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Your Survey Closed, Now What? Quantitative Analysis Basics
 
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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: 16961 CSSLOhioStateU
How to Analyze Survey Data Part 1 - Unpivot Data with Power Query
 
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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: 32952 Excel Campus - Jon
Analysing Questionnaires
 
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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/
Fundamentals of Qualitative Research Methods: Data Analysis (Module 5)
 
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Qualitative research is a strategy for systematic collection, organization, and interpretation of phenomena that are difficult to measure quantitatively. Dr. Leslie Curry leads us through six modules covering essential topics in qualitative research, including what it is qualitative research and how to use the most common methods, in-depth interviews and focus groups. These videos are intended to enhance participants' capacity to conceptualize, design, and conduct qualitative research in the health sciences. Welcome to Module 5. Bradley EH, Curry LA, Devers K. Qualitative data analysis for health services research: Developing taxonomy, themes, and theory. Health Services Research, 2007; 42(4):1758-1772. Learn more about Dr. Leslie Curry http://publichealth.yale.edu/people/leslie_curry.profile Learn more about the Yale Global Health Leadership Institute http://ghli.yale.edu
Views: 146209 YaleUniversity
How to Analyze Satisfaction Survey Data in Excel with Countif
 
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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: 346456 Ann K. Emery
Data Analysis in SPSS Made Easy
 
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Use simple data analysis techniques in SPSS to analyze survey questions.
Views: 791931 Claus Ebster
How to analyze your data and write an analysis chapter.
 
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In this video Dr. Ziene Mottiar, DIT, discusses issues around analyzing data and writing the analysing chapter. The difference between Findings and Analysis chapters is also discussed. This video is useful for anyone who is writing a dissertation or thesis.
Views: 64328 ZieneMottiar
3.6 Research Strategy: Survey
 
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Do you like this video? Check out full course on Udemy only for 9.99 USD with following link: https://www.udemy.com/research-methods-for-business-students/?couponCode=RESEARCH_METHODS_1 Survey is a research strategy that is very often used among business administration and marketing students. It will allow us to collect large amount of standardized data for instance through questionnaires. In this video we will talk just through the very basics of this research strategy.
Views: 674 MeanThat
How to tabulate, analyze, and prepare graph from Likert Scale questionnaire data using Ms Excel.
 
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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: 78922 Edifo
Data Analysis & Discussion
 
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This video is meant to be used as an introductory lesson to Mini Research Writing focusing on Data Analysis and Discussion. As this is a mini class project, some of the requirements have been made simple due to time constraints. Plus, the focus of this mini research paper is to get students familiarized to the ways of writing an academic paper and the items that needs to be included. suitable for beginners!
Views: 16898 NurLiyana Isa
Sampling Methods and Bias with Surveys: Crash Course Statistics #10
 
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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: 65814 CrashCourse
Choosing which statistical test to use - statistics help.
 
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Seven different statistical tests and a process by which you can decide which to use. The tests are: Test for a mean, test for a proportion, difference of proportions, difference of two means - independent samples, difference of two means - paired, chi-squared test for independence and regression. This video draws together videos about Helen, her brother, Luke and the choconutties. There is a sequel to give more practice choosing and illustrations of the different types of test with hypotheses.
Views: 680130 Dr Nic's Maths and Stats
SPSS Questionnaire/Survey Data Entry - Part 1
 
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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: 458929 Quantitative Specialists
Mini Statistics Lecture: Analyzing Likert Scale Questionnaire Data using R
 
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Likert Scale: http://en.wikipedia.org/wiki/Likert_scale R: http://www.r-project.org/
Views: 200803 Alan Cann
SPSS for questionnaire analysis:  Correlation analysis
 
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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: 494941 Phil Chan
How to Analyze Survey Data - Questionpro Webinar
 
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Join us as we look into the most frequently used question types, and how to effectively analyze your findings.
Views: 813 QuestionPro
Methods of collecting survey data
 
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What kind of survey should I create? Political Science Professor Kenneth Fernandez discusses the pros and cons of each survey collection method. He also outlines 3 questions to ask yourself as you’re choosing a survey method.
Views: 22951 Elon University Poll
Survey Data Analysis using Google Form surveys
 
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Survey Data Analysis using Google Form surveys
Views: 27472 HiMrBogle
DataCracker - How To Analyze Survey Data
 
