Search results “Analysis of sample survey”
Survey Design and Analysis
Published on 8/7/17 Presented on 8/7/17 Presented by Dr. Victor R. Prybutok The focus of this Webinar is to provide an overview of how to develop and contextualize surveys for use in obtaining quality customer feedback. Covered topics include how surveys are used to develop insight from customers, consumers, business partners, etc. The presentation will provide an overview of survey design and analysis including how item writing or modification of validated items in a construct are verified via exploratory factor analysis & reliability measures. We will also discuss how the model for which the survey is designed is tested via regression, logistic regression, or structural equation modeling. By the end of this webinar, participants should have a basic understanding of survey design and analytical techniques that result in obtaining better customer feedback even when one purchases an existing survey instrument. Suggestions on how to learn more will also be provided.
Views: 2468 ASQStatsDivision
Analysis of Complex Sample Survey Data
Excerpt from Summer 2008 workshop titled "Integrating Cultural and Ethnic Influences on Mental Health" as part of the Collaborative Psychiatric Epidemiology Surveys (CPES) project. Patricia Berglund, Harvard Medical School PowerPoint files are available here: http://www.icpsr.umich.edu/files/CPES/berglund.ppt
Views: 4405 ICPSR
SPSS: Survey Analysis
Views: 20664 Ross Avilla
Your Survey Closed, Now What? Quantitative Analysis Basics
This webinar provides an overview of basic quantitative analysis, including the types of variables and statistical tests commonly used by Student Affairs professionals. Specifically discussed are the basics of Chi-squared tests, t-tests, and ANOVAs, including how to read an SPSS output for each of these tests.
Views: 19783 CSSLOhioStateU
Sampling Methods and Bias with Surveys: Crash Course Statistics #10
Participate in our survey! We'll analyze the results in future episodes! (individual data will be kept anonymous). https://bit.ly/2J1zimn Today we’re going to talk about good and bad surveys. From user feedback surveys, telephone polls, and those questionnaires at your doctors office, surveys are everywhere, but with their ease to create and distribute, they're also susceptible to bias and error. So today we’re going to talk about how to identify good and bad survey questions, and how groups (or samples) are selected to represent the entire population since it's often just not feasible to ask everyone. Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse Thanks to the following Patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Mark Brouwer, Justin Zingsheim, Nickie Miskell Jr., Jessica Wode, Eric Prestemon, Kathrin Benoit, Tom Trval, Jason Saslow, Nathan Taylor, Divonne Holmes à Court, Brian Thomas Gossett, Khaled El Shalakany, Indika Siriwardena, Robert Kunz, SR Foxley, Sam Ferguson, Yasenia Cruz, Daniel Baulig, Eric Koslow, Caleb Weeks, Tim Curwick, Evren Türkmenoğlu, Alexander Tamas, D.A. Noe, Shawn Arnold, mark austin, Ruth Perez, Malcolm Callis, Ken Penttinen, Advait Shinde, Cody Carpenter, Annamaria Herrera, William McGraw, Bader AlGhamdi, Vaso, Melissa Briski, Joey Quek, Andrei Krishkevich, Rachel Bright, Alex S, Mayumi Maeda, Kathy & Tim Philip, Montather, Jirat, Eric Kitchen, Moritz Schmidt, Ian Dundore, Chris Peters,, Sandra Aft, Steve Marshall -- Want to find Crash Course elsewhere on the internet? Facebook - http://www.facebook.com/YouTubeCrashCourse Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids
Views: 88078 CrashCourse
Presentation of Analysis of Survey Results
By Lauren Brotherton & Lucya (Hyu) Lee
Views: 10556 Lauren Brotherton
Analysing Questionnaires
This video is part of the University of Southampton, Southampton Education School, Digital Media Resources http://www.southampton.ac.uk/education http://www.southampton.ac.uk/~sesvideo/
Sampling & its 8 Types: Research Methodology
