics of a Good Problem Statement Investigating the problem has theoretical or practical significance.
80 Characteristics of a Good Problem Statement It is ethical to investigate the problem.
81 Step 2: State a Hypothesis
82 Step 3: Identify the Independent Variable
83 Step 4: Identify and Describe the Dependent Variable
84 Step 5: Choose the Right Statistical Test
85 Step 6: Data Computation and Analysis to Test the Hypothesis
86 Case 1: Residents in a lower socioeconomic section of town recently complained to local health officials that ambulance response times to their neighborhood were not as fast as average response times throughout town. This, of course, worried the officials, and they decided to investigate. Their records showed the average response time throughout the city to be 90 seconds after an emergency was phoned in. They decided to monitor the next 20 response times to the concerned neighborhood to help determine if the complaint had any merit.
87 Step 1: Identify the Problem
88 Question: What do you think is the problem which we need to investigate?
89 Answer: Yes, the city officials are interested in this problem.
90 Question: Will this meet our criteria for a good research problem?
91 Answer: Yes, the scope of the problem is manageable by city officials. They would simply need to collect response times for each section of town.
92 Question: Does the researcher possess knowledge, time, and resources needed to investigate the problem?
93 Answer: Yes, the city officials have the knowledge, time, and resources needed to investigate the problem.
94 Question: Is the problem can be researched through collection and analysis of numeric data?
95 Answer: Yes, the problem can be researched through the collection and analysis of numeric data.
96 Statement of the Problem: "This study will investigate whether ambulance response times vary between different sections of the city."
97 Step 2: State the Hypothesis How will we state our null hypothesis?
98 Null Hypothesis "Ambulance response times to the lower socioeconomic community are not significantly greater than 90 seconds."
99 Step 3: Identify the Independent Variable
100 Question: What is our independent variable? Why?
101 Answer: In this case we are interested in looking at times for 20 ambulance calls to the affected neighborhood (i.e., our sample) and compare them to a known population parameter (i.e., the average time for the total number of calls in the town). Because of that, our independent variable is "calls for an ambulance."
102 Question: How many levels do we have in our independent variable?
103 Answer: We only have one level; calls to the specific part of the town. While it seems that calls to the town overall are another variable, that is not the case. They represent the overall population and cannot be considered as a level of an independent variable.
104 Step 4: Identify and Describe the Dependent Variable
105 Question: What is our dependent variable?
106 Answer: The dependent variable is the average response time for the 20 ambulance response times in the sample.
107 Data:
108 Step 5: Choosing the Right Statistical Tool How many independent variable do we have? How many level? How many dependent variable?
109 Answer: We have one independent variable with one level. We also have one dependent variable representing quantitative data. As a result, we are going to use the one-sample t-test.
110 Step 6: Data Computation and Analysis to Test the Hypothesis
111 Task 1 Compute the computed Value of t
112 Task 2 Determine the Critical Value of t
113 Task 3 Construct and plot the values on the normal distribution
114 Task 4 Determine the p value
115 Task 5 Compare the p value to alpha value
116 Task 6 Determine the effect size
117 Task 7 Make a decision and conclusion
118 Decision and Conclusion: Our one-tailed p value is much smaller than our alpha value (i.e.,.05), so we reject the null hypothesis. This significant difference is supported by a somewhat large effect size of.520. This is further substantiated by noting that our computed value of t, 2.326, is much larger than our critical value of t, 1.729
119 Let s Practice
120 Direction: Read and analyze each case below. Answer it by using the Six-Step Statistical Model.
121 The Case of Stopping Sneezing Physicians at a premiere hospital are constantly working to lower the amount of time it takes a patient to stop sneezing after being exposed to an allergen. Their experience has shown, on average that it takes about 2 minutes for standard drugs to be effective. Today, however, they are listening to a representative from a pharmaceutical company who is introducing a drug the company claims will end sneezing in significantly less time. The physicians skeptically agreed to try the drug and decided to use it on a sample of ten patients. The results of that sample, they believe, will help them decide whether to use the new "miracle drug."
