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

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?

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

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

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

Statistical Analysis Designing research Sample size Sampling error Appropriateness of instruments

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

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

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

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

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

Normal Curve 14% 2% 14% 34% 34% 2%

Bar Graph

Histogram

Boxplot

Pie Chart

Scattergram

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 ##.

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

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.

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

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

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

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

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

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

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

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

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

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

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

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

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

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