Dr. Manishika Jain in this lecture explains the meaning of Sampling & Types of Sampling Research Methodology Population & Sample Systematic Sampling Cluster Sampling Non Probability Sampling Convenience Sampling Purposeful Sampling Extreme, Typical, Critical, or Deviant Case: Rare Intensity: Depicts interest strongly Maximum Variation: range of nationality, profession Homogeneous: similar sampling groups Stratified Purposeful: Across subcategories Mixed: Multistage which combines different sampling Sampling Politically Important Cases Purposeful Sampling Purposeful Random: If sample is larger than what can be handled & help to reduce sample size Opportunistic Sampling: Take advantage of new opportunity Confirming (support) and Disconfirming (against) Cases Theory Based or Operational Construct: interaction b/w human & environment Criterion: All above 6 feet tall Purposive: subset of large population – high level business Snowball Sample (Chain-Referral): picks sample analogous to accumulating snow Advantages of Sampling Increases validity of research Ability to generalize results to larger population Cuts the cost of data collection Allows speedy work with less effort Better organization Greater brevity Allows comprehensive and accurate data collection Reduces non sampling error. Sampling error is however added. Population & Sample @2:25 Sampling @6:30 Systematic Sampling @9:25 Cluster Sampling @ 11:22 Non Probability Sampling @13:10 Convenience Sampling @15:02 Purposeful Sampling @16:16 Advantages of Sampling @22:34 #Politically #Purposeful #Methodology #Systematic #Convenience #Probability #Cluster #Population #Research #Manishika #Examrace For IAS Psychology postal Course refer - http://www.examrace.com/IAS/IAS-FlexiPrep-Program/Postal-Courses/Examrace-IAS-Psychology-Series.htm For NET Paper 1 postal course visit - https://www.examrace.com/CBSE-UGC-NET/CBSE-UGC-NET-FlexiPrep-Program/Postal-Courses/Examrace-CBSE-UGC-NET-Paper-I-Series.htm types of sampling types of sampling pdf probability sampling types of sampling in hindi random sampling cluster sampling non probability sampling systematic sampling
Views: 352604 Examrace
Basic introduction to the analysis of complex survey data in Stata®
A basic introduction to the analysis of complex survey data in Stata. Created using Stata 13; new features available in Stata 14. Copyright 2011-2017 StataCorp LLC. All rights reserved.
Views: 31614 StataCorp LLC
What is Survey Weights? by Natalie Shlomo
Nonresponse to a survey occurs when a selected unit does not provide the requested information. This is out of control of the research and affects the quality of the survey estimates. For more methods resources see: http://www.methods.manchester.ac.uk
Views: 11527 methodsMcr
How to determine the Sample Size?
The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In this video I have discussed a very simple way to determine the Sample size with reference.
Views: 56599 My Easy Statistics
Qualitative analysis of interview data: A step-by-step guide
The content applies to qualitative data analysis in general. Do not forget to share this Youtube link with your friends. The steps are also described in writing below (Click Show more): STEP 1, reading the transcripts 1.1. Browse through all transcripts, as a whole. 1.2. Make notes about your impressions. 1.3. Read the transcripts again, one by one. 1.4. Read very carefully, line by line. STEP 2, labeling relevant pieces 2.1. Label relevant words, phrases, sentences, or sections. 2.2. Labels can be about actions, activities, concepts, differences, opinions, processes, or whatever you think is relevant. 2.3. You might decide that something is relevant to code because: *it is repeated in several places; *the interviewee explicitly states that it is important; *you have read about something similar in reports, e.g. scientific articles; *it reminds you of a theory or a concept; *or for some other reason that you think is relevant. You can use preconceived theories and concepts, be open-minded, aim for a description of things that are superficial, or aim for a conceptualization of underlying patterns. It is all up to you. It is your study and your choice of methodology. You are the interpreter and these phenomena are highlighted because you consider them important. Just make sure that you tell your reader about your methodology, under the heading Method. Be unbiased, stay close to the data, i.e. the transcripts, and do not hesitate to code plenty of phenomena. You can have lots of codes, even hundreds. STEP 3, decide which codes are the most important, and create categories by bringing several codes together 3.1. Go through all the codes created in the previous step. Read them, with a pen in your hand. 3.2. You can create new codes by combining two or more codes. 