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The Data Analysis Process
 
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The process of doing statistical analysis follows a clearly defined sequence of steps whether the analysis is being done in a formal setting like a medical lab or informally like you would find in a corporate environment. This lecture gives a brief overview of the process.
Views: 50036 White Crane Education
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: 157566 YaleUniversity
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: 20603 NurLiyana Isa
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: 702348 Kent Löfgren
data analysis, quality of research
 
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Description
Views: 58 rosemesh
Lecture 4 Data preparation in research methodology
 
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It covers the process to prepare the data collected for data analysis in Research methodology
Views: 5361 Educate Motivate
Data Collection & Analysis
 
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Impact evaluations need to go beyond assessing the size of the effects (i.e., the average impact) to identify for whom and in what ways a programme or policy has been successful. This video provides an overview of the issues involved in choosing and using data collection and analysis methods for impact evaluations
Views: 57725 UNICEF Innocenti
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: 69855 Last moment tuitions
Data Analysis in Qualitative Research
 
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Description
Views: 80 dennissale
Analysis of Empirical research Data
 
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The Complete data Analysis of an Empirical research Data starting from questionnaire to final interpretation of the analysed data. very useful for writing Empirical research Articles. I have used Factor analysis and Amos to interpreted the mediation effect of variables.
Views: 856 My Easy Statistics
Choosing which statistical test to use - statistics help.
 
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Seven different statistical tests and a process by which you can decide which to use. The tests are: Test for a mean, test for a proportion, difference of proportions, difference of two means - independent samples, difference of two means - paired, chi-squared test for independence and regression. This video draws together videos about Helen, her brother, Luke and the choconutties. There is a sequel to give more practice choosing and illustrations of the different types of test with hypotheses.
Views: 728854 Dr Nic's Maths and Stats
Types of Data: Nominal, Ordinal, Interval/Ratio - Statistics Help
 
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The kind of graph and analysis we can do with specific data is related to the type of data it is. In this video we explain the different levels of data, with examples. Subtitles in English and Spanish.
Views: 846911 Dr Nic's Maths and Stats
Research Project: Data Analysis in SPSS
 
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Research Project: Data Analysis in SPSS
Research Metholdology: Content Analysis
 
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This video is about Research Metholdology: Content Analysis
Views: 17476 Jessica Kager
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: 475 Keith Donohue
Analysis of the data - How to write a research dissertation (ebook video)
 
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http://www.etextbooks.ac.uk/dissertation/chapter-9-dissertation-analysis-of-the-data/ Once the research results have been carefully gathered and recorded using some filing system, the data needs to be able to be explained and interpreted in order to attempt to answer the initial research question. The type of analysis and the means of presentation need to be considered at an early stage – even before the results themselves have been obtained – in order to be certain that the research method(s) chosen can actually be used to generate sensible results. This chapter in the book outlines some key steps to ensure that your data analysis is appropriate for your needs. The companion website shares the experiences of some active researchers in how they approach data analysis in their own research areas.
Eye Tracking Research - Visual Analysis of Eye Tracking Data
 
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Kuno Kurzhals, PhD student at the University of Stuttgart and research assistant associated with the SFB-TRR 161, talking about his scientific activities in Visual Computing, particularly in the Visual Analysis of Eye Tracking Data.
Views: 1250 SFB-TRR 161
Factor Analysis - Factor Loading, Factor Scoring & Factor Rotation (Research & Statistics)
 
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Dr. Manishika Jain in this lecture explains factor analysis. Introduction to Factor Analysis: Factor Loading, Factor Scoring & Factor Rotation. NET Psychology postal course - https://www.examrace.com/CBSE-UGC-NET/CBSE-UGC-NET-FlexiPrep-Program/Postal-Courses/Examrace-CBSE-UGC-NET-Psychology-Series.htm NET Psychology MCQs - https://www.doorsteptutor.com/Exams/UGC/Psychology/ IAS Psychology - https://www.examrace.com/IAS/IAS-FlexiPrep-Program/Postal-Courses/Examrace-IAS-Psychology-Series.htm IAS Psychology test series - https://www.doorsteptutor.com/Exams/IAS/Mains/Optional/Psychology/ Steps in Research Proposal @0:24 Research Topic @0:43 Review of Literature @0:56 Rationale and Need for the Study @1:18 Definition of Terms @1:24 Assumptions @3:03 Method, Sample and Tools @4:06 Probability Sampling @4:23 Non - Probability Sampling @4:34 Significance of Study @5:13 Technique for Data Analysis @5:18 Bibliography @5:42 Budget @6:28 Chapterisation @6:39 #Expenditure #Tabulate #Significance #Assumption #Literature #Rationale #Constitutive #Phenomena #Elucidate #Literature #Manishika #Examrace Factor Analysis and PCA Reduce large number of variables into fewer number of factors Co-variation is due to latent variable that exert casual influence on observed variables Communalities – each variable’s variance that can be explained by factors Types of Factoring • PCA – maximum variance for 1st factor; removes that and uses maximum for 2nd factor and so on… • Common Factor Analysis – Same as factor analysis (only common variance – used in CFA) • Image Factoring – correlation matrix; uses OLS regression matrix • Maximum Likelihood Method – on correlation matrix • Alpha Factoring • Weight Square Estimate communalities - each variable’s variance that can be explained by factor. See factors are retained Factor rotation - Procedure in which the eigenvectors (factors) are rotated in an attempt to achieve simple structure. Factor loading - Relation of each variable to the underlying factor. Output of a simple factor analysis looking at indicators of wealth, with just six variables and two resulting factors 6 variables: Income, education, occupation, house value, public parks and crimes 2 factors: individual socioeconomic status and neighborhood socioeconomic status Factor Score – if value of variables are given then factor values can be predicted Interpretation
Views: 6286 Examrace
Writing a Research Proposal - Data Analysis
 