122 The Case of Stopping Sneezing
123 The Case of Stopping Sneezing I have lived in big cities most of my life and recently decided to move out into the country. One of the pleasures I've discovered is the ability to grow your own garden and "live off the fruit of the land." In talking to some of the other folks around here, I've discovered that many people consider growing tomatoes a science somewhat akin to nuclear physics. They talk about the amount of rain needed, the type of fertilizer to use, how far plants should be spaced apart, and other really exciting topics. One thing I found interesting is that they consider a 10-ounce tomato to be about average; most folks can't grow them any bigger than that. After hearing that, I figured a good way for a city boy to fit in would be to grow the biggest, juiciest tomatoes in town! In order to set my plan in action, I went to the local "feed and seed" store and inquired as to which fertilizer I should use. The guy running the place said he had basically two types. The cheaper variety worked well enough, but he told me, by spending a few extra pesos, I could grow tomatoes I would probably be proud of! Given that, I bought the costlier of the two, drove home, and put my plan into action!
124 The Case of Stopping Sneezing
Chapter 12. The One- Sample
Chapter 12 The One- Sample z-test Objective We are going to learn to make decisions about a population parameter based on sample information. Lesson 12.1. Testing a Two- Tailed Hypothesis Example 1: Let's
Inferential Statistics
Inferential Statistics and t - tests ScWk 242 Session 9 Slides Inferential Statistics Ø Inferential statistics are used to test hypotheses about the relationship between the independent and the dependent
Applied Statistical Analysis EDUC 6050 Week 4
Applied Statistical Analysis EDUC 6050 Week 4 Finding clarity using data Today 1. Hypothesis Testing with Z Scores (continued) 2. Chapters 6 and 7 in Book 2 Review! = $ & '! = $ & ' * ) 1. Which formula
One-Way ANOVAs t-test two statistically significant Type I error alpha null hypothesis dependant variable Independent variable three levels;
1 One-Way ANOVAs We have already discussed the t-test. The t-test is used for comparing the means of two groups to determine if there is a statistically significant difference between them. The t-test
Lesson 11.1: The Alpha Value
Hypothesis Testing Lesson 11.1: The Alpha Value The alpha value is the degree of risk we are willing to take when making a decision. The alpha value, often abbreviated using the Greek letter α, is sometimes
Objectives. Quantifying the quality of hypothesis tests. Type I and II errors. Power of a test. Cautions about significance tests
Objectives Quantifying the quality of hypothesis tests Type I and II errors Power of a test Cautions about significance tests Designing Experiments based on power Evaluating a testing procedure The testing
CHAPTER ONE CORRELATION
CHAPTER ONE CORRELATION 1.0 Introduction The first chapter focuses on the nature of statistical data of correlation. The aim of the series of exercises is to ensure the students are able to use SPSS to
PROSTATE CANCER SCREENING SHARED DECISION MAKING VIDEO
PROSTATE CANCER SCREENING SHARED DECISION MAKING VIDEO 1 00:00:00,067 --> 00:00:10,968 2 00:00:10,968 --> 00:00:12,701 So, you were given a decision aid sheet 3 00:00:12,701 --> 00:00:14,567 about prostate
Chapter 23. Inference About Means. Copyright 2010 Pearson Education, Inc.
Chapter 23 Inference About Means Copyright 2010 Pearson Education, Inc. Getting Started Now that we know how to create confidence intervals and test hypotheses about proportions, it d be nice to be able
15.301/310, Managerial Psychology Prof. Dan Ariely Recitation 8: T test and ANOVA
15.301/310, Managerial Psychology Prof. Dan Ariely Recitation 8: T test and ANOVA Statistics does all kinds of stuff to describe data Talk about baseball, other useful stuff We can calculate the probability.
