1 / 37

Measurement

Measurement. 9/11/2012. Readings. Chapter 3 Proposing Explanations, Framing Hypotheses, and Making Comparisons (Pollock) (pp.48-58) Chapter 1 Introduction to SPSS (Pollock Workbook) . Opportunities to discuss course content. Office Hours For the Week. When And appointment

duff
Download Presentation

Measurement

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Measurement 9/11/2012

  2. Readings • Chapter 3 Proposing Explanations, Framing Hypotheses, and Making Comparisons (Pollock) (pp.48-58) • Chapter 1 Introduction to SPSS (Pollock Workbook)

  3. Opportunities to discuss course content

  4. Office Hours For the Week • When • And appointment • Not scientific knowledge

  5. Course Learning Objectives • Students will learn the research methods commonly used in behavioral sciences and will be able to interpret and explain empirical data. • Students will learn the basics of research design and be able to critically analyze the advantages and disadvantages of different types of design. 

  6. A way of getting content validity Indexes and Scales

  7. Why create a scale/index? • To form a composite measure of a complex phenomenon by using two or more items • Get at all facets • Simplify our data

  8. Examples • GPA

  9. Likert Scale • A common way of creating a scale • Advantages • Disadvantages

  10. Guttman Scaling • Employs a series of items to produce a score for respondents • Ordering questions that become harder to agree with • Advantages and disadvantages

  11. Guttman Scale

  12. SPSS Statistical Package for the Social Sciences

  13. What is a statistical package • Popular Versions • SPSS • SAS • R • Stata

  14. Getting SPSS Don’t Do Use it on the machines on campus- free! Consider purchasing a 6-month license (49.00 + 4.99 download fee) • Purchase a student version • Limited functions • Limited variables • Searching the internet for a “free version” • You might get a virus • The Russians will steal your identity (exception fallacy).

  15. How to Open Data files • Data Files on the Pollack CD • GSS2008.SAV- the 2008 General Social Survey Dataset • n=2023 • 301 variables • NES2008.SAV- the National Election Study from 2008. n=2323 • 302 variables • STATES.SAV- aggregate level data for the 50 States. N=50 • 82 Variables • WORLD.SAV- aggregate level data for the nations of the world. n=191 • 69 Variables

  16. SPSS uses 2 windows • Data Editor Window • is used to define and enter your data and to perform statistical procedures. • very spread-sheet like • .sav extension • The Output Window • this is where results of statistical tests appear • This opens when you run your first test • .spv extension

  17. How SPSS Works

  18. It is like a spreadsheet • In Variable View • You define your parameters • Give variables names • Operationalize variables • We will not do a lot of this

  19. Names and Labels Name Labels A longer definition of the variable These describe the actual variable • how the label appears at the top of the column (like the first row in excel) • you cant use dashes, special characters or start with numbers • These should represent the variable

  20. Value Labels • This shows how variables are operationalized • Value= the numeric value given to a category • Label= the attribute of the concept

  21. In Data View • You type in raw data • It looks very much like Excel • Rows= cases • Columns= Variables

  22. How Things are Displayed Edit • Options • Display names • Alphabetical

  23. Exiting SPSS • If you changed the actual dataset you must save it • If you ran any statistics, you must save these as well

  24. Variables

  25. Variables • Measured Concepts • We need to operationalize concepts to test hypotheses

  26. Four Categories of Variables

  27. Discrete variables

  28. Nominal Variables • Identify, label, and operationalize categories • Categories are • Exhaustive • Mutually Exclusive • Values are their for quantification only

  29. Nominal Examples

  30. Ordinal Variables • These identify, rank order, label, and operationalize categories • The Numbers mean something here • Operationalization denotes more or less of an attribute

  31. Ordinal Examples

  32. Continuous Variables

  33. What about em’ • The values matter • Your variable includes all possible values, not just the one’s that you assign. • Name, order, and the distances between values matter.

  34. Interval Level Variables • The values matter at this level • The distances matter • The zero is arbitrary

  35. Examples of Interval Scales

  36. Ratio Variables • The Full properties of numbers • A zero means the absence of a property • Classify, order, set units of distance

  37. Examples

More Related