• Coding Qualitative Data

    At the end of the module the learner will be expected to be able to: •Discuss the key assumptions of qualitative research and the measurement of empirical phenomena •Describe and evaluate a range of qualitative techniques suitable utilised in applied research •Evaluate the validity, reliability and ethical implications of specific qualitative research strategies •Select appropriate quantitative techniques for particular research questions This session has been developed through the Learning from WOeRK project at Plymouth University and seeks to support learning in the work place. For an overview of all related modules and resources please visit http://cpdoer.net/collections/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: Eng...

    published: 28 Sep 2011
  • The Coding Data Matrix and Variable Types. Part 1 of 3 on Quantitative Coding and Data Entry

    A lecture on coding and data entry in quantitative research by Graham R Gibbs taken from a series on quantitative data analysis and statistics given to undergraduate students at the University of Huddersfield. This is part 1 of 3 and covers the basic principles of coding quantitative data from questionnaires and the types of variables that can be used. Credits: Music: Kölderen Polka by Tres Tristes Tangos is licensed under an Attribution-ShareAlike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos/ Image: Ice-ferns by Schnobby, Wikimedia Commons, licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.

    published: 27 Feb 2014
  • Zafar Abbas Data Coder

    Zafar Abbas Data Coder CMP Lahore

    published: 19 Sep 2009
  • Excel and Questionnaires: How to enter the data and create the charts

    This is a tutorial on how to enter the results of your questionnaires in Excel 2010. It then shows you how to create frequency tables (using the countif function not the frequency function). The next stage is creating charts.

    published: 14 Feb 2013
  • Qualitative analysis of interview data: A step-by-step guide

    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 ...

    published: 19 May 2013
  • Ascribe Coder

    published: 17 Feb 2014
  • Coding Part 2: Thematic coding

    Thematic coding is one of the most common forms of qualitative data analysis and it is found in grounded theory, several forms of phenomenological analysis and framework analysis. The analyst tries to identify themes, categories or classifications of the data. Passages of the data (commonly an interview transcript) are coded to the themes - that is the passages are tagged or marked with the name of the theme.

    published: 25 Oct 2011
  • Ordinal data: Krippendorff alpha inter-rater reliability test

    How to use a statistical test (Krippendorff alpha) to check the reliability of a variable with ordinal data, using a Windows PC and SPSS. Six observers have rated 30 student. The question was “How would you rate this individual student?” 1 = Excellent 2 = Above Average 3 = Average 4 = Below Average Here, I have six judges and no missing data. However, this statistical test can be used with any number of judges and with or without missing data. In SPSS, click File, Open, Syntax, and open the macro “kalpha.sps”. If you do not have this special file, please see my previous video “Nominal dichotomous yes/no data: Krippendorff alpha inter-rater reliability” where I show you how to find and download it. Execute this macro. Open your data file. Run the statistical test, by clicking File, N...

    published: 03 Mar 2017
  • Coding Part 1: Alan Bryman's 4 Stages of qualitative analysis

    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

    published: 24 Oct 2011
  • Your Database is Slow | Coder Radio 91

    Oren Eini from Hibernating Rhinos joins us to discuss their "second generation" document database written in .NET. We have an insightful conversation about RavenDB, a flexible data model designed to address requirements coming from real-world systems. Plus our surprising answer to the big certification question, your emails, and more. Show Notes & Download: http://bit.ly/cradio91

    published: 03 Mar 2014
  • Ascribe Coder Walk Thru 01 29 2015

    This is a general overview of Ascribe Coder. Ascribe Coder is a web-based text mining and text coding management solution that allows users to categorize unstructured data, specifically text data, with ease and precision. Ascribe Coder’s best-in-class technology provides an environment to code and analyze mass amounts of textual content with the detail needed to make informed business decisions. This is why the world’s largest research organizations use Ascribe Coder – it puts high-quality results in the client’s hands faster, at lower costs, for a better experience. http://goascribe.com/

    published: 17 Feb 2016
  • coding open-ended questions made easy with smart.coder

    This tutorial shows how to automatically code answers to open-ended questions with smart.coder. Code open-ended questions at http://www.smartcoder.at/

    published: 04 May 2013
  • Slacking while Coding | Coder Radio 187

    Is the age of Apps finally coming to an end? Data points to yes & we discuss how platforms like Slack might offer more potential. Then, more web developers are switching to Linux, is this the start of a trend? Plus what caught our attention in the new iOS release, and interesting projects Google has in store for 2016. Show Notes & Download: http://bit.ly/coder187

    published: 11 Jan 2016
  • Content Analysis Coding

    published: 10 Jan 2016
  • Information Theory And Coding - Convolutional Codes

    Information Theory And Coding.