UNEQUAL CELL SIZES DO MATTER
1 of 7 1/12/2010 11:26 AM UNEQUAL CELL SIZES DO MATTER David C. Howell Most textbooks dealing with factorial analysis of variance will tell you that unequal cell sizes alter the analysis in some way. I
Chapter 11. Experimental Design: One-Way Independent Samples Design
11-1 Chapter 11. Experimental Design: One-Way Independent Samples Design Advantages and Limitations Comparing Two Groups Comparing t Test to ANOVA Independent Samples t Test Independent Samples ANOVA Comparing
THIS PROBLEM HAS BEEN SOLVED BY USING THE CALCULATOR. A 90% CONFIDENCE INTERVAL IS ALSO SHOWN. ALL QUESTIONS ARE LISTED BELOW THE RESULTS.
Math 117 Confidence Intervals and Hypothesis Testing Interpreting Results SOLUTIONS The results are given. Interpret the results and write the conclusion within context. Clearly indicate what leads to
DECISION QUALITY WORKSHEET TREATMENTS FOR DEPRESSION
DECISION QUALITY WORKSHEET TREATMENTS FOR DEPRESSION Instructions This survey has questions about what it is like for you to make decisions about treating your depression. Please check the box or circle
Genetic Counselor: Hi Lisa. Hi Steve. Thanks for coming in today. The BART results came back and they are positive.
Hi, I m Kaylene Ready, a genetic counselor who specializes in the education and counseling of individuals at high-risk for hereditary breast and ovarian cancer syndrome. Women with an inherited BRCA 1
Statistics for Psychology
Statistics for Psychology SIXTH EDITION CHAPTER 3 Some Key Ingredients for Inferential Statistics Some Key Ingredients for Inferential Statistics Psychologists conduct research to test a theoretical principle
Combining Individualized Treatment Options with Patient-Clinician Dialogue
Transcript Details This is a transcript of a continuing medical education (CME) activity accessible on the ReachMD network. Additional media formats for the activity and full activity details (including
Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo
Please note the page numbers listed for the Lind book may vary by a page or two depending on which version of the textbook you have. Readings: Lind 1 11 (with emphasis on chapters 10, 11) Please note chapter
EXERCISE: HOW TO DO POWER CALCULATIONS IN OPTIMAL DESIGN SOFTWARE
...... EXERCISE: HOW TO DO POWER CALCULATIONS IN OPTIMAL DESIGN SOFTWARE TABLE OF CONTENTS 73TKey Vocabulary37T... 1 73TIntroduction37T... 73TUsing the Optimal Design Software37T... 73TEstimating Sample
Question: I m worried my child is using illegal drugs, what should I do about it?
Question: I m worried my child is using illegal drugs, what should I do about it? Answer: Many parents worry about whether their son or daughter is using illegal drugs and what they should do about it.
Why Are So Many Clinicians Choosing to Practice Functional Medicine?
Transcript Details This is a transcript of an educational program accessible on the ReachMD network. Details about the program and additional media formats for the program are accessible by visiting: https://reachmd.com/programs/integrative-and-functional-medicine-in-practice/why-are-so-manyclinicians-choosing-practice-functional-medicine/8424/
Your Money or Your Life An Exploration of the Implications of Genetic Testing in the Workplace
Activity Instructions This Role Play Activity is designed to promote discussion and critical thinking about the issues of genetic testing and pesticide exposure. While much of the information included
Teaching Family and Friends in Your Community
2 CHAPTER Teaching Family and Friends in Your Community 9 Old people can remember when there were fewer problems with teeth and gums. Children s teeth were stronger and adults kept their teeth longer.
