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# Intro to quant_s_tudents

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### Intro to quant_s_tudents

1. 1. Week 10 Intro. to Quantitative Methods 1 Prof. Michelle Brady and Lindsay Tedds Basic Concepts
2. 2. Overview • Qualitative vs. Quantitative • Main Goals of Quant Research • Operationalization & Measurement • Types of Variables • Levels of Measurement (Variables) • Data & Statistics @ Uvic 2
3. 3. Introduction Prof. Michelle Brady & Lindsay Tedds3  Qualitative vs. Quantitative  Characteristics of Quant. Analysis (Positivism)  Numbers and statistics (counting)  Objective, context-free  Researcher is separate from the data  One reality  Representative  Efficient http://www.youtube.com/watch?v=WDo7jwikqqI
4. 4. Main Goals of Quantitative Researchers Prof. Michelle Brady & Lindsay Tedds4  Measurement  Generalization  External Validity  Replication  Reliability  Establishing causality (Sometimes)  Internal Validity
5. 5. Operationalization & Measurement Research Question Operationalizing Variables Measuring Variables 5 Construct Validity Reliability
6. 6. Types of Variables Variables Categorical or Qualitative Numerical or Quantitative Discrete Continuous 6
7. 7. Levels of Measurement Nominal Ordinal Interval Ratio Levels of Measurement  Data can be classified into one of four levels of measurement Page 7
8. 8. Atlantic Canada 1 60 Quebec 2 316 Ontario 3 343 Prairies 4 114 B.C. 5 77 Levels of Measurement 1. Nominal  Qualitative variable that can only be classified into categories and counted  Categories have no logical order  Categories are mutually exclusive and exhaustive Page 8
9. 9. Never 1 4 Sometimes 2 23 Frequently 3 27 Always 4 8 Levels of Measurement 2. Ordinal  Mutually exhaustive and exclusive categories, counted, and ranked but we can’t distinguish the magnitude of the difference between the categories  E.G. is “Always” twice as much as “Sometimes”? Page 9
10. 10. 3. Interval  Mutually exhaustive and exclusive categories, counted, and ranked and we can distinguish the magnitude of the difference between the categories and the difference between values is a constant size  0, if present, is just a point on the scale and does not represent the absence of the condition  Rare in data: E.g. temperature, dates Levels of Measurement Page 10
11. 11. 4. Ratio  Mutually exhaustive and exclusive categories, counted, and ranked and we can distinguish the magnitude of the difference between the categories and the difference between values is a constant size  The zero point is meaningful as is the ratio between two number  Most quantitative data fall into this category  E.G. Income Levels of Measurement Page 11
12. 12. Measurement Levels Page 12 Interval Data Ordinal Data Nominal Data Quantitative Data Qualitative Data Categories (no ordering or direction) Ordered Categories (rankings, order, or scaling) Differences between measurements but no true zero Ratio Data Differences between measurements, true zero exists
13. 13. Data & Statistics: Where to find them Prof. Michelle Brady & Lindsay Tedds13  For help with Data and Statistics sources, contact Kathleen Matthews, Data Services Librarian kmatthew@uvic.ca http://library.uvic.ca/site/data/default.html  Published statistics are available from a variety of print and online sources. Consult the Libraries Subject Guides. For a quick overview, you can check statistics by topic from Statistics Canada. For help in finding published statistics, Ask a Librarian, or contact the Subject Librarian of your choice. http://webapp.library.uvic.ca/kb/?View=entry&EntryID=35
14. 14. Next Week Prof. Michelle Brady & Lindsay Tedds14  We are in the computer lab (See Moodle)  Work through the Excel tutorials in advance  We will cover based data analysis techniques and practice them in the lab
15. 15. Scoping Review Prof. Michelle Brady & Lindsay Tedds15  Scope and Limitations  Template