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On planning your quantitative research design for a faculty learning community project ,[object Object],[object Object],[object Object]
Before you begin…don’t read these slides unless you… ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slayter
When babies are on the way, we prepare a nursery, yes? ,[object Object],[object Object],Slayter
Metaphor:  Preparation of nursery – Preparation of data analysis plan ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Slayter
Presentation Overview: How to approach this task Slayter
Step 1:  Identify project research question, goals, objectives, intervention ,[object Object],[object Object],[object Object],Slayter
Step 1:  Identify project research question, goals, objectives, intervention Slayter Your goal is LINKAGE!!!
Step 2:  Design data collection approach that best answers your question ,[object Object],[object Object],[object Object],[object Object],[object Object],Slayter
Step 3:   Define analytic task, choose statistical test, example 1 Slayter
Step 3:   Define analytic task, choose statistical test, example 2 Slayter
Step 3:   Define analytic task, choose statistical test, example 3 Slayter
On choosing statistical tests for bivariate analyses Slayter
Requirements for each bivariate statistical test differ ,[object Object],[object Object],Slayter
Link variable type to appropriate statistical test for analytic purpose Slayter
Check assumptions that must be met to conduct statistical testing ,[object Object],[object Object],[object Object],Slayter
Slayter Cheat sheet for choosing bivariate statistics Analytic purpose you are seeking help for: Test name: Basic requirements: How to interpret: Comparing 2 or more groups on a percentage/rate Chi-square test Variable to be compared is nominal Interpret p value for statistical significance only Comparing 2 groups only on a percentage/rate Odds ratio test Variable to be compared is nominal Interpret odds (1.23 times more likely, 0.40 = 60% less likely) Comparing mean difference between 2 groups Independent samples t-test Variable to be compared is continuous Interpret p value for statistical significance only Comparing mean difference between pre and post in one group Paired samples t-test Variable to be compared is continuous Interpret p value for statistical significance only Comparing mean difference between 2 or more groups Analysis of Variance (ANOVA) Variable to be compared is continuous Interpret p value for statistical significance only, conduct post-hoc test to identify divergent group
Step 4: Envision finished product ,[object Object],[object Object],[object Object],[object Object],[object Object],Slayter
Step 4: Envision finished product ,[object Object],Slayter Table 1:  Comparison of student engagement rates between class sections Variable: Target section: N=33 Comparison section: N=31 Statistical test result: Self-reported engagement score# Mean =3.5 Mean =2.5 t=2.45*  (Independent samples t-test result) % reporting increased engagement at end of semester 67% 32% OR=3.42**  (Odds ratio test result) Χ 2 =3.46***  (Chi-square test result) # - Likert scale indicates 1=not engaged to 5=totally engaged *** p<.001; **p<.01; *p<.05
Step 4: Envision finished product ,[object Object],[object Object],[object Object],[object Object],Slayter
You are good to go!  ,[object Object],[object Object],[object Object],Slayter

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Slayter on planning quant design for flc projects - may 2011

  • 1.
  • 2.
  • 3.
  • 4.
  • 5. Presentation Overview: How to approach this task Slayter
  • 6.
  • 7. Step 1: Identify project research question, goals, objectives, intervention Slayter Your goal is LINKAGE!!!
  • 8.
  • 9. Step 3: Define analytic task, choose statistical test, example 1 Slayter
  • 10. Step 3: Define analytic task, choose statistical test, example 2 Slayter
  • 11. Step 3: Define analytic task, choose statistical test, example 3 Slayter
  • 12. On choosing statistical tests for bivariate analyses Slayter
  • 13.
  • 14. Link variable type to appropriate statistical test for analytic purpose Slayter
  • 15.
  • 16. Slayter Cheat sheet for choosing bivariate statistics Analytic purpose you are seeking help for: Test name: Basic requirements: How to interpret: Comparing 2 or more groups on a percentage/rate Chi-square test Variable to be compared is nominal Interpret p value for statistical significance only Comparing 2 groups only on a percentage/rate Odds ratio test Variable to be compared is nominal Interpret odds (1.23 times more likely, 0.40 = 60% less likely) Comparing mean difference between 2 groups Independent samples t-test Variable to be compared is continuous Interpret p value for statistical significance only Comparing mean difference between pre and post in one group Paired samples t-test Variable to be compared is continuous Interpret p value for statistical significance only Comparing mean difference between 2 or more groups Analysis of Variance (ANOVA) Variable to be compared is continuous Interpret p value for statistical significance only, conduct post-hoc test to identify divergent group
  • 17.
  • 18.
  • 19.
  • 20.