Business Statistics Probability
Business Statistics The following was provided by Dr. Suzanne Delaney, and is a comprehensive review of Business Statistics. The workshop instructor will provide relevant examples during the Skills Assessment
Name: Chapters Three and Four. Page 1 of 8
Chapters Three and Four Page 1 of 8 Chapter Three 1. What did Slim give Lennie? What does George say? What are George s feelings towards the gift? 2. What does Slim think of Lennie? 3. What does Slim find
Probability Models for Sampling
Probability Models for Sampling Chapter 18 May 24, 2013 Sampling Variability in One Act Probability Histogram for ˆp Act 1 A health study is based on a representative cross section of 6,672 Americans age
t-test for r Copyright 2000 Tom Malloy. All rights reserved
t-test for r Copyright 2000 Tom Malloy. All rights reserved This is the text of the in-class lecture which accompanied the Authorware visual graphics on this topic. You may print this text out and use
Lesson 9: Two Factor ANOVAS
Published on Agron 513 (https://courses.agron.iastate.edu/agron513) Home > Lesson 9 Lesson 9: Two Factor ANOVAS Developed by: Ron Mowers, Marin Harbur, and Ken Moore Completion Time: 1 week Introduction
Still important ideas
Readings: OpenStax - Chapters 1 11 + 13 & Appendix D & E (online) Plous - Chapters 2, 3, and 4 Chapter 2: Cognitive Dissonance, Chapter 3: Memory and Hindsight Bias, Chapter 4: Context Dependence Still
PSYCHOLOGY 300B (A01) One-sample t test. n = d = ρ 1 ρ 0 δ = d (n 1) d
PSYCHOLOGY 300B (A01) Assignment 3 January 4, 019 σ M = σ N z = M µ σ M d = M 1 M s p d = µ 1 µ 0 σ M = µ +σ M (z) Independent-samples t test One-sample t test n = δ δ = d n d d = µ 1 µ σ δ = d n n = δ
Still important ideas
Readings: OpenStax - Chapters 1 13 & Appendix D & E (online) Plous Chapters 17 & 18 - Chapter 17: Social Influences - Chapter 18: Group Judgments and Decisions Still important ideas Contrast the measurement
The Wellbeing Course. Resource: Mental Skills. The Wellbeing Course was written by Professor Nick Titov and Dr Blake Dear
The Wellbeing Course Resource: Mental Skills The Wellbeing Course was written by Professor Nick Titov and Dr Blake Dear About Mental Skills This resource introduces three mental skills which people find
In this chapter we discuss validity issues for quantitative research and for qualitative research.
Chapter 8 Validity of Research Results (Reminder: Don t forget to utilize the concept maps and study questions as you study this and the other chapters.) In this chapter we discuss validity issues for
Statistical Significance, Effect Size, and Practical Significance Eva Lawrence Guilford College October, 2017
Statistical Significance, Effect Size, and Practical Significance Eva Lawrence Guilford College October, 2017 Definitions Descriptive statistics: Statistical analyses used to describe characteristics of
Living My Best Life. Today, after more than 30 years of struggling just to survive, Lynn is in a very different space.
Living My Best Life Lynn Allen-Johnson s world turned upside down when she was 16. That s when her father and best friend died of Hodgkin s disease leaving behind her mom and six kids. Lynn s family was
Two-sample Categorical data: Measuring association
Two-sample Categorical data: Measuring association Patrick Breheny October 27 Patrick Breheny University of Iowa Biostatistical Methods I (BIOS 5710) 1 / 40 Introduction Study designs leading to contingency
Module 28 - Estimating a Population Mean (1 of 3)
Module 28 - Estimating a Population Mean (1 of 3) In "Estimating a Population Mean," we focus on how to use a sample mean to estimate a population mean. This is the type of thinking we did in Modules 7
Reflection Questions for Math 58B
Reflection Questions for Math 58B Johanna Hardin Spring 2017 Chapter 1, Section 1 binomial probabilities 1. What is a p-value? 2. What is the difference between a one- and two-sided hypothesis? 3. What
DIFFERENCE BETWEEN TWO MEANS: THE INDEPENDENT GROUPS T-TEST
DIFFERENCE BETWEEN TWO MEANS: THE INDEPENDENT GROUPS T-TEST The previous unit demonstrated how to test the difference between two means calculated from dependent or correlated observations. Difference
Chapter 9: Comparing two means
Chapter 9: Comparing two means Smart Alex s Solutions Task 1 Is arachnophobia (fear of spiders) specific to real spiders or will pictures of spiders evoke similar levels of anxiety? Twelve arachnophobes
The t-test: Answers the question: is the difference between the two conditions in my experiment "real" or due to chance?
