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# Data Analysis Presentation

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• 1. Data Analysis RWJF || GRC
• 2. Available SoftwareQuantitative R SPSS STATAQualitative NVivo Atlas.ti
• 3. The Big ProblemHow do you ask a question that a computer can answer?
• 4. Asking the right questionAre you looking for descriptive statistics?Are you looking for confirmation/refutation of a hypothesis?
• 5. Asking the right questionDescriptive statistics are perhaps theeasiest to structure. Quantitative: Central tendency, quartiles, data range Qualitative: Frequent words, reoccurring themes
• 6. Asking the right questionHypothesis testing requiresadditional steps Formulate hypothesis prior to test, have a clear null and alternative established
• 7. Asking the right questionH0: There is no difference/relationshipHa: There is a difference/relationship
• 8. Asking the right questionQuantitative Regression Is there a relationship between variable X and Y?
• 9. Asking the right questionQuantitative Difference Is there a difference between variable X and Y?
• 10. Asking the right questionMany problems with any kind of data analysis software stem fromimpossible to answer questions.
• 11. Simplify QuestionsBreak your question down to individual steps, as small as you cango.
• 12. Simplify Questions“I need to test the GPA of students who scored below a 26 on theACT vs. those who scored above.”
• 13. Simplify QuestionsTo answer this question, you need a software function that canorder the data, split it, and test the variables you need.It can be hard to find one program that does all that - but it can beeasier if you break the problem up into its components.
• 14. Simplify Questions“I need to test the GPA of studentswho scored below a 26 on the ACTvs. those who scored above.”• Break the question down into individual steps: 1. Sort the data by lowest to highest ACT 2. Divide into ACT scores below 26 and scores above 3. Run a two-sample T-test on the GPA’s from each group.
• 15. Simplify QuestionsData analysis is a lot easier when each step is made smaller.
• 16. Choosing your SoftwareQuantitative R Pros: Most flexibility, free, customized software Cons: Very difficult to learn
• 17. Choosing your SoftwareQuantitative SPSS Pros: User friendly, frequently used, allows for infinite cases, has drop-down commands. Cons: Expensive, can be difficult to interpret results.
• 18. Choosing your SoftwareQuantitative STATA Pros: Allows for syntax-based do-files that create consistent change tracking Cons: Expensive, can be difficult use
• 19. Choosing your SoftwareQuantitative Excel Pros: Ubiquitous, somewhat smaller learning curve Cons: Fundamental limitations in formulas
• 20. Choosing your SoftwareQualitative NVivo Pros: Can structure qualitative data Cons: Expensive, can be difficult use
• 21. Choosing your SoftwareQualitative ATLAS.ti Pros: Can structure qualitative data Cons: Expensive, can be difficult use
• 22. Moving towards your resultsResearch oftentimes can be broken down into two distinct kinds: Quantitative – Confirms (Deductive) Qualitative – Exploratory (Inductive)In reality, this differentiation is not concrete.
• 23. Where does software fit in?QuantitativeTheory Hypothesis Test (Software) Conclusion
• 24. Where does software fit in?Qualitative Data Analysis (Software) Patterns/Theory Conclusion