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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: 168517 YaleUniversity
Introduction to experimental design and analysis of variance (ANOVA)
 
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Covers introduction to design of experiments. Includes, - one-way analysis of variance (ANOVA) - two-way ANOVA - Use of Microsoft Excel for developing ANOVA table Design of experiments is considered heart of the six-sigma DMAIC process and heavily used during improvement phase.
Views: 57471 Bharatendra Rai
9. Understanding Experimental Data
 
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MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 View the complete course: http://ocw.mit.edu/6-0002F16 Instructor: Eric Grimson Prof. Grimson talks about how to model experimental data in a way that gives a sense of the underlying mechanism and to predict behavior in new settings. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 15108 MIT OpenCourseWare
Types of statistical studies | Study design | AP Statistics | Khan Academy
 
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Types of statistical studies. View more lessons or practice this subject at http://www.khanacademy.org/math/ap-statistics/gathering-data-ap/types-of-studies-experimental-vs-observational/v/types-of-statistical-studies?utm_source=youtube&utm_medium=desc&utm_campaign=apstatistics AP Statistics on Khan Academy: Meet one of our writers for AP¨_ Statistics, Jeff. A former high school teacher for 10 years in Kalamazoo, Michigan, Jeff taught Algebra 1, Geometry, Algebra 2, Introductory Statistics, and AP¨_ Statistics. Today he's hard at work creating new exercises and articles for AP¨_ Statistics. Khan Academy is a nonprofit organization with the mission of providing a free, world-class education for anyone, anywhere. We offer quizzes, questions, instructional videos, and articles on a range of academic subjects, including math, biology, chemistry, physics, history, economics, finance, grammar, preschool learning, and more. We provide teachers with tools and data so they can help their students develop the skills, habits, and mindsets for success in school and beyond. Khan Academy has been translated into dozens of languages, and 15 million people around the globe learn on Khan Academy every month. As a 501(c)(3) nonprofit organization, we would love your help! Donate or volunteer today! Donate here: https://www.khanacademy.org/donate?utm_source=youtube&utm_medium=desc Volunteer here: https://www.khanacademy.org/contribute?utm_source=youtube&utm_medium=desc
Views: 48405 Khan Academy
Types of statistical studies | Statistical studies | Probability and Statistics | Khan Academy
 
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Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/probability/statistical-studies/types-of-studies/e/types-of-statistical-studies?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Watch the next lesson: https://www.khanacademy.org/math/probability/statistical-studies/types-of-studies/v/correlation-and-causality?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/statistical-studies/statistical-questions/v/reasonable-samples?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Probability and statistics on Khan Academy: We dare you to go through a day in which you never consider or use probability. Did you check the weather forecast? Busted! Did you decide to go through the drive through lane vs walk in? Busted again! We are constantly creating hypotheses, making predictions, testing, and analyzing. Our lives are full of probabilities! Statistics is related to probability because much of the data we use when determining probable outcomes comes from our understanding of statistics. In these tutorials, we will cover a range of topics, some which include: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. So buckle up and hop on for a wild ride. We bet you're going to be challenged AND love it! About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to KhanAcademy’s Probability and Statistics channel: https://www.youtube.com/channel/UCRXuOXLW3LcQLWvxbZiIZ0w?sub_confirmation=1 Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 170907 Khan Academy
5.1 Using Secondary Data In Your Research
 
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If you are having troubles with your research paper, I might have a solution for you. My full course "Research Methods for Business Students" is available on Udemy. Here you can also submit YOUR questions to me and receive FEEDBACK ON YOUR PAPER! As you are my students, the course is only for 9.99 USD with following link: https://www.udemy.com/research-methods-for-business-students/?couponCode=RESEARCH_METHODS_1
Views: 3079 MeanThat
When To Use A Qualitative Research Design? 4 Things To Consider
 
