1. Three Types of Unobtrusive Research 1.Content analysis - examine written documents such as editorials. 2.Analyses of existing statistics. 3.Historical/comparative analysis - historical records.

2. What is Content Analysis? Study of recorded human communication Topic Appropriate for CA –Interpretation of texts “who says what, to whom, how, and with what” Assist in analyzing interview data Media transcripts

3. Example Investigated the media’s role in framing the welfare privatization debate with a content analysis of ABC, CBS & NBC evening news & special programs from 1/1/94 to 8/22/96. Specials include Nightline, 20/20 and This Week with David Brinkley on ABC; 60 Minutes, 48 Hours and Face the Nation on CBS. Searched LexisNexis and the Vanderbilt Television Archives for all transcripts pertaining to the issue of how welfare should be administered, and found 191 stories. At the time of the study NBC’s transcripts are not available on LexisNexis prior to 1997. Authors searched for stories using the Vanderbilt News Archives and then purchased pre-1997 transcripts from Burrell’s Transcripts.

4. Coding, Counting and Record Keeping Unit of Analysis Sampling Designing coding procedures –Conceptualization and operationalization Analysis: –Counting –Qualitative evaluation

5. Coding: Pro-Privatization Frames CAUSE OF PROBLEM/PROBLEM/SOLUTION 9. Delivery / dependency / faith-based 10. Delivery / economic costs / faith-based 11. Delivery / dependency / non-profits 12. Delivery / econ. costs / non-profits 13. Delivery / dependency / for-profits 14. Delivery / econ. costs / for-profits 16. Gen govt / dependency / faith-based 17. Gen govt / econ. costs / faith-based 18. Gen govt / dependency / non-profits

6. Coding: Anti-Privatization Frames CAUSE OF PROBLEM/PROBLEM/SOLUTION 3. Privatization / job loss / don’t privatize 4. Privatization / job loss / don’t devolve 5. Privatization / accountability / don’t privatize 6. Privatization / accountability / don’t devolve 11. Secular / job loss / don’t privatize 12. Secular / job loss / don’t devolve 13. Secular / accountability / don’t privatize

7. Hypothesis & Findings Authors hypothesized that mainstream (corporate owned) media would be biased toward privatization. Findings did not support such a hypothesis. Media coverage was remarkably balanced (with slight leaning against privatization)

8. Strengths of Content Analysis Economy of time and money. Easy to repeat a portion of the study if necessary. Permits study of processes over time. Researcher seldom has any effect on the subject being studied. Reliability.

9. Weaknesses of Content Analysis Limited to the examination of recorded communications. Problems of validity are likely.

10. Analyzing Existing Statistics Can be the main source of data or a supplemental source of data. Often existing data doesn't cover the exact question. Reliability is dependent on the quality of the statistics. Examples: Census data, Crime Stats

11. Analyzing Existing Statistics Can be the main source of data or a supplemental source of data. Often existing data doesn't cover the exact question. Reliability is dependent on the quality of the statistics. Examples: Census data, Crime Stats

12. Problems with Existing Statistics Problems with Validity –What’s available v. what is needed Problems with Reliability –Moreno Valley Example

13. OLS Regression What is it? Closely allied with correlation – interested in the strength of the linear relationship between two variables One variable is specified as the dependent variable The other variable is the independent (or explanatory) variable

14. Regression Model Y = a + bx + e What is Y? What is a? What is b? What is x? What is e? What is Y-hat?

15. Elements of the Regression Line a = Y intercept (what Y is predicted to equal when X = 0) b = Slope (indicates the change in Y associated with a unit increase in X) e = error (the difference between the predicted Y (Y hat) and the observed Y

16. Regression Has the ability to quantify precisely the relative importance of a variable Has the ability to quantify how much variance is explained by a variable(s) Use more often than any other statistical technique

17. The Regression Line Y = a + bx + e Y = sentence length X = prior convictions Each point represents the number of priors (X) and sentence length (Y) of a particular defendant The regression line is the best fit line through the overall scatter of points

18. X and Y are observed. We need to estimate a & b

20. How do you draw a line when the line can be drawn in almost any direction? The Method of Least Squares: drawing a line that minimizing the squared distances from the line (Σe 2 ) This is a minimization problem and therefore we can use differential calculus to estimate this line.

21. X and Y are observed. We need to estimate a & b

22. Least Squares Method xy Deviation =y-(a+bx)d2 011 - a(1 - a) 2 1-2a+a2 133 - a - b(3 - a - b) 2 9 - 6a + a 2 - 6b + 2ab + b 2 222 - a - 2b(2 - a - 2b) 2 4 - 4a - a 2 - 8b + 4ab + 4b 2 344 - a - 3b(4 - a - 3b) 2 16 - 8a + a 2 - 24b + 6ab +9b 2 455 - a - 4b(5 - a - 4b) 2 25 - 10a +a 2 -40b +8ab +16b 2

23. Estimating the model (the easy way) Calculating the slope (b)

24. Sum of Squares for X Some of Squares for Y Sum of produces

25. Calculating the Y-intersept (a) Calculating the error term (e) Y hat = predicted value of Y e will be different for every observation. It is a measure of how much we are off in are prediction.

26. Regression is strongly related to Correlation