3.3. You do not have to use all the codes that you created in the previous step. 3.4. In fact, many of these initial codes can now be dropped. 3.5. Keep the codes that you think are important and group them together in the way you want. 3.6. Create categories. (You can call them themes if you want.) 3.7. The categories do not have to be of the same type. They can be about objects, processes, differences, or whatever. 3.8. Be unbiased, creative and open-minded. 3.9. Your work now, compared to the previous steps, is on a more general, abstract level. You are conceptualizing your data. STEP 4, label categories and decide which are the most relevant and how they are connected to each other 4.1. Label the categories. Here are some examples: Adaptation (Category) Updating rulebook (sub-category) Changing schedule (sub-category) New routines (sub-category) Seeking information (Category) Talking to colleagues (sub-category) Reading journals (sub-category) Attending meetings (sub-category) Problem solving (Category) Locate and fix problems fast (sub-category) Quick alarm systems (sub-category) 4.2. Describe the connections between them. 4.3. The categories and the connections are the main result of your study. It is new knowledge about the world, from the perspective of the participants in your study. STEP 5, some options 5.1. Decide if there is a hierarchy among the categories. 5.2. Decide if one category is more important than the other. 5.3. Draw a figure to summarize your results. STEP 6, write up your results 6.1. Under the heading Results, describe the categories and how they are connected. Use a neutral voice, and do not interpret your results. 6.2. Under the heading Discussion, write out your interpretations and discuss your results. Interpret the results in light of, for example: *results from similar, previous studies published in relevant scientific journals; *theories or concepts from your field; *other relevant aspects. STEP 7 Ending remark Nb: it is also OK not to divide the data into segments. Narrative analysis of interview transcripts, for example, does not rely on the fragmentation of the interview data. (Narrative analysis is not discussed in this tutorial.) Further, I have assumed that your task is to make sense of a lot of unstructured data, i.e. that you have qualitative data in the form of interview transcripts. However, remember that most of the things I have said in this tutorial are basic, and also apply to qualitative analysis in general. You can use the steps described in this tutorial to analyze: *notes from participatory observations; *documents; *web pages; *or other types of qualitative data. STEP 8 Suggested reading Alan Bryman's book: 'Social Research Methods' published by Oxford University Press. Steinar Kvale's and Svend Brinkmann's book 'InterViews: Learning the Craft of Qualitative Research Interviewing' published by SAGE. Text and video (including audio) © Kent Löfgren, Sweden
Views: 728094 Kent Löfgren
51 Survey Research- Survey Data Analysis-Sample vs Population 51
Survey Data Analysis- Sample vs Population
Coding a survey for SPSS or statistics
This video explains how to create a coding sheet for a survey. Data types and how to code the results of a survey are presented. This information is helpful for research methodology, statistics, or social science courses.
Views: 31592 watsonpho1
How to Analyze Satisfaction Survey Data in Excel with Countif
Purchase the spreadsheet (formulas included!) that's used in this tutorial for $5: https://gum.co/satisfactionsurvey ----- Soar beyond the dusty shelf report with my free 7-day course: https://depictdatastudio.teachable.com/p/soar-beyond-the-dusty-shelf-report-in-7-days/ Most "professional" reports are too long, dense, and jargony. Transform your reports with my course. You'll never look at reports the same way again.