The t-test: Answers the question: is the difference between the two conditions in my experiment "real" or due to chance? Two versions: (a) Dependent-means t-test: ( Matched-pairs" or "one-sample" t-test).
1 The conceptual underpinnings of statistical power
1 The conceptual underpinnings of statistical power The importance of statistical power As currently practiced in the social and health sciences, inferential statistics rest solidly upon two pillars: statistical
Sheila Barron Statistics Outreach Center 2/8/2011
Sheila Barron Statistics Outreach Center 2/8/2011 What is Power? When conducting a research study using a statistical hypothesis test, power is the probability of getting statistical significance when
Audio: In this lecture we are going to address psychology as a science. Slide #2
Psychology 312: Lecture 2 Psychology as a Science Slide #1 Psychology As A Science In this lecture we are going to address psychology as a science. Slide #2 Outline Psychology is an empirical science.
CCM6+7+ Unit 12 Data Collection and Analysis
Page 1 CCM6+7+ Unit 12 Packet: Statistics and Data Analysis CCM6+7+ Unit 12 Data Collection and Analysis Big Ideas Page(s) What is data/statistics? 2-4 Measures of Reliability and Variability: Sampling,
Research Methods 1 Handouts, Graham Hole,COGS - version 1.0, September 2000: Page 1:
Research Methods 1 Handouts, Graham Hole,COGS - version 10, September 000: Page 1: T-TESTS: When to use a t-test: The simplest experimental design is to have two conditions: an "experimental" condition
STAT 113: PAIRED SAMPLES (MEAN OF DIFFERENCES)
STAT 113: PAIRED SAMPLES (MEAN OF DIFFERENCES) In baseball after a player gets a hit, they need to decide whether to stop at first base, or try to stretch their hit from a single to a double. Does the
Stat 13, Intro. to Statistical Methods for the Life and Health Sciences.
Stat 13, Intro. to Statistical Methods for the Life and Health Sciences. 0. SEs for percentages when testing and for CIs. 1. More about SEs and confidence intervals. 2. Clinton versus Obama and the Bradley
Problem Situation Form for Parents
Problem Situation Form for Parents Please complete a form for each situation you notice causes your child social anxiety. 1. WHAT WAS THE SITUATION? Please describe what happened. Provide enough information
My Father Has a Mood. Disorder
My Father Has a Mood Disorder 1996 Bipolar Support Canterbury Inc. Reprinted 2004 Illustrations by Judy Lee Bipolar Support Canterbury would like to acknowledge the assistance of J R McKenzie Trust and
ORIENTATION SAN FRANCISCO STOP SMOKING PROGRAM
ORIENTATION SAN FRANCISCO STOP SMOKING PROGRAM PURPOSE To introduce the program, tell the participants what to expect, and set an overall positive tone for the series. AGENDA Item Time 0.1 Acknowledgement
CHAPTER NINE DATA ANALYSIS / EVALUATING QUALITY (VALIDITY) OF BETWEEN GROUP EXPERIMENTS
CHAPTER NINE DATA ANALYSIS / EVALUATING QUALITY (VALIDITY) OF BETWEEN GROUP EXPERIMENTS Chapter Objectives: Understand Null Hypothesis Significance Testing (NHST) Understand statistical significance and
Catherine. I am 46 yrs old with Usher syndrome 2a. I am married with two teenage boys 15 and 13. I am
I am 46 yrs old with Usher syndrome 2a. I am married with two teenage boys 15 and 13. I am Director of EC Energy Ltd, we are a small family run company. I manage the finances of this and 3 other sister
BBC LEARNING ENGLISH 6 Minute English Diabetes
BBC LEARNING ENGLISH 6 Minute English Diabetes NB: This is not a word-for-word transcript Hello and welcome to 6 Minute English. I'm And I'm. Can you pass me my drink,? Cola,? That's very unhealthy. You
Section 4 Decision-making
Decision-making : Decision-making Summary Conversations about treatments Participants were asked to describe the conversation that they had with the clinician about treatment at diagnosis. The most common
Group Behavior By Michael Stahl
Group Behavior Group Behavior By Michael Stahl The word social means: relating to society or its organization. There is a special type of science that studies how human beings interact with each other
I. Introduction and Data Collection B. Sampling. 1. Bias. In this section Bias Random Sampling Sampling Error
I. Introduction and Data Collection B. Sampling In this section Bias Random Sampling Sampling Error 1. Bias Bias a prejudice in one direction (this occurs when the sample is selected in such a way that
You re listening to an audio module from BMJ Learning. Hallo. I'm Anna Sayburn, Senior Editor with the BMJ Group s Consumer Health Team.
