This webinar provides an overview of basic quantitative analysis, including the types of variables and statistical tests commonly used by Student Affairs professionals. Specifically discussed are the basics of Chi-squared tests, t-tests, and ANOVAs, including how to read an SPSS output for each of these tests.
Views: 18915 CSSLOhioStateU
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: 21364 NurLiyana Isa
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: 5009 Ranywayz Random
www.pinnacleadvisory.com --- Pinnacle Advisory Group's Quantitative Analyst Sauro Locatelli explains what he does and how it aids the investment process. This is the fifth presentation from our February 25 Inside the Investment Committee event. www.pinnacleadvisory.com
Views: 108984 Pinnacle Advisory Group
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
In this video Dr. Ziene Mottiar, DIT, discusses issues around analyzing data and writing the analysing chapter. The difference between Findings and Analysis chapters is also discussed. This video is useful for anyone who is writing a dissertation or thesis.
Views: 66779 ZieneMottiar
In this lecture, I provide a very basic introduction to quantitative data analysis and statistics. We begin by defining what "data" is, what a dataset looks like, and software tools for analyzing data.
Views: 3913 David Russell
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: 158979 YaleUniversity
Data falls into several categories. Each type has some pros and cons, and is best suited for specific needs. Learn more in this short video from our Data Collection DVD available at http://www.velaction.com/data-collection-lean-training-on-dvd/.
Views: 146328 VelactionVideos
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: 58152 UNICEF Innocenti
In this lecture, Dr Rob Johns explores using quantitative, rather than qualitative, data when carrying out political analysis. This lecture is taken from our module on 'Political Analysis' (GV200) which is compulsory for 2nd year students in: BA Politics, BA Economics and Government, BA Politics and International Relations, BA Democratic Politics and BA European Politics. To find out more about studying politics at Essex go to: http://www.essex.ac.uk/government/
Views: 6790 University of Essex
This session will provide information regarding descriptive statistics that are often used when reviewing assessment data. We will cover the statistics available in the Baseline reporting site and we will use example situations to identify which statistics should be used to answer the questions being asked. We will also provide an overview regarding levels of measurement that can help determine what types of statistics you are able to run on your data. - See more at: http://www2.campuslabs.com/support/training/basic-statistics-quantitative-analysis-i-5/#sthash.FDO5HA6i.dpuf
Views: 35145 Campus Labs
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: 227530 The Doctoral Journey
This is a short practical guide to Qualitative Data Analysis
Views: 115428 James Woodall
Basic introduction to correlation - how to interpret correlation coefficient, and how to chose the right type of correlation measure for your situation. 0:00 Introduction to bivariate correlation 2:20 Why does SPSS provide more than one measure for correlation? 3:26 Example 1: Pearson correlation 7:54 Example 2: Spearman (rhp), Kendall's tau-b 15:26 Example 3: correlation matrix I could make this video real quick and just show you Pearson's correlation coefficient, which is commonly taught in a introductory stats course. However, the Pearson's correlation IS NOT always applicable as it depends on whether your data satisfies certain conditions. So to do correlation analysis, it's better I bring together all the types of measures of correlation given in SPSS in one presentation. Watch correlation and regression: https://youtu.be/tDxeR6JT6nM ------------------------- Correlation of 2 rodinal variables, non monotonic This question has been asked a few times, so I will make a video on it. But to answer your question, monotonic means in one direction. I suggest you plot the 2 variables and you'll see whether or not there is a monotonic relationship there. If there is a little non-monotonic relationship then Spearman is still fine. Remember we are measuring the TENDENCY for the 2 variables to move up-up/down-down/up-down together. If you have strong non-monotonic shape in the plot ie. a curve then you could abandon correlation and do a chi-square test of association - this is the "correlation" for qualitative variables. And since your 2 variables are ordinal, they are qualitative. Good luck
Views: 507908 Phil Chan
Quantitative Data vs Qualitative Data Additional Information on Qualitative vs Quantitative Data http://www.moomoomath.com/qualitative-and-quantitative-data.html Data can be divided into two groups called quantitative and qualitative data Quantitative data is numerical Qualitative Data id descriptive data Let’s look at examples of both Examples of quantitative data would be The number of pets, time of day, the temperature outside Quantitative data can be graphed If you count or measure, you are collecting quantitative data There are two types of quantitative data, discrete and continuous Discrete data is usually data you can count and continuous data is usually data you measure. I have a separate video on these two types of data. Qualitative is descriptive or observations and uses words For example, the color of a house, smell of a sock, texture of a shirt Quantitative or Qualitative Consider a cat Quantitative Data would be the cat has 4 legs and weighs 10 pounds Qualitative data would be the cat is yellow, and has soft fur A bookshelf Quantitative would be you have 50 books and is 150 centimeters tall. Qualitative data would be it is multi-color and has a smooth texture You may also enjoy.. Qualitative and Quantitative Data https://www.youtube.com/watch?v=2X-QSU6-hPU Quantitative Qualitative Song https://www.youtube.com/watch?v=-S2EiPD4-W0 -~-~~-~~~-~~-~- Please watch: "Study Skills Teacher's Secret Guide to your Best Grades" https://www.youtube.com/watch?v=f3bsg8gaSbw -~-~~-~~~-~~-~-
Views: 144185 MooMoo Math and Science
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: 71524 Last moment tuitions
In this video tutorial, you will get to learn the difference between qualitative and quantitative research, along with the methods and suitable examples. You can further study this topic on our official website:- https://keydifferences.com/difference-between-qualitative-and-quantitative-research.html In keydifferences.com, you can find the substantial differences between two topics.
