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Normality tests P RACTICIN G S TATIS TICS IN TERVIEW QUES TION S IN R Zuzanna Chmielewska Actuary PRACTICING STATISTICS INTERVIEW QUESTIONS IN R Testing normality Statistical tests Shapiro-Wilk test Kolmogorov-Smirnov test Visual


  1. Normality tests P RACTICIN G S TATIS TICS IN TERVIEW QUES TION S IN R Zuzanna Chmielewska Actuary

  2. PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  3. Testing normality Statistical tests Shapiro-Wilk test Kolmogorov-Smirnov test Visual measure Q-Q plot PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  4. Shapiro-Wilk test PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  5. Shapiro-Wilk test 1 Razali, Nornadiah; Wah, Yap Bee (2011). "Power comparisons of Shapiro–Wilk, Kolmogorov–Smirnov, Lilliefors and Anderson–Darling tests" PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  6. P-value PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  7. Shapiro-Wilk test PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  8. Kolmogorov-Smirnov test PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  9. Kolmogorov-Smirnov test PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  10. Kolmogorov-Smirnov test PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

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  15. Transforming data for normality PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  16. Transforming data for normality PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  17. Checking normality in R Method Function Shapiro-Wilk test shapiro.test(x) Kolmogorov-Smirnov test ks.test(x, y = "pnorm") Q-Q plot qqnorm(x); qqline(x) PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  18. Summary normality tests Shapiro-Wilk test Kolmogorov-Smirnov test p-value Q-Q plot data transformation checking normality in R PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  19. Let's practice! P RACTICIN G S TATIS TICS IN TERVIEW QUES TION S IN R

  20. Inference for a mean P RACTICIN G S TATIS TICS IN TERVIEW QUES TION S IN R Zuzanna Chmielewska Actuary

  21. Inference for a mean PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  22. Inference for a mean con�dence interval one-sample mean PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  23. Assumptions The t-test's assumptions: normally distributed underlying data (recall CLT!) random sample independent observations PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  24. Con�dence interval PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  25. Con�dence interval PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  26. Con�dence interval PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  27. Con�dence interval PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  28. 95% con�dence interval PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  29. 95% con�dence interval PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  30. 95% con�dence interval PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  31. 95% con�dence interval PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  32. One-sample t-test H : μ = μ 0 0 H : μ ≠ μ 1 0 where: μ - the population's mean μ - the hypothesized mean 0 PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  33. t-test in R t.test(x) PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  34. t-test in R t.test(x) PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  35. t-test in R t.test(x) PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  36. t-test in R t.test(x, mu = 2) PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  37. t-test in R t.test(x, mu = 2, conf.level = 0.9) PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  38. Summary t-test's assumptions con�dence interval one-sample t-test t.test() in R PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  39. Let's practice! P RACTICIN G S TATIS TICS IN TERVIEW QUES TION S IN R

  40. Comparing two means P RACTICIN G S TATIS TICS IN TERVIEW QUES TION S IN R Zuzanna Chmielewska Actuary

  41. Comparing two means PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  42. Hypotheses Two-tailed test: H : μ = μ 0 1 2 H : μ ≠ μ 1 1 2 where: μ - the �rst population's mean 1 μ - the second population's mean 2 PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  43. Assumptions The two-sample t-test's assumptions: normally distributed underlying data random samples independent observations homogeneity of variances PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  44. Assumptions The two-sample t-test's assumptions: normally distributed underlying data random sample independent observations homogeneity of variances - e.g. bartlett.test() PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  45. Teaching methods PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  46. Teaching methods PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  47. Teaching methods PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  48. Teaching methods PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  49. Teaching methods PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  50. Teaching methods PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  51. Teaching methods PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  52. Teaching methods PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  53. Teaching methods PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  54. Teaching methods PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  55. PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  56. PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  57. PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  58. PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  59. PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  60. t-test in R Two-sample t-test t.test(value ~ group, data = df, var.equal = TRUE) PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  61. t-test in R Two-sample t-test t.test(value ~ group, data = df, var.equal = TRUE) Paired t-test t.test(value ~ group, data = df, paired = TRUE) PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  62. Summary two-sample t-test hypotheses assumptions paired t-test t.test() in R PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  63. Let's practice! P RACTICIN G S TATIS TICS IN TERVIEW QUES TION S IN R

  64. ANOVA P RACTICIN G S TATIS TICS IN TERVIEW QUES TION S IN R Zuzanna Chmielewska Actuary

  65. PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  66. Hypotheses H : μ = μ = ... = μ 0 1 2 n H : ∃ μ ≠ μ 1 ( i , j ) i j PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  67. Hypotheses H : μ = μ = μ 0 1 2 3 PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  68. Hypotheses Two-sample t-test: H : μ = μ 0 1 2 PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  69. Hypotheses H : μ = μ = ... = μ 0 1 2 n PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

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  73. PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  74. Why not multiple t-tests? PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  75. Why not multiple t-tests? PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  76. Why not multiple t-tests? PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  77. Why not multiple t-tests? PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  78. Why not multiple t-tests? PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  79. Assumptions independence of cases normal distributions homogeneity of variances PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  80. ANOVA in R oneway.test(value ~ group, data, var.equal = TRUE) PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  81. Box plot PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  82. Box plot PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  83. Box plot PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  84. Box plot PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  85. Box plot PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  86. Box plot PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  87. Box plot PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  88. Summary hypotheses of ANOVA type I and II errors assumptions of ANOVA oneway.test() in R box plot PRACTICING STATISTICS INTERVIEW QUESTIONS IN R

  89. Let's practice! P RACTICIN G S TATIS TICS IN TERVIEW QUES TION S IN R

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