1. A N I NTRODUCTION TO QDA M INER: or IS QDA MINER REALLY A BETTER SOLUTION FOR MIXED METHODS RESEARCH? By Normand Péladeau President Provalis Research Corp.

2. Integration of numerical data Inclusion of socio-demographic data, responses to closed-ended questions, etc.Inclusion of socio-demographic data, responses to closed-ended questions, etc. Limited ability to perform comparisons & no statisticsLimited ability to perform comparisons & no statistics Performing statistics on/with qualitative data 1)Export code frequency matrix to file 2)Open statistical software 3)Import saved matrix 4)Run statistical analysis MIXED METHODS IN TRADITIONNAL CAQDAS

3. 1)Same file format as SimStat (a stat software) and full interoperability between the two. Ability to keep numerical, categorical data, dates and text data in a single data file HOW DOES QDA MINER DIFFERS?

6. 1)Same file format as SimStat (a stat software) and full interoperability between the two. Ability to keep numerical, categorical data, dates and text data in a single data file HOW DOES QDA MINER DIFFERS?

7. 1)Same file format as SimStat (a stat software) and full interoperability between the two. Ability to keep numerical, categorical data, dates and text data in a single data file 2)Integration of statistical tools Frequencies and percentages, F-test, chi-square, correlation, clustering, multidimensional scaling, correspondence analysis. HOW DOES QDA MINER DIFFERS?

8. STATISTICS ON QUALITATIVE DATA

10. 1)Same file format as SimStat (a stat software) and full interoperability between the two. Ability to keep numerical, categorical data, dates and text data in a single data file 2)Integration of statistical tools Frequencies and percentages, F-test, chi-square, correlation, clustering, multidimensional scaling, correspondence analysis. HOW DOES QDA MINER DIFFERS?

11. 1)Same file format as SimStat (a stat software) and full interoperability between the two. Ability to keep numerical, categorical data, dates and text data in a single data file 2)Integration of statistical tools Frequencies and percentages, F-test, chi-square, correlation, clustering, multidimensional scaling, correspondence analysis. 3)Integration of other text analysis techniques Within QDA Miner itselfWithin QDA Miner itself With WordStat (a content analysis add-on)With WordStat (a content analysis add-on) HOW DOES QDA MINER DIFFERS?

12. ANALYSIS OF TEXTUAL DATA Text Mining Content Analysis Information Retrieval ANALYSIS OF NUMERICAL DATA Statistical Analysis Qualitative Analysis Computational Linguistic Mixed Methods INTEGRATING TEXT ANALYSIS TECHNIQUES

13. QUALITATIVE CONTENT ANALYSIS One can use codings in QDA Miner to control what will be analyzed by WordStat

14. QUALITATIVE CONTENT ANALYSIS

15. One can use WordStat text-mining features or dictionaries to search and code segments in QDA Miner CONTENT ANALYSIS QUALITATIVE

16. Boolean search ( AND, OR, NOT ) Information Retrieval Models Similarity search Similarity search QUALITATIVE + INFORMATION RETRIEVAL

17. QUERY BY EXAMPLES

20. Relevance feedback mechanismRelevance feedback mechanism Fuzzy string matchingFuzzy string matching Resistant to misspelling Matches related words Ex.: resistant to misspelling Ex.: resistant to misspelling resistent to mispeling resistent to mispeling resist to misspelled words resist to misspelled words resist to words not correctly spelled resist to words not correctly spelled QUERY BY EXAMPLES

21. General Introduction 10 minutes tour of QDA Miner 3.2 10 minutes tour of QDA Miner 3.210 minutes tour of QDA Miner 3.210 minutes tour of QDA Miner 3.2 10 minutes tour of WordStat 5.0 10 minutes tour of WordStat 5.010 minutes tour of WordStat 5.010 minutes tour of WordStat 5.0 Specific Features of QDA Miner Importing NVivo projectsThe Bubble Chart featureImporting NVivo projectsThe Bubble Chart feature The Coding of GraphicsThe Query by ExampleThe Coding of GraphicsThe Query by Example The Report ManagerKeyword Retrieval featuresThe Report ManagerKeyword Retrieval features The Command LogAutomatic Document ClassificationThe Command LogAutomatic Document Classification The Code Sequences FeatureCoded text highlightingThe Code Sequences FeatureCoded text highlighting Segment Retrieval Techniques ADDITIONAL LEARNING RESOURCES Click on any of the above links for self-running demos