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This video discusses when one should choose to use a qualitative research design. There are 4 things to consider: are you a terrible statistician? is your supervisor a qualitative or quantitative researcher? what do you know about qualitative data analysis? and is your research question exploratory?... My other research videos: Zhang, R. (2017). When to use a qualitative research design? Four things to consider. [Video File]. Retrieved from https://youtu.be/4FJPNStnTvA Zhang, R. (2017). What is a good Central Research Question? [Video File]. Retrieved from https://youtu.be/I4MfCDy7wDw Zhang, R. (2017). Research aim, research objective, research question, and investigative question. [Video File]. Retrieved from https://youtu.be/ujKIM59hy9I Zhang, R. (2016) Research Types, Research Designs, Data Collection, and Sampling. [Video File]. Retrieved from https://youtu.be/WY9j_t570LY Please LIKE this video if you enjoyed it. Otherwise, there is a thumb-down button, too... :P ▶ Please SUBSCRIBE to see new videos (almost) every week! ◀ ▼MY OTHER CHANNEL (MUSIC AND PIANO TUTORIALS)▼ https://www.youtube.com/ranywayz ▼MY SOCIAL MEDIA PAGES▼ https://www.facebook.com/ranywayz https://nl.linkedin.com/in/ranywayz https://www.twitter.com/ranywayz Animations are made with Sparkol. Music files retrieved from YouTube Audio Library. All images used in this video are free stock images or are available in the public domain. The views expressed in this video are my own and do not necessarily reflect the organizations with which I am affiliated.
Views: 13200 Ranywayz Random
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: 26734 NurLiyana Isa
Experimental Process and Data Collection for the Scientific Method
 
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Experimental Process. Mr. Causey discusses the Experimental Process or otherwise known as the testing part of the scientific method. http://www.yourCHEMcoach.com SUBSCRIBE for more chemistry videos: http://bit.ly/1jeutVl ABOUT MR. CAUSEY'S VIDEO ACADEMY Mr. Causey's Video Academy is an educational video series of short video lessons for chemistry, algebra and physics. You can get lessons on a variety of topics or homework helpers that show you how to solve certain problems. There are over 120 videos to choose from. CONTACT ME: [email protected] FOLLOW ME: http://www.twitter.com/#!/mrcausey http://www.twitter.com/#!/mr_causey http://pinterest.com/mistercausey/ http://www.facebook.com/profile.php?id=814523544 https://plus.google.com/u/0/111105504415887392612 RESOURCES: Polyatomic Ion Cheat Sheet: http://bit.ly/14e2pbw Periodic Table: http://bit.ly/ptable9 RELATED VIDEOS: Scientific Method: http://www.youtube.com/watch?v=9PUPcsEEoNE The process of science is the scientific method but truly the most important step is the testing or experimenting. The experimental process is what makes the scientific study different from other disciplines. If you are doing science right you are collecting and providing proof of your ideas. You need to design a step by step experiment, determine the independent variable, the dependent variables and devise a method to properly collect data. Then and only then, you can truly analyze your work.
Views: 26013 Mr. Causey
Research design: interview analysis basics
 
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A short video covering some very basic introductory ideas about how to analyse interview data. This is aimed at people trying out interviews for the first time, to help you figure out what to do with the data!
Views: 1978 Nick Hopwood
Quantitative Research Designs: Descriptive non-experimental, Quasi-experimental or Experimental?
 