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https://www.datacracker.com/ DataCracker is web-based survey data analysis software. Easily analyze your survey data. It provides you with statistical test results on your data without requiring expert knowledge in market research. Upload your data, and DataCracker will automatically discover significant results and write a basic report with tables and charts. You can dig deep into your data using advanced data analysis tools that allow you to discover segments and perform predictive analytics.
Views: 3030 DataCracker
Data Collection I: Surveys, Interviews, Observations (COM1110 English Communication Skills)
 
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Lecture on data collection methods (survey, interview and observations) for COM1110 English Communication Skills)
Views: 16530 Lisa Kwan
Part 1 - Using Excel for Open-ended Question Data Analysis
 
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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: 155261 Jacqueline C
How to enter survey data into Excel from a pen-and-paper questionnaire
 
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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: 88149 Kent Löfgren
Qualtrics Series Part III: Survey Distribution & Data Analysis
 
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Prepare a survey instrument for distribution, construct a link for your instrument, and convert survey responses to analyzable data files in Qualtrics. The video was recorded as part of a teaching assistantship in EPY 710: Survey Research Methods with Alice Corkill, Ph.D. using Camtasia software.
Qualitative analysis of interview data: A step-by-step guide
 
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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; *it surprises you; *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. 3.10. 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 This tutorial showed how to focus on segments in the transcripts and how to put codes together and create categories. However, it is important to remember that 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. Good luck with your study. Text and video (including audio) © Kent Löfgren, Sweden
Views: 667530 Kent Löfgren
How to Analyze Survey Data Part 3 - Summarize with Pivot Tables and Charts
 
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Checkout the full article and download the file at: http://www.excelcampus.com/pivot-tables/analyze-survey-data-in-excel/ In this third part of the series we learn how to use Pivot Tables and formulas to analyze the multiple choice survey data. We also create a chart that shows the percentage of total responses for each item (choice) in the survey question. 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: 31802 Excel Campus - Jon
Using Tableau Software to Analyze Survey Data
 
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Learn how leveraging Tableau's drag and drop methodology can help you visualize your survey data in more meaningful ways so you are able to derive richer insights. And discover how their interactive dashboard reports makes it easier to share high impact results with less effort.
Analyzing Research Questionnaire using SPSS
 
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How to analyze a research questionnaire data that has been collected using SPSS. The proper techniques that are based on your research objectives and hypothesis are used. The analysis of the data is done by focusing on reliability of the questionnaire. Descriptive analysis, frequencies, correlation, factor analysis and regression analysis.
Views: 20311 Knowledge Abundance
Surveys as a qualitative research method
 
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Surveys as a qualitative research method
Views: 4392 DrKKHewitt
Reliability in Survey Design
 
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An in-depth look at measuring reliability in survey items
Views: 1969 Jessica Uriarte
Descriptive Statistics and Surveys
 
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Communication Research Methods - Week 4 Descriptive Statistics and Surveys
Views: 1280 Dan's Academy
Student Surveys Data Analysis
 
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Student Surveys Data Analysis
Views: 85 Dustin Washam
Preliminary Quantitative Analysis of Survey Data
 
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Cursory review quantitative elements of the survey data.
Views: 2290 moriartp1
AP Statistics: Sample Surveys, Bias, and Sampling Methods
 
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This video goes over the big ideas when it comes to samples from a population, bias in samples, and different sampling methods.
Views: 23664 Michael Porinchak
Correlation analysis using Excel
 
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How to run a correlation analysis using Excel and write up the findings for a report
Views: 288187 Chris Olson
Qualitative Data Analysis: Working with Surveys in MAXQDA
 
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In this video tutorial, we'll show you how to import and analyze qualitative and quantitative survey data with MAXQDA 2018.
Views: 298 MAXQDA VERBI
Qualitative Data Analysis - Coding & Developing Themes
 
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This is a short practical guide to Qualitative Data Analysis
Views: 97888 James Woodall
Enter data from a questionnaire, Ex 4: Ranked response
 
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Enter and define variables from a questionnaire in SPSS. This example looks at a question in which participants rank a list of items. ASK SPSS Tutorial Series
Views: 57804 BrunelASK
Questionnaire Formation for Data Collection & Statistical Analysis (For Beginners in Urdu)
 
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In order to tell how to prepare a questionnaire for Survey research this video is made i hope it will help you a lot. If you have anything to ask about or anything to add into this video you are welcome to give your valuable comments in comments box Be gentle and nice when you say something, Thank you Subscribe for more:)
Sampling & its 8 Types: Research Methodology
 
