As participants analyze data, consider the following :

  1. While the discrete data has been collected and provided to you, how would you describe the research objective? You, the statistician get to determine your objective. State it. (Participants may consider data sets containing continuous data, in order to have a variety of possibilities for students.)
  2. Use descriptive statistics to organize the discrete data:
  3. Construct a histogram , stem and leaf plot, dot plot, and /or dot plot
  4. Describe the shape of the data distribution, given your findings
  5. Calculate the three measures of central tendency and explain why which is the best measure of central tendency for this data set
  6. Calculate the three measures of dispersion and describe the one that you feel is most efficient in expressing the “spread” of the data values
  7. Assume the data is bell shaped. Use the Empirical Rule to describe the data set
  8. Using Measures of Position and Outliers:
  9. Select any two data values and calculate their z scores. Describe what these values mean in relation to the data set.
  10. Given the same two data values, calculate and interpret their relative standings (percentiles) within the data set.
  11. Calculate the Five Number Summary
  12. Draw a boxplot and identify outliers
  13. Describe the relation between two variables
  14. Draw a scatter diagram
  15. Calculate and interpret r
  16. Describe any lurking variables
  17. Find the least squares regression line and interpret the slope and y-intercept
  18. Select any two explanatory data values and predict their associated y values. Calculate the residuals as well. Describe what the residuals mean / represent.
  19. Compute and interpret the coefficient of determination
  20. Probability
  21. Using your own creativity, explore and describe disjoint and independent events
  22. Develop a probability experiment using the Classical and Empirical Methods
  23. Solve a probability experiment using the General Multiplication Rule
  24. Solve a probability problem using AT Least Probabilities.
  25. Develop a probability experiment using Conditional Probability
  26. Normality
  27. Assess normality of data
  28. Confidence Intervals
  29. Construct confidence intervals when intervals about a population mean when the population standard deviation is known
  30. Construct confidence intervals when intervals about a population mean when the population standard deviation is unknown
  31. Construct confidence intervals about a population proportion
  32. Hypothesis Testing
  33. For a population mean when the standard deviation is known
  34. For a population mean when the standard deviation is unknown
  35. For a population proportion
  36. Inference about two means when samples are dependent
  37. Inference about two means when samples are independent
  38. Inference about two population proportions
  39. Goodness of Fit Test
  40. Test for Independence and Homogeneity of Proportions