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http://youstudynursing.com/ Get my research terminology eBook on Amazon: http://amzn.to/1hB2eBd Students often have difficulty classifying quantitative research designs. In quantitative research, designs can be classified into one of three categories: descriptive non-experimental, quasi-experimental or experimental. To identify which of these designs your study is using follow the steps in this video. Check out the links below and SUBSCRIBE for more youtube.com/user/NurseKillam **The PDF version of my book is better and is being approved by Google Play right now. For help with Research - Get my eBook "Research terminology simplified: Paradigms, axiology, ontology, epistemology and methodology" here: http://books.google.ca/books/about/Research_terminology_simplified.html?id=tLMRAgAAQBAJ&redir_esc=y Related Videos: http://www.youtube.com/watch?v=UA0-RMPi7qE&feature=share&list=PLs4oKIDq23AdTCF0xKCiARJaBaSrwP5P2 Connect with me on Facebook Page: https://www.facebook.com/NursesDeservePraise Twitter: @NurseKillam https://twitter.com/NurseKillam Facebook: https://www.facebook.com/laura.killam LinkedIn: http://ca.linkedin.com/in/laurakillam Students often have difficulty classifying quantitative research designs. In quantitative research, designs can be classified into one of three categories: descriptive non-experimental, quasi-experimental or experimental. To identify which of these designs your study is using follow the steps in this video. First, ask yourself if the researchers did anything to the participants. More specifically, was there an intervention? ...If the answer is yes, there was an intervention, then the study is either a quasi-experimental or experimental. I will tell you how to decide in a moment. If the answer is no, the study is descriptive non-experimental. Sure, you could be more specific in the description of the design, but for the purposes of grouping your research in a literature review this label is often sufficient at an undergraduate level. Descriptive non-experimental studies may also be called observational. Some examples of more specific labels include case control, cohort and correlational studies. ... To find out if the design is experimental ask yourself if it is a randomized controlled trial. Randomized controlled trials are considered the gold standard or "best" possible design (in quantitative research). You may also hear randomized controlled trails referred to as true experiments. However, in the real world it is difficult to conduct a true randomized controlled trial in many situations, which means that a lot of studies are done that are not classified as randomized controlled trials. Randomized control trials have three key components: a random sample, a control group and an intervention. If your study is truly a randomized control trial it should say in the abstract and/or the methods section of the article. If it doesn't say then it is likely that the study is either descriptive non-experimental or quasi-experimental. You can tell the difference by looking into the methods section further. ...If there is no control group than the study is quasi-experimental. A control group is a group of people that enter the study but do not receive the intervention under study. Instead, they are used for the purpose of comparison. If the sample was not randomized properly or adequately or even at all then the study is also quasi-experimental. You may also see this type of study being called a non-randomized trial. ... Sometimes I see students that are confused about the study design because of terms that relate to the length of time the study was conducted or the sampling process. ... Terms like cross-sectional and longitudinal tell you how much time the study was conducted over. Cross sectional means that data were collected at one point in time. Longitudinal means that data were collected over a long period of time. These terms alone will not tell you if the study is descriptive non-experimental, quasi-experimental or experimental. If you use these words to describe your study design in the absence of one of the labels we discussed in this video you will not have given your teacher enough information about the study design to properly classify it. Other confusing terms often relate to the way samples were collected, like convenience sampling. Convenience sampling means that the sample was readily available or accessible to the researchers. This term will give you the hint that the study does not have a random sample and is therefore not a randomized controlled trial, but you still need to classify it further as descriptive non-experimental or quasi-experimental. To decide how to classify the design of a study you are looking at, follow the steps outlined in this video. Ask yourself the following three questions: Was there an intervention? Is there a control group? Was the sample random? ...
Views: 203715 NurseKillam
Class 1: introduction to research data analysis
 
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PSYC 440/640 is called "Experimental Methods", but really the course is mostly about data analytic techniques that could be used in a variety of research contexts, including both experimental studies, and non-experimental studies. This lecture provides a brief introduction to the course and to the topics that we will cover in this course. It also reviews the whole research process, to show how research design, methods, and analyses are connected.
Views: 512 Keith Donohue
Grounded Theory | Overview
 
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Grounded Theory is a Qualitative approach that let's theory emerge from data. This video is a conversation starter about Grounded Theory basics and shows some examples of axial coding. Coding, categories, and memoing. There a various types of Grounded Theory and two particular popular methods are highlighted.
Views: 50539 Diana Lizarraga
SPSS: How To Perform Quantitative Data Analyses For Bachelor's Research? 5 Basic Analysis Methods
 
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1. Descriptives: 1:32 2. T test: 2:52 3. Correlation: 4:41 4. Chi square: 5:39 5. Linear regression: 6:45 This video discusses the basic statistical analytical procedures that are required for a typical bachelor's thesis. Five stats are highlighted here: descriptives, T test, correlation, Chi square, and linear regression. For requirements on reporting stats, please refer to the appendix of your research module manuals -- Frans Swint and I wrote an instructional text on APA reporting of stats. There is no upper limit in terms of how advanced your stats should be in your bachelor's dissertation. This video covers the basic procedures and is not meant to replace the instructions of your own research supervisor. Please consult your own research advisor for specific questions regarding your data analyses. Please LIKE this video if you enjoyed it. Otherwise, there is a thumb-down button, too... :P ▶ Please SUBSCRIBE to see new videos (almost) every week! ◀ ▼MY OTHER CHANNEL (MUSIC AND PIANO TUTORIALS)▼ https://www.youtube.com/ranywayz ▼MY SOCIAL MEDIA PAGES▼ https://www.facebook.com/ranywayz https://nl.linkedin.com/in/ranywayz https://www.twitter.com/ranywayz Animations are made with Sparkol. Music files retrieved from YouTube Audio Library. All images used in this video are free stock images or are available in the public domain. The views expressed in this video are my own and do not necessarily reflect the organizations with which I am affiliated. #RanywayzRandom #SPSS #Research
Views: 7172 Ranywayz Random
Qualitative Analysis: Coding and Categorizing Data by Philip Adu, Ph.D.
 