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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
Views: 269759 Examrace
how to analyze questionnaire data from excel spss
 
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This video shows the idea of data analysis from MS Excel to SPSS. The easier way to run the descriptive statistic for your questionnaire of customer satisfaction survey. The first thing you should do is setting up your questionnaire, then extract, coding and run for analysis using SPSS. If you interested to learn more about our video, trick and analysis of SPSS and statistical procedure, visit our website at http://kajidataonline.com To learn SPSS freely visit: http://spss.kajidataonline.com/online/login/index.php Please subscribe and share our videos to your friend and families. Thanks Admin
Views: 66 Kajidataonline
Coding Multiple Variables and Open-ended Questions. Part 2 of 3 on Quantitative Coding
 
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A lecture on coding and data entry in quantitative research by Graham R Gibbs taken from a series on quantitative data analysis and statistics given to undergraduate students at the University of Huddersfield. This is part 2 of 3 and examines how to deal with questions with more than one answer and questions with open-ended answers. Credits: Music: Kölderen Polka by Tres Tristes Tangos is licensed under an Attribution-ShareAlike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos/ Image: Ice-ferns by Schnobby, Wikimedia Commons, licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
Views: 71422 Graham R Gibbs
Differential Abundance Analysis for Microbial Marker-Gene Surveys
 
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Presented At: LabRoots Genetics & Genomics Virtual Event 2018 Presented By: Joseph Paulson, PhD - Research Fellow, Dana-Farber Cancer Institute Speaker Biography: I am a Research Fellow in the Department of Biostatistics and Computational Biology at the Dana-Farber Cancer Institute and Department of Biostatistics at the Harvard TH Chan School of Public Health under the guidance of Professor John Quackenbush. Prior to joining Harvard I was a National Science Foundation Graduate Research Fellow at the University of Maryland, College Park where I received my Ph.D. in Applied Mathematics, Statistics and Scientific Computation. As a computer scientist and computational biologist, my interests are to develop computational methods for the analysis of high-throughput sequencing data. I also desire to develop software and support these methods as open-source software for the broader scientific community through Bioconductor and popular domain tools such as QIIME and Phyloseq. MetagenomeSeq, is my most popular tool developed and is in the top 5% of all Bioconductor packages downloaded in the last year with over 5,000 unique users. I am excited to leverage statistical and network methodologies in accounting for technological when identifying disease markers. Webinar: Differential Abundance Analysis for Microbial Marker-Gene Surveys Webinar Abstract: We introduce a differential abundance analysis method for the analysis of sparse high-throughput data from large-scale surveys of marker genes for microbial communities. Our approach relies on cumulative sum scaling (CSS) normalization - a count data normalization technique - and the zero-inflated Gaussian (ZIG) model as a statistical method for detecting differential abundance of taxonomic features. ZIG differential abundance detection method accounts for bias introduced by the under-sampling of microbial communities commonly found in large-scale marker gene studies. We have implemented these methods in the publicly available metagenomeSeq bioconductor package. In addition we highlight the utility of the method in a large scale study characterizing the diarrheal microbiome in young children from developing children. Diarrhea, a major cause of mortality and morbidity in young children from developing countries, leading to as many as 15% of all deaths in children under 5 years of age. While many causes of this disease are already known, conventional diagnostic approaches fail to detect a pathogen in up to 60% of diarrheal cases. Using our novel methodology Streptococci were found in our study to be statistically associated with diarrheal disease in general and more severe forms (such as dysentery) in particular. Earn PACE/CME Credits: 1. Make sure you’re a registered member of LabRoots (https://www.labroots.com/virtual-event/genetics-genomics-2018) 2. Watch the webinar on YouTube above or on the LabRoots Website (https://www.labroots.com/virtual-event/genetics-genomics-2018) 3. Click Here to get your PACE (Expiration date – May 10, 2020 06:00 AM)– https://www.labroots.com/credit/pace-credits/2873/third-party LabRoots on Social: Facebook: https://www.facebook.com/LabRootsInc Twitter: https://twitter.com/LabRoots LinkedIn: https://www.linkedin.com/company/labroots Instagram: https://www.instagram.com/labrootsinc Pinterest: https://www.pinterest.com/labroots/ SnapChat: labroots_inc
Views: 116 LabRoots

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