    published: 08 Dec 2015
  • THE CODER 명품 보안 솔루션

    THE CODER (社)는 사물에 데이터를 삽입할수있는 IT 기업입니다. (IT/IOT/ICT/Sound transmission/Security) A company that can insert data into all things www.thecoder.co.kr Email :jmin@thecoder.co.kr The Coder mr j. min 🔊 사운드 코딩 기술 코더의 음성 인식 기술은 스마트폰 으로 인식 할 수있는 가청 주파수 범위의 소리를 인코딩합니다. 통신 가능한 정보는 이미지 스캔 기술에 필적한다. 일반적인 음성 인식 시스템은 소리의 손실을 피하기 위해 저음 또는 고주파 음을 사용하지만, 이러한 주파수는 필터링 된 공중 방송에서는 데이터가 삭제된다. 코더의 음성 인식 기술은 실제 소리를 손상시키지 않고 가청 주파수 범위의 소리를 인코딩합니다. 따라서 이러한 기술은 스피커의 사양이나 환경 소음에 관계없이 높은 인식률로 공중 방송에 이용할수 있습니다. Sound Coding Technology The Coder's sound recognition technology encodes audible frequency range sounds that can be recognized by mobile applications. The information that can be communicated is comparable to the image scan technology. General sound recognition systems use low or high frequ...

    published: 28 Apr 2017
Coding Qualitative Data

Coding Qualitative Data

  • Order:
  • Duration: 6:41
  • Updated: 28 Sep 2011
  • views: 51362
videos
At the end of the module the learner will be expected to be able to: •Discuss the key assumptions of qualitative research and the measurement of empirical phenomena •Describe and evaluate a range of qualitative techniques suitable utilised in applied research •Evaluate the validity, reliability and ethical implications of specific qualitative research strategies •Select appropriate quantitative techniques for particular research questions This session has been developed through the Learning from WOeRK project at Plymouth University and seeks to support learning in the work place. For an overview of all related modules and resources please visit http://cpdoer.net/collections/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales License
https://wn.com/Coding_Qualitative_Data
The Coding Data Matrix and Variable Types. Part 1 of 3 on Quantitative Coding and Data Entry

The Coding Data Matrix and Variable Types. Part 1 of 3 on Quantitative Coding and Data Entry

  • Order:
  • Duration: 19:31
  • Updated: 27 Feb 2014
  • views: 9815
videos
A lecture on coding and data entry in quantitative research by Graham R Gibbs taken from a series on quantitative data analysis and statistics given to undergraduate students at the University of Huddersfield. This is part 1 of 3 and covers the basic principles of coding quantitative data from questionnaires and the types of variables that can be used. Credits: Music: Kölderen Polka by Tres Tristes Tangos is licensed under an Attribution-ShareAlike 3.0 International License. http://freemusicarchive.org/music/Tres_Tristes_Tangos/ Image: Ice-ferns by Schnobby, Wikimedia Commons, licensed under the Creative Commons Attribution-Share Alike 3.0 Unported license.
https://wn.com/The_Coding_Data_Matrix_And_Variable_Types._Part_1_Of_3_On_Quantitative_Coding_And_Data_Entry
Zafar Abbas Data Coder

Zafar Abbas Data Coder

  • Order:
  • Duration: 0:07
  • Updated: 19 Sep 2009
  • views: 17
videos
Zafar Abbas Data Coder CMP Lahore
https://wn.com/Zafar_Abbas_Data_Coder
Excel and Questionnaires: How to enter the data and create the charts

Excel and Questionnaires: How to enter the data and create the charts

  • Order:
  • Duration: 14:37
  • Updated: 14 Feb 2013
  • views: 197574
videos
This is a tutorial on how to enter the results of your questionnaires in Excel 2010. It then shows you how to create frequency tables (using the countif function not the frequency function). The next stage is creating charts.
https://wn.com/Excel_And_Questionnaires_How_To_Enter_The_Data_And_Create_The_Charts
Qualitative analysis of interview data: A step-by-step guide

Qualitative analysis of interview data: A step-by-step guide

  • Order:
  • Duration: 6:51
  • Updated: 19 May 2013
  • views: 308162
videos
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
https://wn.com/Qualitative_Analysis_Of_Interview_Data_A_Step_By_Step_Guide
Ascribe Coder