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Data analysis is all about data reduction. But how do you reduce data without losing the meaning? What is the coding process? What coding strategies can you use? How do you make sure the categories or themes address your research question(s)? How do you present your qualitative findings in a meaningful manner? If you want answers to these questions, watch this video. To access the PowerPoint slides, please go to:https://www.slideshare.net/kontorphilip/qualitative-analysis-coding-and-categorizing To buy Dr. Philip Adu's new book, 'A Step-by-Step Guide to Qualitative Data Coding', please go to Amazon (https://www.amazon.com/Step-Step-Guide-Qualitative-Coding/dp/1138486876/ref=sr_1_3?ie=UTF8&qid=1543874247&sr=8-3&keywords=Philip+adu)
What is COMPARATIVE RESEARCH? What does COMPARATIVE RESEARCH mean? COMPARATIVE RESEARCH meaning
 
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What is COMPARATIVE RESEARCH? What does COMPARATIVE RESEARCH mean? COMPARATIVE RESEARCH meaning - COMPARATIVE RESEARCH definition - COMPARATIVE RESEARCH explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. SUBSCRIBE to our Google Earth flights channel - https://www.youtube.com/channel/UC6UuCPh7GrXznZi0Hz2YQnQ Comparative research is a research methodology in the social sciences that aims to make comparisons across different countries or cultures. A major problem in comparative research is that the data sets in different countries may not use the same categories, or define categories differently (for example by using different definitions of poverty). Comparative research, simply put, is the act of comparing two or more things with a view to discovering something about one or all of the things being compared. This technique often utilizes multiple disciplines in one study. When it comes to method, the majority agreement is that there is no methodology peculiar to comparative research. The multidisciplinary approach is good for the flexibility it offers, yet comparative programs do have a case to answer against the call that their research lacks a "seamless whole." There are certainly methods that are far more common than others in comparative studies, however. Quantitative analysis is much more frequently pursued than qualitative, and this is seen by the majority of comparative studies which use quantitative data. The general method of comparing things is the same for comparative research as it is in our everyday practice of comparison. Like cases are treated alike, and different cases are treated differently; the extent of difference determines how differently cases are to be treated. If one is able to sufficiently distinguish two carry the research conclusions will not be very helpful. Secondary analysis of quantitative data is relatively widespread in comparative research, undoubtedly in part because of the cost of obtaining primary data for such large things as a country's policy environment. This study is generally aggregate data analysis. Comparing large quantities of data (especially government sourced) is prevalent. A typical method of comparing welfare states is to take balance of their levels of spending on social welfare. In line with how a lot of theorizing has gone in the last century, comparative research does not tend to investigate "grand theories," such as Marxism. It instead occupies itself with middle-range theories that do not purport to describe our social system in its entirety, but a subset of it. A good example of this is the common research program that looks for differences between two or more social systems, then looks at these differences in relation to some other variable coexisting in those societies to see if it is related. The classic case of this is Esping-Andersen's research on social welfare systems. He noticed there was a difference in types of social welfare systems, and compared them based on their level of decommodification of social welfare goods. He found that he was able to class welfare states into three types, based on their level of decommodification. He further theorized from this that decommodification was based on a combination of class coalitions and mobilization, and regime legacy. Here, Esping-Andersen is using comparative research: he takes many western countries and compares their level of decommodification, then develops a theory of the divergence based on his findings. Comparative research can take many forms. Two key factors are space and time. Spatially, cross-national comparisons are by far the most common, although comparisons within countries, contrasting different areas, cultures or governments also subsist and are very constructive, especially in a country like New Zealand, where policy often changes depending on which race it pertains to. Recurrent interregional studies include comparing similar or different countries or sets of countries, comparing one's own country to others or to the whole world....
Views: 5862 The Audiopedia
Worked example identifying observational study | Study design | AP Statistics | Khan Academy
 
