1. Disseminating Research Findings Shawn A. Lawrence, PhD, LCSW SOW 3401
Analyzing Data and
Disseminating Research Findings
Shawn A. Lawrence, PhD, LCSW
SOW 3401

2. The Data in Perspective
Understand basic characteristics of the data
Who was the population?
How was the sample selected?
How was the data gathered?
What was the response rate?
What does the data mean?

3. Preparing Data for Analysis
Review purpose of the study
Compare treatment and control groups
Relate two or more variables
Explore the processes of a phenomenon
Provide statistics on prevalence

4. Data Analysis: Qualitative
Looser rules
Can be creative
Can use software to
Help code data
Perform statistical analyses
Can use separate judges

5. Data Analysis: Quantitative
Relies heavily on statistics
Can use software
SPSS, R, Minitab, etc.
Statistical analysis
Designing research
Summarizing data distribution
Estimating population characteristics
Answering questions and testing hypotheses

6. Statistical Analysis Designing research Sample size Sampling error
Appropriateness of instruments

7. Coding
In order for computers to read data that has been collected the information must be coded
Reduce a wide variety of items of information into a limited set of attributes that compose a variable

8. Coding Better to start off with categories with great detail
If data is coded into a few large categories there is no way to bring back the detail

9. Statistical Analysis Summarizing data distribution
Descriptive statistics
Provides an understandable idea of what the data looks like
Percentages
Frequency distributions
Central tendency
Mean, median, mode
Variation
Range, interquartile range, standard variation

10. Statistical Analysis
Frequency table- shows how frequently each rating occurred. Makes a pattern of numbers easy to see

11. Statistical Analysis Descriptive statistics Figures Bar graphs
Histogram
Boxplots
Pie chart
Scattergram

12. Normal Curve
14% 2%
14%
34%
34% 2%

13. Bar Graph

14. Histogram

15. Boxplot

16. Pie Chart

17. Scattergram

18. Estimating Population Characteristics
Using data from a sample
Can estimate the characteristics of that population with a degree of certainty
Confidence interval
We are 95% sure that the mean is between ## and ##.

19. Answering Questions and Testing Hypotheses
Inferential statistics
Tests used to help determine whether what was seen was do to the manipulation or sampling error
Provide the probability that the results are correct
In social sciences, the threshold is typically 95%
Statistically significant-calculates the odds that our results are due to chance
Measures of association
Provide the magnitude of a relationship between variables

20. Null Hypothesis
Postulates that the relationship being tested is explained by chance. When our findings are shown to be statistically significant, we reject the null.

21. Type I Error
Occurs when you reject the null, but the null is really true. Problem is: You never know whether you are committing a type II error. Probability of making this type of error is .05 risk

22. Type II Error
Occurs if you fail to reject a false null hypothesis. This type of error indicates that just because we do not have significant findings does not mean that our hypothesis has been proven false, it just means that we lack the level of probability needed to rule out chance

23. Interpreting and Reporting the Results
Consider
Purpose of the study
Research question
Hypothesis
Provide interpretations of what the study found
Relate results back to the literature review
Include limitations of the study
Suggestions for future research
Mention any interesting findings

24. The Influence of Sample Size
The same relationship that was too weak to be significant with a smaller sample size can be significant with a larger sample.
Safer to generalize findings from large samples then from smaller ones

25. Disseminating Research Findings
Reports and monographs
Internal correspondence and in-service training
Major conferences
Other professional gatherings
Publications in professional journals

26. Measures of Association
A significance level of .001 is not stronger than .05.
Significance testing does not tell us how strong a relationship is.

27. Disseminating Research Findings
Reports and monographs
Theses
Dissertations
Reports to the funders

28. Disseminating Research Findings
Quantitative reports
Introduction
Literature review
Research questions and hypotheses
Methodology
Results
Discussion, conclusions, and implications
Limitations
Conclusions and recommendations
Appendices

29. Disseminating Research Findings
Qualitative reports
Intro, lit. rev., and methods tend to be shorter
Typically lack a hypothesis
Findings and discussion tend to be longer
Limitations tend to be shorter
Conclusions and recommendations are more tentative

30. Disseminating Research Findings
Internal correspondence and in-service training
Inform coworkers of findings
Improve their programs
Are likely to be interested in a coworker's research

31. Disseminating Research Findings
Major conferences
Researcher answers a call for proposal/abstract
Provide objectives of presentation
Proposals are reviewed anonymously
Researchers are informed of the acceptance/denial
Researchers accept their acceptance
Present presentation!
Can also present a poster

32. Disseminating Research Findings
Other professional gatherings
Benefits
Cheaper
Research tends to be local
May be easier to network

33. Disseminating Research Findings
Publication in professional journals
Most traditional manner
Bought by libraries
Tend to use a blind review system
Only send one copy to one journal at a time!
May take a long time
Expect many reviews

34. Disseminating Research Findings
Publication in professional journals
Possible responses to a submission
Accepted the first time
Very rare
Rejected
Try another journal
Rejected, but can revise
Make the revisions and resubmit
Or submit elsewhere