Views: 377063 Ann K. Emery
How to Analyze Survey Data Part 1 - Unpivot Data with Power Query
Checkout the full article and download the file at: http://www.excelcampus.com/pivot-tables/analyze-survey-data-in-excel/ Learn how to use Power Query to transform multiple choice survey data in Excel. This survey data has been exported to Excel in a format that is not easy to use for a pivot table. In this video you will learn how to use the Unpivot feature in Power Query to transform or normalize the data. This will make it easier to analyze with a pivot table and chart. Please subscribe to my free email newsletter to get more Excel tips and tutorials like this. http://www.excelcampus.com/newsletter PART 2: https://youtu.be/h-sKEPEvwZ8 PART 3: https://youtu.be/NBgL8ItVdKY
Views: 38614 Excel Campus - Jon
Methods: Survey Analysis in Small Populations (HD)
Topics: Small sampling fraction, finite population correction, sampling with/without replacement
Views: 219 Dana R Thomson
SPSS for questionnaire analysis:  Correlation analysis
Basic introduction to correlation - how to interpret correlation coefficient, and how to chose the right type of correlation measure for your situation. 0:00 Introduction to bivariate correlation 2:20 Why does SPSS provide more than one measure for correlation? 3:26 Example 1: Pearson correlation 7:54 Example 2: Spearman (rhp), Kendall's tau-b 15:26 Example 3: correlation matrix I could make this video real quick and just show you Pearson's correlation coefficient, which is commonly taught in a introductory stats course. However, the Pearson's correlation IS NOT always applicable as it depends on whether your data satisfies certain conditions. So to do correlation analysis, it's better I bring together all the types of measures of correlation given in SPSS in one presentation. Watch correlation and regression: https://youtu.be/tDxeR6JT6nM ------------------------- Correlation of 2 rodinal variables, non monotonic This question has been asked a few times, so I will make a video on it. But to answer your question, monotonic means in one direction. I suggest you plot the 2 variables and you'll see whether or not there is a monotonic relationship there. If there is a little non-monotonic relationship then Spearman is still fine. Remember we are measuring the TENDENCY for the 2 variables to move up-up/down-down/up-down together. If you have strong non-monotonic shape in the plot ie. a curve then you could abandon correlation and do a chi-square test of association - this is the "correlation" for qualitative variables. And since your 2 variables are ordinal, they are qualitative. Good luck
Views: 513221 Phil Chan
Methods: Survey Analysis in Small Populations (Low)
Topics: Small sampling fraction, finite population correction, sampling with/without replacement
Views: 1579 Dana R Thomson
Research Method : Survey and Sampling
This Lecture talks about survey and sampling.
Views: 19174 cec
Survey Sampling example
Survey Sampling example.mp4
Views: 2991 zedstatistics
SPSS Questionnaire/Survey Data Entry - Part 1
How to enter and analyze questionnaire (survey) data in SPSS is illustrated in this video. Lots more Questionnaire/Survey & SPSS Videos here: https://www.udemy.com/survey-data/?couponCode=SurveyLikertVideosYT Check out our next text, 'SPSS Cheat Sheet,' here: http://goo.gl/b8sRHa. Prime and ‘Unlimited’ members, get our text for free. (Only 4.99 otherwise, but likely to increase soon.) Survey data Survey data entry Questionnaire data entry Channel Description: https://www.youtube.com/user/statisticsinstructor For step by step help with statistics, with a focus on SPSS. Both descriptive and inferential statistics covered. For descriptive statistics, topics covered include: mean, median, and mode in spss, standard deviation and variance in spss, bar charts in spss, histograms in spss, bivariate scatterplots in spss, stem and leaf plots in spss, frequency distribution tables in spss, creating labels in spss, sorting variables in spss, inserting variables in spss, inserting rows in spss, and modifying default options in spss. For inferential statistics, topics covered include: t tests in spss, anova in spss, correlation in spss, regression in spss, chi square in spss, and MANOVA in spss. New videos regularly posted. Subscribe today! YouTube Channel: https://www.youtube.com/user/statisticsinstructor Video Transcript: In this video we'll take a look at how to enter questionnaire or survey data into SPSS and this is something that a lot of people have questions with so it's important to make sure when you're working with SPSS in particular when you're entering data from a survey that you know how to do. Let's go ahead and take a few moments to look at that. And here you see on the right-hand side of your screen I have a questionnaire, a very short sample questionnaire that I want to enter into SPSS so we're going to create a data file and in this questionnaire here I've made a few modifications. I've underlined some variable names here and I'll talk about that more in a minute and I also put numbers in parentheses to the right of these different names and I'll also explain that as well. Now normally when someone sees this survey we wouldn't have gender underlined for example nor would we have these numbers to the right of male and female. So that's just for us, to help better understand how to enter these data. So let's go ahead and get started here. In SPSS the first thing we need to do is every time we have a possible answer such as male or female we need to create a variable in SPSS