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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: 145113 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: 46368 Bharatendra Rai
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: 1919 Nick Hopwood
Psychological Research - Crash Course Psychology #2
 
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You can directly support Crash Course at http://www.subbable.com/crashcourse Subscribe for as little as $0 to keep up with everything we're doing. Also, if you can afford to pay a little every month, it really helps us to continue producing great content. So how do we apply the scientific method to psychological research? Lots of ways, but today Hank talks about case studies, naturalistic observation, surveys and interviews, and experimentation. Also he covers different kinds of bias in experimentation and how research practices help us avoid them. -- Table of Contents The Scientific Method 2:06 Case Studies 3:05 Naturalistic Observation 3:48 Surveys and Interviews 4:15 Experimentation 6:35 Proper Research Practices 8:40 -- 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 CrashCourse on Subbable: http://subbable.com/crashcourse
Views: 3026804 CrashCourse
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: 166307 Khan Academy
Cohort, Case-Control, Meta-Analysis, Cross-sectional Study Designs & Definition
 
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http://www.stomponstep1.com/cohort-case-control-meta-analysis-cross-sectional-study-designs/ Based on the types of bias that are inherent in some study designs we can rank different study designs based on their validity. The types of research studies at the top of the list have the highest validity while those at the bottom have lower validity. In most cases if 2 studies on the same topic come to different conclusions, you assume the trial of the more valid type is correct. However, this is not always the case. Any study design can have bias. A very well designed and executed cohort study can yield more valid results than a clinical trial with clear deficiencies. • Meta-analysis of multiple Randomized Trials (Highest Validity) • Randomized Trial • Prospective Cohort Studies • Case Control Studies or Retrospective Cohort • Case Series (Lowest Validity) Meta-analysis is the process of taking results from multiple different studies and combining them to reach a single conclusion. Doing this is sort of like having one huge study with a very large sample size and therefore meta-analysis has higher power than individual studies. Clinical trials are the gold standard of research for therapeutic and preventative interventions. The researchers have a high level of control over most factors. This allows for randomization and blinding which aren't possible in many other study types. Participant's groups are assigned by the researcher in clinical trials while in observational studies "natural conditions" (personal preference, genetics, social determinants, environment, lifestyle ...) assign the group. As we will see later, the incidence in different groups is compared using Relative Risk (RR). Cohort Studies are studies where you first determine whether or not a person has had an exposure and then you monitor the occurrence of health outcomes overtime. It is the observational study design with the highest validity. Cohort is just a fancy name for a group, and this should help you remember this study design. You start with a group of people (some of whom happen to have an exposure and some who don't). Then you follow this group for a certain amount of time and monitor how often certain diseases or health outcomes arise. It is easier to conceptually understand cohort studies that are prospective. However, there are retrospective cohort studies also. In this scenario you identify a group of people in the past. You then first identify whether or not these people had the particular exposure at that point in time and determine whether or not they ended up getting the health outcomes later on. As we will see later, the incidence in different groups in a cohort study is compared using Relative Risk (RR). Case-Control Studies are retrospective and observational. You first identify people who have the health outcome of interest. Then you carefully select a group of controls that are very similar to your diseased population except they don't have that particular disease. Then you try to determine whether or not the participants from each group had a particular exposure in the past. I remember this by thinking that in a case control study you start off knowing whether a person is diseased (a case) or not diseased (a control). There isn't a huge difference between retrospective cohort and case-control. You are basically doing the same steps but in a slightly different order. However, the two study designs are used in different settings. As we will see later, the incidence in different groups in a case-control study is compared using Odds Ratio (OR). A Case-Series is a small collection of individual cases. It is an observational study with a very small sample size and no control group. Basically you are just reviewing the medical records for a few people with a particular exposure or disease. A study like this is good for very rare exposures or diseases. Obviously the small sample size and lack of a control group limits the validity of any conclusions that are made, but in certain situations this is the best evidence that is available. Cross Sectional Studies are different from the others we have discussed. While the other studies measure the incidence of a particular health outcome over time, a cross-sectional study measures Prevalence. In this observational study the prevalence of the exposure and the health outcome are measured at the same time. You are basically trying to figure out how many people in the population have the disease and how many people have the exposure at one point in time. It is hard to determine an association between the exposure and disease just from this information, but you can still learn things from these studies. If the exposure and disease are both common in a particular population it may be worth investing more resources to do a different type of study to determine whether or not there is a causal relationship.
Views: 110965 Stomp On Step 1
Epidemiological Studies - made easy!
 
