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Best Practices for Statistics: Enhancing Research and Data Analysis

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keaton
68 diapositives · 844 Views · Aug 14, 2014

Improve your statistical skills with best practices in research questions, data collection, analysis methods, and data presentation. Learn about variables, measures, data plans, exploratory data analysis, spread of data, and transformation techniques.

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  1. Best Practices for Statistics

  2. Best Practices

  3. Purpose of Statistics

  4. Best Practice:Know what you already know, what you want to know and what you don’t know

  5. Starting with Your Research Question How do users differ when (searching, finding, selecting) (articles, books, Web sites)? What are factors associated with ___________? What are the effects of ___________On ____________? Which is better at improving _________? How are people (finding, selecting, using) _______?

  6. Kinds of Variables

  7. Levels of Measurement (NOIR)

  8. Another Way

  9. Likert-Type Scale?

  10. Best Practice:Have a Comparison Group

  11. Ways of comparing…

  12. Kinds of Comparison

  13. Best Practice: Use a Valid Measure

  14. Validity of Measures Are you actually measuring what you are trying to measure?

  15. Use a tool with established validity User Engagement Scale (UES) Approaches and Study Skills Inventory for Students (ASSIST)

  16. Establish Validity of Measures

  17. Best Practice: Have a Data Plan

  18. Goal of Data Collection in Statistics

  19. Bias Systematic (not random) deviation from the true value (Statistics.com)

  20. Data Input Have a data entry plan Train the inputters Use data validation tricks Double-entry

  21. Best Practice:Get to know your data

  22. Exploratory Data Analysis

  23. Measures of Central Tendency

  24. Spread & Distribution

  25. Distribution or Spread of Qualitative Data

  26. Pivot Tables in Excel

  27. Demonstration of Pivot Tables for Spread of Qualitative Data

  28. Graph & Chart Rules of Thumb

  29. Quantitative Distributions

  30. Exploratory Data Analysis • John W. Tukey • Exploratory Data Analysis • Examining your data visually. • Stem & Leaf • Hinges • Box plots • Scatter plots, etc.

  31. Stem-and-Leaf First digit(s) Last digit

  32. From Stem-and-Leaf to Histograms

  33. Histograms in Excel

  34. Demonstration of Histogram in Excel

  35. Spread of Quantitative Data How variable is the data?

  36. Range & Quartiles

  37. Presentation of Spread • Box plots • Median • Upper & lower quartiles • Outliers

  38. Standard Deviation • Measure of dispersion of data • Square root of the average variation from the mean

  39. What does the SD tell you?

  40. Spread in Excel

  41. Normal Distribution

  42. Skewed Distributions

  43. Demonstration of distributions Distribution of the Population The “Truth” N is the # of samples n is the number of items in each sample Watch the cumulative mean & medians slowly merge to the population

  44. Best Practice:If it doesn’t fit, change it Transformation of data

  45. Why Transform?

  46. How Transformation Works

  47. How to Become Normal • Express the result in the terms of the transformation

  48. Best Practice: Place your bets before you start