that will hold those different answers. So our first variable needs to be gender and that's why that's underlined there just to assist us as we're doing this. So we want to make sure we're in the Variable View tab and then in the first row here under Name we want to type gender and then press ENTER and that creates the variable gender. Now notice here I have two options: male and female. So when people respond or circle or check here that they're male, I need to enter into SPSS some number to indicate that. So we always want to enter numbers whenever possible into SPSS because SPSS for the vast majority of analyses performs statistical analyses on numbers not on words. So I wouldn't want and enter male, female, and so forth. I want to enter one's, two's and so on. So notice here I just arbitrarily decided males get a 1 and females get a 2. It could have been the other way around but since male was the first name listed I went and gave that 1 and then for females I gave a 2. So what we want to do in our data file here is go head and go to Values, this column, click on the None cell, notice these three dots appear they're called an ellipsis, click on that and then our first value notice here 1 is male so Value of 1 and then type Label Male and then click Add. And then our second value of 2 is for females so go ahead and enter 2 for Value and then Female, click Add and then we're done with that you want to see both of them down here and that looks good so click OK. Now those labels are in here and I'll show you how that works when we enter some numbers in a minute. OK next we have ethnicity so I'm going to call this variable ethnicity. So go ahead and type that in press ENTER and then we're going to the same thing we're going to create value labels here so 1 is African-American, 2 is Asian-American, and so on. And I'll just do that very quickly so going to Values column, click on the ellipsis. For 1 we have African American, for 2 Asian American, 3 is Caucasian, and just so you can see that here 3 is Caucasian, 4 is Hispanic, and other is 5, so let's go ahead and finish that. Four is Hispanic, 5 is other, so let's go to do that 5 is other. OK and that's it for that variable. Now we do have it says please state I'll talk about that next that's important when they can enter text we have to handle that differently.
Views: 564098 Quantitative Specialists
Central Statistics Office (CSO), National Sample Survey Office (NSSO)  EXPLAIN ANALYSIS EASY TRICK
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Views: 3870 Tosh Lubek
How to enter survey data into Excel from a pen-and-paper questionnaire
I show my technique of entering raw data into Microsoft Excel that has been collected via a pen-and-paper survey. This includes both questions with fixed responses and open-ended questions. Copyright: Text and video © Kent Löfgren, Sweden.
Views: 107266 Kent Löfgren
How to tabulate, analyze, and prepare graph from Likert Scale questionnaire data using Ms Excel.
This video describes the procedure of tabulating and analyzing the likert scale survey data using Microsoft Excel. This video also explains how to prepare graph from the tabulated data. Photo courtesy: http://littlevisuals.co/
Views: 109455 Edifo
53 Survey Research-Survey Data Analysis
Survey Data Analysis- Calculating Survey Sampling Error and Confidence Intervals
R for Every Survey Analysis
Delivered by Max Richman at the inaugural New York R Conference in New York City at Work-Bench on Friday, April 24th, and Saturday, April 25th.
Views: 6137 Work-Bench
SPSS Tutorial 5 - The Opinions Survey Dataset & Univariate Analysis
This video introduces the Opinions Survey Dataset, which will be used in the rest of these tutorials. You can download the data set used in these videos here: http://goo.gl/GpXK4D Information on the origins, license and permissions for this data set can be downloaded here: http://goo.gl/bhc07L
Views: 44355 patrickkwhite
Part 1 - Using Excel for Open-ended Question Data Analysis
Completing data analysis on open-ended questions using Excel. For analyzing multiple responses to an open-ended question see Part 2: https://youtu.be/J_whxIVjNiY Note: Selecting "HD" in the video settings (click on the "gear" icon) makes it easier to view the data entries
Views: 165268 Jacqueline C
How to Conduct a Market Research Survey
Watch more Advertising & Marketing 101 videos: http://www.howcast.com/videos/314251-How-to-Conduct-a-Market-Research-Survey Market research surveys help businesses understand marketing preferences and trends by gathering data from potential customers. Step 1: Decide on your research approach Decide whether you will ask quantitative or qualitative questions. Quantitative research yields hard numbers, while qualitative research looks for open-ended responses to research questions. Step 2: Decide who to survey Decide who to include in your marketing survey. Tip Select a random sample of respondents and optimize your sample size for survey accuracy Step 3: Decide what questions to ask Decide what questions you will ask. Tip Questions asked in quantitative studies should be clear and should not lead respondents toward a particular response. The order in which questions are asked can also be important. Step 4: Recruit interviewers Recruit your interviewers. Make sure they have relevant skills. Step 5: Analyze your results Conduct your survey and analyze the results. Did You Know? Marketing survey research positions have increased in the past decade due to an increase in the number of customer databases and greater global competition.