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This video gives a simple overview of the most common types of epidemiological studies, their advantages and disadvantages. These include ecological, case-series, case control, cohort and interventional studies. It also looks at systematic reviews and meta-analysis. This video was created by Ranil Appuhamy Voiceover - James Clark -------------------------------------------------------------------------------------------------------- Disclaimer: These videos are provided for educational purposes only. Users should not rely solely on the information contained within these videos and is not intended to be a substitute for advice from other relevant sources. The author/s do not warrant or represent that the information contained in the videos are accurate, current or complete and do not accept any legal liability or responsibility for any loss, damages, costs or expenses incurred by the use of, or reliance on, or interpretation of, the information contained in the videos.
Experimental Design and Observational Analysis
 
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Part of the Data Science in Real Life Coursera class as part of the Executive Data Science Specialization.
Views: 607 Brian Caffo
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: 664727 Kent Löfgren
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: 43109 Khan Academy
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: 423 Keith Donohue
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: 214928 The Doctoral Journey
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.
Views: 676332 Dr Nic's Maths and Stats
Performing a t-test in Excel on experimental data
 
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A tutorial demonstrating how to carry out a T-test in microsoft Excel using the built-in Data analysis tool pack This is part of a series of tutorials designed to help research scientists in the use of certain software applications commonly used in scientific laboratory work. You can find the entire set of tutorial videos here: http://ehealth.kcl.ac.uk/sites/physiology/ The screencast videos have been made by the author (Dr James Clark, King's College London) in response to common questions raised by students on BSc and MSc courses and are recorded using Camtasia Studio. The content is targeted at students of all levels of undergraduate and postgraduate education as well as professional research scientists. If you wish to link to this video on another web site please make sure you credit the author and provide a link to the blog site (shown above) ©2013 James Clark, king's College London. All rights reserved.
Views: 147118 Dory Video
RESEARCH DESIGN
 
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Research Design The most important step after defining the research problem is preparing the design of the research project, which is popularly known as the ‘research design’. A research design helps to decide upon issues like what, when, where, how much, by what means etc. with regard to an enquiry or a research study. A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research purpose with economy in procedure. In fact, research design is the conceptual structure within which research is conducted; it constitutes the blueprint for the collection, measurement and analysis of data. Thus, research design provides an outline of what the researcher is going to do in terms of framing the hypothesis, its operational implications and the final data analysis. Specifically, the research design highlights decisions which include: (i) the nature of the study (ii) the purpose of the study (iii) the location where the study would be conducted (iv) the nature of data required (v) from where the required data can be collected (vi) what time period the study would cover (vii) the type of sample design that would be used (viii) the techniques of data collection that would be used (ix) the methods of data analysis that would be adopted and (x) the manner in which the report would be prepared. In view of the stated research design decisions, the overall research design may be divided into the following: (a) The sampling design that deals with the method of selecting items to be observed for the selected study; (b) the observational design that relates to the conditions under which the observations are to be made; (c) the statistical design that concerns with the question of how many items are to be observed, and how the information and data gathered are to be analysed; and (d) the operational design that deals with the techniques by which the procedures specified in the sampling, statistical and observational designs can be carried out.
Views: 1219 aucommerce Scholar
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: 2523 The Audiopedia
3.7 Research Strategy: Case Study
 
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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
Views: 58461 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: 9003 Ranywayz Random
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: 12930 Kate Little
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: 687425 ChrisFlipp
Narrative Research Design
 
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-- Created using PowToon -- Free sign up at http://www.powtoon.com/join -- Create 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: 7831 Lauren Watanabe
Grounded Theory - Core Elements. Part 1
 
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In this two part video, Graham R Gibbs introduces the idea of developing grounded theory and discusses some of the core elements of the approach to qualitative data analysis. See: Gibbs, Graham Robert. (2012) 'Grounded theory, coding and computer-assisted analysis'. In S. Becker, A. Bryman & H. Ferguson (eds.), Understanding Research for Social Policy and Social Work: Themes, Methods and Approaches. 2nd edn. Bristol: Policy Press. pp. 337-343. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) http://creativecommons.org/licenses/by-nc-sa/4.0/
Views: 105856 Graham R Gibbs
Quantitative data analysis in psychology tutorial
 
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Narrated slideshow tutorial about quantitative data analysis in psychology. Covers levels of data, measures of central tendency, measures of dispersion, graphs and probability. Further reading: Textbook pages 103-109 (orange Hodder book) http://www.smartpsych.co.uk/wp-content/uploads/2012/02/psych_methods1.pdf
Views: 8023 missowen1
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: 138265 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/
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: 21521 Sherry Cuku
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: 189671 YaleUniversity
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: 36206 Diana Lizarraga
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: 265459 Examrace
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
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Topic 11 Qualitative Data Analysis
 
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Process involves in analysing qualitative data. Thanks to SMMTC & Mr. Faharul from Aspati Sdn Bhd for the production.
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Correlational Research
 
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Psychologists often study the relationship between two variables. In this PSYCHademia episode I cover the correlational method. For students and teachers of AP Psychology, this episode aligns with Unit 2 Research Methods.
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Introduction to Longitudinal Data Analysis
 
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Paper: Advanced Data Analytic Techniques Module: Introduction to Longitudinal Data Analysis Content Writer: Souvik Bandyopadhyay
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What Are The Methods Of Data Analysis In Research?
 