Transcript of learning module Shared decision making (Dur: 26' 13") Contributors: Anna Sayburn and Alf Collins Available online at: http://learning.bmj.com/ V/O: You re listening to an audio module from
Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo
Business Statistics The following was provided by Dr. Suzanne Delaney, and is a comprehensive review of Business Statistics. The workshop instructor will provide relevant examples during the Skills Assessment
Read the next two selections. Then choose the best answer to each question. A Book for Jonah
Read the next two selections. Then choose the best answer to each question. A Book for Jonah 1 A six-year-old boy named Dylan Siegel wanted to help his friend Jonah, who has a rare liver disease. Jonah
Readings: Textbook readings: OpenStax - Chapters 1 11 Online readings: Appendix D, E & F Plous Chapters 10, 11, 12 and 14
Readings: Textbook readings: OpenStax - Chapters 1 11 Online readings: Appendix D, E & F Plous Chapters 10, 11, 12 and 14 Still important ideas Contrast the measurement of observable actions (and/or characteristics)
Statistics Spring Study Guide
Name: Statistics Spring Study Guide NORMAL AND SAMPLING DISTRIBUTIONS CHAPTER SIX As opposed to the discrete distributions in the previous chapter, the normal distribution is a continuous distribution,
OCW Epidemiology and Biostatistics, 2010 David Tybor, MS, MPH and Kenneth Chui, PhD Tufts University School of Medicine October 27, 2010
OCW Epidemiology and Biostatistics, 2010 David Tybor, MS, MPH and Kenneth Chui, PhD Tufts University School of Medicine October 27, 2010 SAMPLING AND CONFIDENCE INTERVALS Learning objectives for this session:
What family members have told us about having HIV at home
Family Matters Changing Lives Chapter 6 P1 The great indoors the family living with HIV HIV has brought us closer together. The most important part of the day is around the kitchen table for dinner. We
News English.com Ready-to-use ESL / EFL Lessons
www.breaking News English.com Ready-to-use ESL / EFL Lessons 1,000 IDEAS & ACTIVITIES FOR LANGUAGE TEACHERS The Breaking News English.com Resource Book http://www.breakingnewsenglish.com/book.html Warmer
3 CONCEPTUAL FOUNDATIONS OF STATISTICS
3 CONCEPTUAL FOUNDATIONS OF STATISTICS In this chapter, we examine the conceptual foundations of statistics. The goal is to give you an appreciation and conceptual understanding of some basic statistical
Reliability and Validity
Reliability and Validity Why Are They Important? Check out our opening graphics. In a nutshell, do you want that car? It's not reliable. Would you recommend that car magazine (Auto Tester Weakly) to a
Two-Way Independent ANOVA
Two-Way Independent ANOVA Analysis of Variance (ANOVA) a common and robust statistical test that you can use to compare the mean scores collected from different conditions or groups in an experiment. There
One-Way Independent ANOVA
One-Way Independent ANOVA Analysis of Variance (ANOVA) is a common and robust statistical test that you can use to compare the mean scores collected from different conditions or groups in an experiment.