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Worked example identifying observational study. View more lessons or practice this subject at http://www.khanacademy.org/math/ap-statistics/gathering-data-ap/types-of-studies-experimental-vs-observational/v/worked-example-identifying-observational-study?utm_source=youtube&utm_medium=desc&utm_campaign=apstatistics AP Statistics on Khan Academy: Meet one of our writers for AP¨_ Statistics, Jeff. A former high school teacher for 10 years in Kalamazoo, Michigan, Jeff taught Algebra 1, Geometry, Algebra 2, Introductory Statistics, and AP¨_ Statistics. Today he's hard at work creating new exercises and articles for AP¨_ Statistics. Khan Academy is a nonprofit organization with the mission of providing a free, world-class education for anyone, anywhere. We offer quizzes, questions, instructional videos, and articles on a range of academic subjects, including math, biology, chemistry, physics, history, economics, finance, grammar, preschool learning, and more. We provide teachers with tools and data so they can help their students develop the skills, habits, and mindsets for success in school and beyond. Khan Academy has been translated into dozens of languages, and 15 million people around the globe learn on Khan Academy every month. As a 501(c)(3) nonprofit organization, we would love your help! Donate or volunteer today! Donate here: https://www.khanacademy.org/donate?utm_source=youtube&utm_medium=desc Volunteer here: https://www.khanacademy.org/contribute?utm_source=youtube&utm_medium=desc
Views: 15040 Khan Academy
Qualitative Research Designs
 
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Table of Contents: 02:26 - MAJOR PHILOSOPHICAL TRADITIONS/RESEARCH PARADIGMS YOU WILL ENCOUNTER IN EDUCATION 10:47 - Characteristics of Qualitative Research Designs 13:56 - Ethnography 18:07 - Phenomenology 22:28 - Grounded Theory 25:43 - Case Study 28:57 - Discourse Analysis 31:40 - Generic Qualitative Research / Qualitative Description
Views: 26884 Molly Ott
Qualitative and Quantitative research in hindi  | HMI series
 
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For full course:https://goo.gl/J9Fgo7 HMI notes form : https://goo.gl/forms/W81y9DtAJGModoZF3 Topic wise: HMI(human machine interaction):https://goo.gl/bdZVyu 3 level of processing:https://goo.gl/YDyj1K Fundamental principle of interaction:https://goo.gl/xCqzoL Norman Seven stages of action : https://goo.gl/vdrVFC Human Centric Design : https://goo.gl/Pfikhf Goal directed Design : https://goo.gl/yUtifk Qualitative and Quantitative research:https://goo.gl/a3izUE Interview Techniques for Qualitative Research :https://goo.gl/AYQHhF Gestalt Principles : https://goo.gl/Jto36p GUI ( Graphical user interface ) Full concept : https://goo.gl/2oWqgN Advantages and Disadvantages of Graphical System (GUI) : https://goo.gl/HxiSjR Design an KIOSK:https://goo.gl/Z1eizX Design mobile app and portal sum:https://goo.gl/6nF3UK whatsapp: 7038604912
Views: 87850 Last moment tuitions
9 Quantitative data analysis
 
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A video tutorial from the National Union of Students, introducing the basic principles of quantitative data analysis and applying them to National Student Survey data.
Views: 16496 Kate Little
What is Triangulation (Qualitative research) ?
 
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Triangulation is a method used by qualitative researchers to check and establish validity in their studies by analysing a research question from multiple perspectives is to arrive at consistency across data sources or approaches, in fact, such inconsistencies should not be seen as weakening the evidence, but should be viewed as an opportunity to uncover deeper meaning in the data. Reference: http://www.nova.edu/ssss/QR/QR8-4/golafshani.pdf Reference: http://edis.ifas.ufl.edu/fy394 Reference: Patton, M. Q. (2002). Qualitative evaluation and research methods (3rd ed.). Thousand Oaks, CA: Sage Publications, Inc
Views: 106825 B2Bwhiteboard
Types of Experimental Designs (3.3)
 