Ascribe Coder

  • Order:
  • Duration: 8:05
  • Updated: 17 Feb 2014
  • views: 793
videos
https://wn.com/Ascribe_Coder
Coding Part 2: Thematic coding

Coding Part 2: Thematic coding

  • Order:
  • Duration: 6:45
  • Updated: 25 Oct 2011
  • views: 106618
videos
Thematic coding is one of the most common forms of qualitative data analysis and it is found in grounded theory, several forms of phenomenological analysis and framework analysis. The analyst tries to identify themes, categories or classifications of the data. Passages of the data (commonly an interview transcript) are coded to the themes - that is the passages are tagged or marked with the name of the theme.
https://wn.com/Coding_Part_2_Thematic_Coding
Ordinal data: Krippendorff alpha inter-rater reliability test

Ordinal data: Krippendorff alpha inter-rater reliability test

  • Order:
  • Duration: 4:27
  • Updated: 03 Mar 2017
  • views: 575
videos
How to use a statistical test (Krippendorff alpha) to check the reliability of a variable with ordinal data, using a Windows PC and SPSS. Six observers have rated 30 student. The question was “How would you rate this individual student?” 1 = Excellent 2 = Above Average 3 = Average 4 = Below Average Here, I have six judges and no missing data. However, this statistical test can be used with any number of judges and with or without missing data. In SPSS, click File, Open, Syntax, and open the macro “kalpha.sps”. If you do not have this special file, please see my previous video “Nominal dichotomous yes/no data: Krippendorff alpha inter-rater reliability” where I show you how to find and download it. Execute this macro. Open your data file. Run the statistical test, by clicking File, New, Syntax and type: kalpha judges = teacher1 teacher2 teacher3 teacher4 teacher5 teacher6/level = 2/detail = 0/boot = 10000 Then: Run, All The Krippendorff's Alpha Reliability Estimate here is 0.6159. An alpha below 0.67 indicates a really low inter-rater reliability. Ideally, it should be over 0.8. Below 0.8 but above 0.67 indicates low reliability. Source: Krippendorff’s own book Content Analysis: An Introduction to Its Methodology. (Published by SAGE.) The table shows that there is an estimated 70.01 percent chance that the alpha would be below 0.67 if the whole population would be tested. A Krippendorff alpha of just 0.6159 is perhaps too low to be used in a report, but I still include an example here, just to show how these types of results are written out. Method The Krippendorff’s alpha test was used (Hayes & Krippendorff, 2007) to estimate the inter-coder reliability, and these alpha (α) values are reported in the results below. Results The results show that the inter-coder reliability was low (α = 0.6159), i.e. that the six observers did not agree. Discussion (Here, discuss possible reasons why the observers did not agree.) References Hayes, A. F., & Krippendorff, K. (2007). Answering the call for a standard reliability measure for coding data. Communication Methods and Measures 1(1), 77-89. Let us do it again, with another set of example data. Here we have four observers who are rating 12 individuals. There are missing data, but that is no problem for the Krippendorff alpha test. It is one great advantage, compared to other statistical tests. File, New, Syntax. kalpha judges = obsa obsb obsc obsd/level = 2/detail = 0/boot = 10000 The Krippendorff's Alpha Reliability Estimate here is 0.8095. There is a 6.46 percent chance that the alpha would be below 0.67 if the whole population would be tested. This is an example of how it can be reported in text: Method The Krippendorff’s alpha test was used (Hayes & Krippendorff, 2007) to estimate the inter-coder reliability, and these alpha (α) values are reported in the results below. Results The results show a relatively high inter-coder reliability (α = 0.8095), i.e. that the four observers were in agreement with each other. Discussion (Discuss plausible reasons why the observers agreed as well as possible consequences.) References Hayes, A. F., & Krippendorff, K. (2007). Answering the call for a standard reliability measure for coding data. Communication Methods and Measures 1(1), 77-89.
https://wn.com/Ordinal_Data_Krippendorff_Alpha_Inter_Rater_Reliability_Test
Coding Part 1: Alan Bryman's 4 Stages of qualitative analysis

Coding Part 1: Alan Bryman's 4 Stages of qualitative analysis

  • Order:
  • Duration: 9:37
  • Updated: 24 Oct 2011
  • views: 122143
videos
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
https://wn.com/Coding_Part_1_Alan_Bryman's_4_Stages_Of_Qualitative_Analysis
Your Database is Slow | Coder Radio 91