Cognitive Dissonance. by Saul McLeod published 2008, updated
Cognitive Dissonance by Saul McLeod published 2008, updated Cognitive dissonance refers to a situation involving conflicting attitudes, beliefs or behaviors. This produces a feeling of discomfort leading
Chapter 5: Field experimental designs in agriculture
Chapter 5: Field experimental designs in agriculture Jose Crossa Biometrics and Statistics Unit Crop Research Informatics Lab (CRIL) CIMMYT. Int. Apdo. Postal 6-641, 06600 Mexico, DF, Mexico Introduction
Describe what is meant by a placebo Contrast the double-blind procedure with the single-blind procedure Review the structure for organizing a memo
Please note the page numbers listed for the Lind book may vary by a page or two depending on which version of the textbook you have. Readings: Lind 1 11 (with emphasis on chapters 5, 6, 7, 8, 9 10 & 11)
Adapted from information provided at kidshealth.org
Emma's mum first noticed the cuts when Emma was doing the dishes one night. Emma told her mum that their cat had scratched her. Her mum seemed surprised that the cat had been so rough, but she didn't think
Living well today...32 Hope for tomorrow...32
managing diabetes managing managing managing managing managing managing diabetes Scientific research continually increases our knowledge of diabetes and the tools to treat it. This chapter describes what
LEAVING EVERYONE WITH THE IMPRESSION OF INCREASE The Number One Key to Success
LESSON ELEVEN LEAVING EVERYONE WITH THE IMPRESSION OF INCREASE The Number One Key to Success 167 Lesson Eleven AREA 1 NAME AREA 2 NAME AREA 3 NAME KEY POINTS Riches, in the context of this program, refers
Statistics: Bar Graphs and Standard Error
www.mathbench.umd.edu Bar graphs and standard error May 2010 page 1 Statistics: Bar Graphs and Standard Error URL: http://mathbench.umd.edu/modules/prob-stat_bargraph/page01.htm Beyond the scatterplot
Chapter 7: Descriptive Statistics
Chapter Overview Chapter 7 provides an introduction to basic strategies for describing groups statistically. Statistical concepts around normal distributions are discussed. The statistical procedures of
Why do Psychologists Perform Research?
PSY 102 1 PSY 102 Understanding and Thinking Critically About Psychological Research Thinking critically about research means knowing the right questions to ask to assess the validity or accuracy of a
Demonstrating Client Improvement to Yourself and Others
Demonstrating Client Improvement to Yourself and Others Understanding and Using your Outcome Evaluation System (Part 2 of 3) Greg Vinson, Ph.D. Senior Researcher and Evaluation Manager Center for Victims
Study on Gender in Physics
Listening Practice Study on Gender in Physics AUDIO - open this URL to listen to the audio: https://goo.gl/7xmlgh Questions 1-10 Choose the correct letter, A, B C. Study on Gender in Physics 1 The students
Basic Statistics and Data Analysis in Work psychology: Statistical Examples
Basic Statistics and Data Analysis in Work psychology: Statistical Examples WORK PSYCHOLOGY INTRODUCTION In this chapter we examine a topic which is given too little coverage in most texts of this kind,
We know that treatments are now targeting genes, but does genetics play a bigger role in cancer outside of that?