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Get access to practice questions, written summaries, and homework help on our website! http://wwww.simplelearningpro.com Follow us on Instagram http://www.instagram.com/simplelearningpro Like us on Facebook http://www.facebook.com/simplelearningpro Follow us on Twitter http://www.twitter.com/simplelearningp If you found this video helpful, please subscribe, share it with your friends and give this video a thumbs up! Get access to practice questions, written summaries, and homework help on our website! http://wwww.simplelearningpro.com Follow us on Instagram http://www.instagram.com/simplelearningpro Like us on Facebook http://www.facebook.com/simplelearningpro Follow us on Twitter http://www.twitter.com/simplelearningp If you found this video helpful, please subscribe, share it with your friends and give this video a thumbs up!
Views: 160741 Simple Learning Pro
Fundamentals of Qualitative Research Methods: What is Qualitative Research (Module 1)
 
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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 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 1. Patton M. Qualitative Research and Evaluation Methods, 3rd edition. Sage Publishers; 2002. Curry L, Nembhard I, Bradley E. Qualitative and mixed methods provide unique contributions to outcomes research. Circulation, 2009;119:1442-1452. Crabtree, B. & Miller, W. (1999). Doing qualitative research, 2nd edition. Newbury Park, CA:Sage. Schensul S, Schensul J. and Lecompte M. 2012 Initiating Ethnographic research: A mixed Methods Approach, Altamira press. 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: 221999 YaleUniversity
Grounded Theory
 
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Have you ever wanted to create a theory? Now you can! Let's journey through Grounded Theory and learn how to do it!
Views: 157960 ChrisFlipp
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; *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: 747376 Kent Löfgren
Content Analysis
 
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Let's go on a journey and learn how to perform a content analysis!
Views: 107804 ChrisFlipp
1.  Introduction to Methods of Qualitative Research Narrative Research
 
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https://www.academia.edu/1738897/Methods_of_Qualitative_Research_and_Inquiry
Views: 55471 drjasonjcampbell
Qualitative Data Analysis - Coding & Developing Themes
 
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This is a short practical guide to Qualitative Data Analysis
Views: 131552 James Woodall
Narrative Research
 
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Copy of None-- Created using PowToon -- Free sign up at http://www.powtoon.com/ . Make your own animated videos and animated presentations for free. PowToon is a free tool that allows you to develop cool animated clips and animated presentations for your website, office meeting, sales pitch, nonprofit fundraiser, product launch, video resume, or anything else you could use an animated explainer video. PowToon's animation templates help you create animated presentations and animated explainer videos from scratch. Anyone can produce awesome animations quickly with PowToon, without the cost or hassle other professional animation services require.
Views: 26606 Sherry Cuku
Qualitative Data Analysis
 
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This is Chapter 10 about how to analyze qualitative data
Views: 15947 Qingwen Dong
Developing a Quantitative Research Plan: Choosing a Research Design
 
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http://thedoctoraljourney.com/ Learn how to choose a research design for your quantitative research plan. For more statistics, research and SPSS tools, visit http://thedoctoraljourney.com/.
Views: 94567 The Doctoral Journey
Qualitative vs. Quantitative
 
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Let's go on a journey and look at the basic characteristics of qualitative and quantitative research!
Views: 762672 ChrisFlipp
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/
The analysis of narratives
 