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Quantitative research now available sage methods. You also need to consider data interpretation and analysis. Methodology chapter of your dissertation should include discussions about the methods data analysis. Develop a research proposal methodology data analysis bcpsresearch methods and procedures used by qualitative. Approach to de synthesizing data, informational, and or factual elements answer research questions. According to shamoo and resnik (2003) various analytic procedures provide a way of drawing inductive inferences from data distinguishing the signal (the 14 jul 2015 analysis introduction. Each method has their own techniques. Collecting data is only one part of the story. It's much more difficult to define the research problem; Develop and implement a sampling plan; Conceptualize, operationalize test your measures; And develop design structure. By the time you get to analysis of your data, most really difficult work has been done. Introduction to research methods and data analysis learnonline. Data analysis has two prominent methods qualitative research and quantitative. The methods for aims 2 and 4 can be described as qualitative research, whereas the 3 5 are quantitative research. Hypothesis tests are used in everything from science and research to business economic. You have to explain in a brief manner how you are going analyze the primary data will collect employing methods explained this chapter. In qualitative research, you are either exploring the application of a theory or model in different context hoping for to emerge from data. Sampling strategies, data analysis techniques and research ethics of. All are varieties of data analysis. If you have done this work well, the in table 2, method for aim 1 was a literature review, which we already discussed. Most important methods for statistical data analysisanalysing qualitative research. Methods of data collection and analysis the open university. Ut faculties concepts of data analysissome tips for analysis. Data analysis, interpretation and presentation uio. Madhu bala, indira gandhi national open university. What i will not do to teach every bit and pieces of statistical analysisdata analysis the concept. Data analysis techniques & methods video lesson transcript data study academy. Method of data analysis is the process systematically applying statistical and or logical techniques to describe illustrate, condense recap, evaluate. It's much more difficult to define the research problem, develop and implement a sampling plan, design structure, predictive analytics focuses on application of statistical models for forecasting or classification, while text applies statistical, linguistic, structural techniques extract classify information from textual sources, species unstructured data. Because the proposed study contains both qualitative and quantitative components, an overview of sampling strategies, data analysis techniques research ethics when doing dissertation at undergra
"Design and Statistical Considerations for Clinical Trials"
 
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CRDEB January Symposium: WVCTSI Clinical Research Design Epidemiology & Biostatistics Program
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Narrative Research Design
 
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Recorded with http://screencast-o-matic.com
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How to Know You Are Coding Correctly: Qualitative Research Methods
 
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Coding your qualitative data, whether that is interview transcripts, surveys, video, or photographs, is a subjective process. So how can you know when you are doing it well? We give you some basic tips.
What Is Qualitative Data Analysis In Research?
 
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The analysis of qualitative research involves aiming to uncover and / or understand the big picture - by using the data to describe the phenomenon and what this means. Both qualitative and quantitative analysis involves labelling and coding all of the data in order that similarities and differences can be recognised. Research question is linked to methods chosen and type of analysis rationale you apply. Tests hypotheses, uses data to support conclusion& individual responses. What is qualitative data analysis software and how does it support interpretation. The analysis of qualitative research involves aiming to uncover and or understand the big picture by using data describe phenomenon what this means. Often, the output from qualitative research will be in form of words. Both qualitative and quantitative analysis involves labelling coding all of the data in order that similarities methods used to analyze those. Qualitative data analysis research methodology. Pattern or thematic analyses) as the primary basis for organizing and reporting this resource pack is designed researchers working in health social care who have mind, already embarked upon, a piece of qualitative research. Qualitative methods, using narrative and observation rather than numerical data, are increasingly being used in health care settings where they seen to qualitative research methods & methodology overview at atlasti atlas. Analyze qualitative data pell institutequalitative analysis nihr rds yh. Qda is usually based on an interpretative philosophy 6 mar 2012 qualitative data analysis (qda) the range ofprocesses and procedures whereby we move from thequalitative that have been collected into some formof explanation, understanding or interpretation of thepeople situations are investigating. According to easterby smith, thorpe and jackson, in their book qualitative data analysis software supports your research approach offers many ways analyze material. Data analysis in qualitative research data a brief guide to using nvivo. Qualitative data analysis (qda) uwc. The focus on text qualitative data rather than numbers is the most important feature of analysis. Try maxqda and get to know one qualitative data analysis interpretationan attempt by the researcher summarize collected dataattempt find meaning. All codes need to be assigned meaningful titles. The idea is to analysing qualitative research data. Comparison of qualitative and quantitative research atlas. Not guided by universal rules; Is a very fluid process that is highly to analyse qualitative data, the researcher seeks meaning from all of data available. Ti is a powerful workbench for qualitative data analysis of textual graphical, video systems involving language. Faq 35 what are some good approaches to analysing qualitative analyzing data with or without software. Data analysis consists of 23 nov 2005 qualitative data (qda) is the range processes and procedures whereby we move from that have been collected into some for
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.
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