Views: 125780 Key Differences
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: 705825 Kent Löfgren
This Video Give The Basic Concept of Difference Between Qualitative And Quantitative Data (Urdu / Hindi) ? ZPZ Education Channel Link: www.youtube.com/channel/UCwFzeQDf9cGm_ZeTXV_t5SA
Views: 4565 ZPZ Education
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: 8307 missowen1
Completing data analysis on open-ended questions using Excel. For analyzing multiple responses to an open-ended question see Part 2: https://youtu.be/J_whxIVjNiY Note: Selecting "HD" in the video settings (click on the "gear" icon) makes it easier to view the data entries
Views: 161923 Jacqueline C
This video describes the procedure of tabulating and analyzing the likert scale survey data using Microsoft Excel. This video also explains how to prepare graph from the tabulated data. Photo courtesy: http://littlevisuals.co/
Views: 97820 Edifo
Purchase the spreadsheet (formulas included!) that's used in this tutorial for $5: https://gum.co/satisfactionsurvey ----- Soar beyond the dusty shelf report with my free 7-day course: https://depictdatastudio.teachable.com/p/soar-beyond-the-dusty-shelf-report-in-7-days/ Most "professional" reports are too long, dense, and jargony. Transform your reports with my course. You'll never look at reports the same way again.
Views: 366911 Ann K. Emery
This screen cast demonstrates the use of Microsoft Excel to organize information for qualitative research.
Views: 40019 tamuwritingcenter
An introduction to the subjects of Qualitative and Quantitative research. When organisations enter into strategic planning, they often conduct different types of relevant research and analyses enabling them to make informed, strategic decisions. Parts of this process might include conducting qualitative and/or quantitative research, which is what this video aims to explain and exemplify. This video is aimed at marketing management students.
Views: 67802 Tine Wade
How to enter and analyze questionnaire (survey) data in SPSS is illustrated in this video. Lots more Questionnaire/Survey & SPSS Videos here: https://www.udemy.com/survey-data/?couponCode=SurveyLikertVideosYT Check out our next text, 'SPSS Cheat Sheet,' here: http://goo.gl/b8sRHa. Prime and ‘Unlimited’ members, get our text for free. (Only 4.99 otherwise, but likely to increase soon.) Survey data Survey data entry Questionnaire data entry Channel Description: https://www.youtube.com/user/statisticsinstructor For step by step help with statistics, with a focus on SPSS. Both descriptive and inferential statistics covered. For descriptive statistics, topics covered include: mean, median, and mode in spss, standard deviation and variance in spss, bar charts in spss, histograms in spss, bivariate scatterplots in spss, stem and leaf plots in spss, frequency distribution tables in spss, creating labels in spss, sorting variables in spss, inserting variables in spss, inserting rows in spss, and modifying default options in spss. For inferential statistics, topics covered include: t tests in spss, anova in spss, correlation in spss, regression in spss, chi square in spss, and MANOVA in spss. New videos regularly posted. Subscribe today! YouTube Channel: https://www.youtube.com/user/statisticsinstructor Video Transcript: In this video we'll take a look at how to enter questionnaire or survey data into SPSS and this is something that a lot of people have questions with so it's important to make sure when you're working with SPSS in particular when you're entering data from a survey that you know how to do. Let's go ahead and take a few moments to look at that. And here you see on the right-hand side of your screen I have a questionnaire, a very short sample questionnaire that I want to enter into SPSS so we're going to create a data file and in this questionnaire here I've made a few modifications. I've underlined some variable names here and I'll talk about that more in a minute and I also put numbers in parentheses to the right of these different names and I'll also explain that as well. Now normally when someone sees this survey we wouldn't have gender underlined for example nor would we have these numbers to the right of male and female. So that's just for us, to help better understand how to enter these data. So let's go ahead and get started here. In SPSS the first thing we need to do is every time we have a possible answer such as male or female we need to create a variable in SPSS that will hold those different answers. So our first variable needs to be gender and that's why that's underlined there just to assist us as we're doing this. So we want to make sure we're in the Variable View tab and then in the first row here under Name we want to type gender and then press ENTER and that creates the variable gender. Now notice here I have two options: male and female. So when people respond or circle or check here that they're male, I need to enter into SPSS some number to indicate that. So we always want to enter numbers whenever possible into SPSS because SPSS for the vast majority of analyses performs statistical analyses on numbers not on words. So I wouldn't want and enter male, female, and so forth. I want to enter one's, two's and so on. So notice here I just arbitrarily decided males get a 1 and females get a 2. It could have been the other way around but since male was the first name listed I went and gave that 1 and then for females I gave a 2. So what we want to do in our data file here is go head and go to Values, this column, click on the None cell, notice these three dots appear they're called an ellipsis, click on that and then our first value notice here 1 is male so Value of 1 and then type Label Male and then click Add. And then our second value of 2 is for females so go ahead and enter 2 for Value and then Female, click Add and then we're done with that you want to see both of them down here and that looks good so click OK. Now those labels are in here and I'll show you how that works when we enter some numbers in a minute. OK next we have ethnicity so I'm going to call this variable ethnicity. So go ahead and type that in press ENTER and then we're going to the same thing we're going to create value labels here so 1 is African-American, 2 is Asian-American, and so on. And I'll just do that very quickly so going to Values column, click on the ellipsis. For 1 we have African American, for 2 Asian American, 3 is Caucasian, and just so you can see that here 3 is Caucasian, 4 is Hispanic, and other is 5, so let's go ahead and finish that. Four is Hispanic, 5 is other, so let's go to do that 5 is other. OK and that's it for that variable. Now we do have it says please state I'll talk about that next that's important when they can enter text we have to handle that differently.
Views: 526584 Quantitative Specialists
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: 363832 CrashCourse