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Examines the use of narratives in speech and in research analysis. Beginning with a look at the range of ways narratives might be analysed such as linguistic, structural and thematic. Attention is then turned to some of the functions of narrative. This was a lecture given to postgraduate (graduate) students at the University of Huddersfield as part of a course on Qualitative Data Analysis. To learn more about social research methods you might be interested in this new, inexpensive, postgraduate, distance learning course: MSc Social Research and Evaluation. The course is delivered entirely via the Internet. http://sre.hud.ac.uk/ Works referred to in the video include: Bury, M (2001) “Illness narratives: Fact or Fiction” Sociology of Health and Illness 23: 263-85 Cortazzi, M (1993) Narrative Analysis. London: Falmer Press. Denzin, N.K. (1989) Interpretive biography. Newbury Park, Calif., London: Sage. Labov, W. (1972) 'The transformation of experience in narrative syntax', in W. Labov (ed), Language in the inner city: Studies in the Black English vernacular. Philadelphia: University of Pennsylvania Press. pp. 354-396. Lieblich, A., Tuval-Mashiach, R. and Zilber, T. (1998) Narrative Research: Reading, Analysis and Interpretation. London: Sage. Mishler, E.G. (1986) Research Interviewing: Context and Narrative, Cambridge Mass.: Havard University Press Rhodes, C., and Brown, A.D. (2005) “Narrative, Organizations and Research”, International Journal of Management Research, 5: 167-88. Riessman, C.K. (1993) Narrative Analysis. Newbury Park, CA, London: Sage. Credits: Sounds and music: 'Fifth Avenue Stroll' from iLife Sound Effects, http://images.apple.com/legal/sla/docs/ilife09.pdf Image: Freizeitanlage Kräwinklerbrücke, Kräwinklerbrücke in Remscheid by Frank Vincentz, Wikimedia Commons, licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
Views: 36027 Graham R Gibbs
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 types of sampling types of sampling pdf probability sampling types of sampling in hindi random sampling cluster sampling non probability sampling systematic sampling
Views: 366695 Examrace
Qualitative Data Collection
 
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Table of Contents: 00:00 - Qualitative Data Collection & Sampling Strategies 00:36 - How might you collect data for a qualitative study? 03:10 - Qualitative Interviews 07:34 - Tips for constructing interview questions 09:29 - Constructing good qualitative interview questions 15:22 - Tips for conducting effective interviews 19:42 - Focus groups 24:32 - Observation 28:01 - Documents 30:17 - Purposive sampling in qualitative research
Views: 21863 Molly Ott
Sociology Research Methods: Crash Course Sociology #4
 
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Today we’re talking about how we actually DO sociology. Nicole explains the research method: form a question and a hypothesis, collect data, and analyze that data to contribute to our theories about society. Crash Course is made with Adobe Creative Cloud. Get a free trial here: https://www.adobe.com/creativecloud.html *** The Dress via Wired: https://www.wired.com/2015/02/science-one-agrees-color-dress/ Original: http://swiked.tumblr.com/post/112073818575/guys-please-help-me-is-this-dress-white-and *** 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, Les Aker, Robert Kunz, William McGraw, Jeffrey Thompson, Jason A Saslow, Rizwan Kassim, Eric Prestemon, Malcolm Callis, Steve Marshall, Advait Shinde, Rachel Bright, Kyle Anderson, Ian Dundore, Tim Curwick, Ken Penttinen, Caleb Weeks, Kathrin Janßen, Nathan Taylor, Yana Leonor, Andrei Krishkevich, Brian Thomas Gossett, Chris Peters, Kathy & Tim Philip, Mayumi Maeda, Eric Kitchen, SR Foxley, Justin Zingsheim, Andrea Bareis, Moritz Schmidt, Bader AlGhamdi, Jessica Wode, Daniel Baulig, Jirat -- 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: 390052 CrashCourse
Fundamentals of Qualitative Research Methods: Scientific Rigor (Module 6)
 
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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 6. Mays N, Pope C. Qualitative research: rigour and qualitative research. British Medical Journal 1995; 311:109-112. Barbour R. Checklists for improving rigour in qualitative research: a case for the tail wagging the dog? British Medical Journal 2001; 322:1115-1117. 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: 35622 YaleUniversity
Introduction to Statistics..What are they? And, How Do I Know Which One to Choose?
 
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This tutorial provides an overview of statistical analyses in the social sciences. It distinguishes between descriptive and inferential statistics, discusses factors for choosing an analysis procedure, and identifies the difference between parametric and nonparametric procedures.
Views: 236303 The Doctoral Journey
Longitudinal Analysis
 
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In longitudinal studies, subjects are followed for a period of time and outcomes along with other characteristics for each subject are measured at multiple pre-specified time points. Unlike data collected from cross-sectional studies where outcomes and other characteristics are measured at only one time point for each subject, data collected from longitudinal studies allow investigators to study changes in response over time. However, designing and analyzing longitudinal studies require careful considerations. Two major issues that arise in longitudinal studies are the correlation between measurements from the same subject and potential missing data due to loss of follow-up. In this talk, we will introduce common statistical analysis methods that account for the correlation structure of longitudinal data. We will also introduce missing data mechanism and approaches to address this important issue.
Views: 11055 BiostatisticsMCW

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