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This video was recorded for a third year Midwifery module. Featuring University of Nottingham Division of Midwifery's Zoey Spendlove, filmed by the Health E-Learning and Media Team (HELM). This resource was created for University of Nottingham Students and its intended use is as a teaching aid that forms a part of the Midwifery BSc. This video is strictly for information purposes only.
Action Research Data Analysis
 
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Examples from YATST Action Research work.
Views: 1919 Susan Hennessey
Media Research : Statistics or Data Analysis and Interpretation
 
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This Lecture talks about Statistics or Data Analysis and Interpretation
Views: 1842 Cec Ugc
Coding Part 1: Alan Bryman's 4 Stages of qualitative analysis
 
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An overview of the process of qualitative data analysis based on Alan Bryman's four stages of analysis. Reference Bryman, A (2001) Social Research Methods, Oxford: Oxford University Press 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: 197736 Graham R Gibbs
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: 730479 ChrisFlipp
Communication Research Methods - Discourse Analysis
 
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Introduction to Discourse Analysis Communication Research Methods Arkansas State University
Views: 9843 Dan's Academy
What Is The Unit Of Analysis In Research? - Nerd-Out Wednesdays
 
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The unit of analysis is the phenomenon or entity being studied. It is generally the thing that you are sampling in a quantitative study. It varies depending on what you are interested in. The unit of analysis may differ from the unit of observation, as you use the unit of analysis to explain the relationship set the theoretical level in the unit of observation occurs when you actually sample data. This idea of understanding the unit of observation versus the unit of analysis is important for quantitative research. The unit of analysis is important for both quantitative research and qualitative research, but it is often discussed in quantitative research. It differs from the level of analysis. The level of analysis generally pertains to the level at which you are analyzing a particular mechanism for a unit of analysis. For example, you might use population ecology to study the behavior of firms. Population ecology occurs at the population level (ie. aggregate) of firms but you are really studying firm behavior. It is important to get the right unit of analysis so that the theories you choose hold and are consistent when you analyze your data. For example, if you analyze transaction costs but then you look at firm behavior, you’re likely going to capture something other than transaction costs. Generally, you want to have the unit of analysis at the same level of analysis of your theory. You can also focus on a unit of analysis that cuts across levels of analysis. This is called multi-level theorizing, but it generally is not recommended because unless it is well done, it makes your paper seem very shallow. Most people end up just gathering theories from many different areas to explain the unit of analysis. The reason why you want to ensure that the unit of analysis in the level of analysis are similar is because you are unlikely to explain the phenomenon fully if you choose different levels of analysis, and rule out other possible explanations. Check out: What Is A Level Of Analysis? Nerd-out Wednesday https://youtu.be/MIlQIfrXmN8 What Is A Confirmation Bias? Confirmation Biases - Nerd-Out Wednesday https://youtu.be/72PnUjoSNKY How To Write A Research Question - Nerd-Out Wednesdays https://youtu.be/TQF7H0sEDcA How Do You Analyze Data In Research When Nothing Works? - Nerd-Out Wednesday https://youtu.be/AqRFsv7umhk What is reliability and validity? https://youtu.be/5lmUFIxfuAs **************** David Maslach is a research professor of entrepreneurship, innovation, and business strategy, I discuss topics, such as behavioral science, strategy, innovation, and entrepreneurship, and apply these to my new peer proofreading and editing platform. Topics include the sharing economy, altruism, investing in technology, starting a business, and bounded rationality. My favorite videos pertain to incentives, goal setting, and learning from failure to drive behaviors such as weight loss, stopping telemarketers, creating novel technologies, and creating new movements. https://r3ciprocity.com: Peer proofreading and editing platform A new platform where you can earn credits by editing other people's documents. Use these credits to have your own work edited. If you do a good enough job, you can convert these credits to money. The goal of the platform is to get people to 'pay it forward' and help other people out by creating incentives for people to give back. Check out https://www.r3ciprocity.com Please subscribe to the Youtube channel: https://www.youtube.com/channel/UC5spxk7bNDMGPSHjW_8ndZA
Views: 906 r3ciprocity Team
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: 360542 CrashCourse
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: 332205 Examrace
Using data analysis on Azure for cancer research
 