Welcome to the 3Ps of Cancer podcast, where we'll discuss prevention, preparedness, and progress in cancer treatments and research. Brought to you by the University of Michigan Rogel Cancer Center. I'm
P O D C A S T Transcript. Dr. Gary Small. Author of 2 Weeks to a Younger Brain
P O D C A S T Transcript Dr. Gary Small Author of 2 Weeks to a Younger Brain Dr. Small, what is your first memory of being interested in the subject of memory? Well, I think I got interested in it when
CHAPTER THIRTEEN. Data Analysis and Interpretation: Part II.Tests of Statistical Significance and the Analysis Story CHAPTER OUTLINE
CHAPTER THIRTEEN Data Analysis and Interpretation: Part II.Tests of Statistical Significance and the Analysis Story CHAPTER OUTLINE OVERVIEW NULL HYPOTHESIS SIGNIFICANCE TESTING (NHST) EXPERIMENTAL SENSITIVITY
It s Time To Talk Again Substance Abuse Among Older Adults
Objectives It s Time To Talk Again Substance Abuse Among Older Adults Julie Stevens, MPS, ACPS, CI 2015 Ohio Prevention & Early Intervention Conference June 30, 2015 1)Understand the magnitude and consequences
Optimization and Experimentation. The rest of the story
Quality Digest Daily, May 2, 2016 Manuscript 294 Optimization and Experimentation The rest of the story Experimental designs that result in orthogonal data structures allow us to get the most out of both
Bipolar Disorder in Children and Teens
Bipolar Disorder in Children and Teens Does your child go through intense mood changes? Does your child have extreme behavior changes? Does your child get much more excited and active than other kids his
suicide Part of the Plainer Language Series
Part of the Plainer Language Series www.heretohelp.bc.ca What is? Suicide means ending your own life. It is sometimes a way for people to escape pain or suffering. When someone ends their own life, we
APPENDIX N. Summary Statistics: The "Big 5" Statistical Tools for School Counselors
APPENDIX N Summary Statistics: The "Big 5" Statistical Tools for School Counselors This appendix describes five basic statistical tools school counselors may use in conducting results based evaluation.
Analysis of Variance (ANOVA)
Research Methods and Ethics in Psychology Week 4 Analysis of Variance (ANOVA) One Way Independent Groups ANOVA Brief revision of some important concepts To introduce the concept of familywise error rate.
Motivational Strategies for Challenging Situations
Motivational Strategies for Challenging Situations Mandy Fauble, PhD, LCSW Executive Director, Safe Harbor Behavioral Health of UPMC Hamot James, Wyler, MA, CPRP Scenario When I talked to her about my
Never P alone: The value of estimates and confidence intervals
Never P alone: The value of estimates and confidence Tom Lang Tom Lang Communications and Training International, Kirkland, WA, USA Correspondence to: Tom Lang 10003 NE 115th Lane Kirkland, WA 98933 USA
MENDELIAN GENETICS. MENDEL RULE AND LAWS Please read and make sure you understand the following instructions and knowledge before you go on.
MENDELIAN GENETICS Objectives Upon completion of this lab, students should: 1. Understand the principles and terms used in Mendelian genetics. 2. Know how to complete a Punnett square to estimate phenotypic
Expert Strategies for Working with Anxiety
Expert Strategies for Working with Anxiety Module 10 - Transcript - pg. 1 Expert Strategies for Working with Anxiety Practical Ways to Diminish the Inner Experience of Anxiety with Kelly McGonigal, PhD;
Instructions for doing two-sample t-test in Excel
Instructions for doing two-sample t-test in Excel (1) If you do not see Data Analysis in the menu, this means you need to use Add-ins and make sure that the box in front of Analysis ToolPak is checked.
STATISTICS - CLUTCH CH.11: HYPOTHESIS TESTING: PART 1.
!! www.clutchprep.com HYPOTHESIS TESTING: HOW IT WORKS The purpose of the hypothesis test is to test a claim about a parameter: There will always be two hypotheses NULL ALTERNATIVE (1) (2) Sin h null is
After Adrenal Cancer Treatment
After Adrenal Cancer Treatment Living as a Cancer Survivor For many people, cancer treatment often raises questions about next steps as a survivor. Lifestyle Changes After Treatment for Adrenal Cancer
The Single-Sample t Test and the Paired-Samples t Test
C H A P T E R 9 The Single-Sample t Test and the Paired-Samples t Test BEFORE YOU GO ON The t Distributions Estimating Population Standard Deviation from the Sample Calculating Standard Error for the t
15 INSTRUCTOR GUIDELINES
STAGE: Former Tobacco User You are a pharmacist at an anticoagulation clinic and are counseling one of your patients, Mrs. Friesen, who is a 60-year-old woman with a history of recurrent right leg deep
Uncovering Significant Emotional Events (S.E.E.'s):
Uncovering Significant Emotional Events (S.E.E.'s): In this article I am going to explain to you what S.E.E. s are and why uncovering them is so important to achieve social confidence. You will read almost