Views: 25378 Howcast
Sample Survey Analysis and Errors
Sample Survey Analysis and Errors
Views: 129 Laura DeWitt
Survey Package in R
Complex designs are common in survey data. In practice, collecting random samples from a populations is costly and impractical. Therefore the data are often non-independent or disproportionately sampled, and violate the typical assumption of independent and identically distributed samples (IDD). The Survey package in R (written by Thomas Lumley) is a powerful tool that incorporates survey designs to the data. Standard statistics, from linear models to survival analysis, are implemented with the corresponding mathematical corrections. This talk will provide an introduction to survey statistics and the Survey package. There will be a brief overview of complex designs and some of the theory behind their analysis, followed by a demonstration using the Survey package. Sebastián Duchêne is a Ph.D. candidate at The University of Sydney, based at the Molecular Phylogenetics, Ecology, and Evolution Lab. His broad area of research is virus evolution. His current projects include an R package for evolutionary analysis, and the development of statistical models for molecular epidemiology. In addition to his PhD studies, he is a reviewer for the PLoS ONE academic journal in the area of evolution and bioinformatics. Before coming to Sydney, he was a data analyst at the National Oceanic and Atmospheric Administration (NOAA) in the USA.
Views: 8438 Jeromy Anglim
Data Analysis in SPSS Made Easy
Use simple data analysis techniques in SPSS to analyze survey questions.
Views: 835515 Claus Ebster
A Regression Tutorial Using the World Values Survey
A Regression Tutorial Using the World Values Survey
Views: 5699 Philip Truscott
NSSO survey‎: A detailed analysis
Money Mantra: A panel of experts share their views on the household consumer expenditure survey for 2009-10, released by the National Sample Survey Office ( NSSO), which shows rising real spending in rural areas, even though it is almost half of urban India's, suggesting increasing incomes.
Views: 10987 NDTV Profit
Preparing raw survey data for ANOVA in Excel
This video describes how to prepare raw survey data in an Excel sheet for running an analysis of variance (ANOVA) test.
Views: 15266 Chris Olson
Analyzing Your Survey Results — SurveyMonkey
Curious how you can benefit from sending a survey? Check out this example and learn how easy it is to uncover insights and answer your burning questions. Start analyzing your survey results today.
Views: 8505 SurveyMonkey
How to Write a Survey or Questionnaire
Watch more Business Communication videos: http://www.howcast.com/videos/383549-How-to-Write-a-Survey-or-Questionnaire To write a survey or questionnaire, you want to cover every possibility and avoid being misunderstood. Make sure you know what information you're after and make it easy for your subjects to help you find it. Step 1: Prepare information Prepare by defining the issues you are exploring and the objectives for the questionnaire. Clarify specifically what you want answered, eliminating generalizations, so that you can draw reliable data. Step 2: Design questions Design succinct and unambiguous questions with familiar words, and no abbreviations or double negatives. Be specific about timing, for instance, by stipulating "Every three hours" instead of "Often." Tip Open-format questions invite free-wheeling responses that tend to be subjective. Closed-format questions, like multiple choice, are easier to tabulate and track for useful information. Step 3: Separate questions Separate questions rather than making them dependent on previous or subsequent questions. Dependent questions can confuse, alienate, and add a level of uncertainty in your findings. Step 4: Do not lead Avoid writing a survey or questionnaire that uses leading questions that, intentionally or not, preserve the likelihood of a certain result. Offer clearly distinct choices. Step 5: Encompass responses Ask questions that anticipate and encompass all possible responses. Tip Expanding multiple choice surveys beyond four or five will dilute the results. Step 6: Organize Group the questions logically. Make them simple, direct, and unthreatening. If someone suspects an agenda, they will not answer truthfully. Step 7: Test survey Test your questionnaire or survey on a small but similar group before starting the official study. Get feedback about how questions were interpreted and suggestions on how to fix problems. Revise the survey based on your results, and you will be on your way to creating a clear study. Did You Know? Gallup found a 12 percent increase in voters who call themselves Independents between elections in 2007, when their numbers rose to 37 percent of the voting public, more than either Democrats or Republicans.
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