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The Hamburg-Eppendorf university hospital wants to use DNA analysis to gain a better understanding of the immune system in cancer cases. Every DNA sequencing process generates 10 billion datasets which have to be handled quickly, reliably and safely. Doing so requires many process steps, tools and adjustments. An integrated solution on Azure now extends, enhances, simplifies and accelerates the process.
Confirmatory Factor Analysis - Part 1 (Psychology, Statistics, Research Methods)
 
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In intelligence research, personality research and other research fields of psychology, factor analytic models are used to structurize the variables' jungle. For example: To simplify the variable structure of a personality questionnaire several questions (items), that are supposed to measure the same construct are grouped to one (latent) factor (e.g. extraversion). But does this group of items really measure extraversion? Maybe some of the items "load" on a different factor. And Maybe other aspects of the model have flaws as well... How well a factor model fits the data can be examined by a confirmatory factor analysis. Keywords: Confirmatory Factor Analysis - Factor Analysis - Psychology - Statistics - Research Methods - Personality Psychology - Extraversion - Conscientiousness - Openness - Neuroticism - Agreeableness - Five Factor Model - Big Five - Intelligence - Carroll
SOCIOLOGY OPTIONAL | UPSC/STATE PCS/ UPPSC | LECTURE 6 | RESEARCH METHODS AND ANALYSIS
 
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Data Analysis For Quantitative Research
 
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Data Analysis For #Quantitative Research: #Qualitative #DataAnalysis is an iterative process of individual and group level review and #interpretation of narrative data. Purpose of Data Analysis Section: 1. Convince readers of your knowledge of the data and how you will use it. 2. Convince readers of your capability as a #researcher. 3. Convince readers of the analysis and results. How to write it? 1. Provide a Level-2 Heading. 2. Provide a roadmap of your data and #analysis. 3. Provide the data you have and what you do with it. Let's quickly talk about T-Test and Anova for Now A) Independent Sample T-Tests 1. State what data you are comparing. 2. Convey experimental group and control group. 3. Mention both groups at beginning and end of study. B) Dependent Sample T-Tests. 1. State what data you are comparing. 2. Convey that you are comparing at different times. 3. Mention the testing times for Comparision. C) Anova 1. State the type of data you have. 2. Describe the results or effects of the comparison. 3. Describe the interaction effects. D) #Hypothesis 1. Restate your hypothesis or predictions Contact Information INDIA: +91-8754446690 UK: +44-1143520021 Email: [email protected] Visit: http://www.statswork.com/
Views: 42 Stats Work
BMI: Research & data analysis
 
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BMI Research CEO Gareth Pearson looks at the trends in research and data analysis in the retail industry
Views: 462 Vi id
Primary & secondary data, meta analysis - Research Methods (7.24) Psychology AQA paper 2
 
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7.24 Primary & secondary data, meta analysis - Research Methods - AQA spec Alevel Psychology, p2 in this video definitions and evaluations of Primary Data, Secondary Data, Meta-analysis If you are a student of A-level AQA psychology I have made these videos for you! They are a full set of videos for every part of the AQA specification from 2015 onwards. They are to be used in preparation for a flipped classroom, revision, self teaching or for anyone who is just interested in psychology in general. I have attempted to make them as simple, focused and accurate as possible, 6 key points for each sub topic, (to match the 6 A01/ knowledge points in the biggest essay you will get, a 16 marker) 2 pieces of evaluative research per sub-topic (with ways to expand these to gain the 10 A03/ Evaluation points available) The channel is an on-going project in my spare time, I'm a full time Psychology A-level teacher teaching over 125 students over A1 and A2. That being said, I'm not perfect, if you spot a mistake or omission, please let me know so I can adapt the next video!
Views: 795 Psych Boost
Data analysis using SPSS | Research Methods | Statisician services on Research
 
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This tutorial is about research metholodoly and data analysis using spss. For more about our services follow the link https://rigorousstatistics.wixsite.com/statistician/services
Views: 13 Nqobile Muleya
QDA Miner - Qualitative Data Analysis Software for Qualitative Research
 
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This video is a short introduction to QDA Miner, a qualitative data analysis software for mixed methods research. For more demos and tutorials visit: http://provalisresearch.com/resources/tutorials/