Your Database is Slow | Coder Radio 91

  • Order:
  • Duration: 54:15
  • Updated: 03 Mar 2014
  • views: 2670
videos
Oren Eini from Hibernating Rhinos joins us to discuss their "second generation" document database written in .NET. We have an insightful conversation about RavenDB, a flexible data model designed to address requirements coming from real-world systems. Plus our surprising answer to the big certification question, your emails, and more. Show Notes & Download: http://bit.ly/cradio91
https://wn.com/Your_Database_Is_Slow_|_Coder_Radio_91
Ascribe Coder Walk Thru 01 29 2015

Ascribe Coder Walk Thru 01 29 2015

  • Order:
  • Duration: 38:28
  • Updated: 17 Feb 2016
  • views: 276
videos
This is a general overview of Ascribe Coder. Ascribe Coder is a web-based text mining and text coding management solution that allows users to categorize unstructured data, specifically text data, with ease and precision. Ascribe Coder’s best-in-class technology provides an environment to code and analyze mass amounts of textual content with the detail needed to make informed business decisions. This is why the world’s largest research organizations use Ascribe Coder – it puts high-quality results in the client’s hands faster, at lower costs, for a better experience. http://goascribe.com/
https://wn.com/Ascribe_Coder_Walk_Thru_01_29_2015
coding open-ended questions made easy with smart.coder

coding open-ended questions made easy with smart.coder

  • Order:
  • Duration: 4:11
  • Updated: 04 May 2013
  • views: 1778
videos
This tutorial shows how to automatically code answers to open-ended questions with smart.coder. Code open-ended questions at http://www.smartcoder.at/
https://wn.com/Coding_Open_Ended_Questions_Made_Easy_With_Smart.Coder
Slacking while Coding | Coder Radio 187

Slacking while Coding | Coder Radio 187

  • Order:
  • Duration: 52:51
  • Updated: 11 Jan 2016
  • views: 1044
videos
Is the age of Apps finally coming to an end? Data points to yes & we discuss how platforms like Slack might offer more potential. Then, more web developers are switching to Linux, is this the start of a trend? Plus what caught our attention in the new iOS release, and interesting projects Google has in store for 2016. Show Notes & Download: http://bit.ly/coder187
https://wn.com/Slacking_While_Coding_|_Coder_Radio_187
Content Analysis Coding

Content Analysis Coding

  • Order:
  • Duration: 11:16
  • Updated: 10 Jan 2016
  • views: 41676
videos
https://wn.com/Content_Analysis_Coding
Information Theory And Coding - Convolutional Codes

Information Theory And Coding - Convolutional Codes

  • Order:
  • Duration: 13:42
  • Updated: 08 Dec 2015
  • views: 12217
videos
Information Theory And Coding.
https://wn.com/Information_Theory_And_Coding_Convolutional_Codes
THE CODER 명품 보안 솔루션

THE CODER 명품 보안 솔루션

  • Order:
  • Duration: 0:30
  • Updated: 28 Apr 2017
  • views: 53
videos
THE CODER (社)는 사물에 데이터를 삽입할수있는 IT 기업입니다. (IT/IOT/ICT/Sound transmission/Security) A company that can insert data into all things www.thecoder.co.kr Email :jmin@thecoder.co.kr The Coder mr j. min 🔊 사운드 코딩 기술 코더의 음성 인식 기술은 스마트폰 으로 인식 할 수있는 가청 주파수 범위의 소리를 인코딩합니다. 통신 가능한 정보는 이미지 스캔 기술에 필적한다. 일반적인 음성 인식 시스템은 소리의 손실을 피하기 위해 저음 또는 고주파 음을 사용하지만, 이러한 주파수는 필터링 된 공중 방송에서는 데이터가 삭제된다. 코더의 음성 인식 기술은 실제 소리를 손상시키지 않고 가청 주파수 범위의 소리를 인코딩합니다. 따라서 이러한 기술은 스피커의 사양이나 환경 소음에 관계없이 높은 인식률로 공중 방송에 이용할수 있습니다. Sound Coding Technology The Coder's sound recognition technology encodes audible frequency range sounds that can be recognized by mobile applications. The information that can be communicated is comparable to the image scan technology. General sound recognition systems use low or high frequency sounds to avoid sound loss, but such frequencies are filtered and data is deleted in public broadcastings. The Coder's sound recognition technology encodes sounds within the audible frequency range without damaging the actual sound. Therefore, such technology can be utilized in public broadcasting given the high level of recognition rate regardless of the speaker specification or environmental noise.
https://wn.com/The_Coder_명품_보안_솔루션
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