Statistics

Statistics labs

1. Lab 01

   What Does One Row Represent?

   Observational units, measurement scales and missing values.

   8 min read

2. Lab 02

   Which Average Answers the Question?

   Mean, median, geometric mean and the influence of a tail.

   10 min read

3. Lab 03

   How Variable Are Delivery Times?

   Sample variance, standard deviation, IQR and rescaling.

   10 min read

4. Lab 04

   Which Denominator Belongs in a Probability?

   Joint, marginal and conditional event frequencies.

   10 min read

5. Lab 05

   What Does a Quality Alert Tell Us?

   Bayes theorem, sensitivity, specificity and base rates.

   10 min read

6. Lab 06

   How Many Orders Arrive in Ten Offers?

   Binomial probabilities, expectation and variance.

   10 min read

7. Lab 07

   From Parcel Weights to Standard Scores

   Normal models, standardization and model versus observed tails.

   10 min read

8. Lab 08

   Why Do Averages Vary Less Than Observations?

   Repeated sampling, standard errors and the CLT.

   10 min read

9. Lab 09

   What Does a Confidence Interval Cover?

   Student-t intervals, coverage and interval width.

   10 min read

10. Lab 10

    Is the Filling Process Centered on Its Target?

    Null hypotheses, t statistics, p values and practical importance.

    10 min read

11. Lab 11

    How Uncertain Is an Opt-In Rate?

    Proportion z tests, Wald and Wilson intervals.

    10 min read

12. Lab 12

    Comparing Two Delivery Methods

    Independent samples, Welch uncertainty and group order.

    11 min read

13. Lab 13

    The Same Workers Before and After

    Pairing, complete pairs and the variance of differences.

    10 min read

14. Lab 14

    Did Two Messages Produce Different Response Rates?

    Pooled null tests, unpooled intervals and percentage points.

    10 min read

15. Lab 15

    Do Study Hours and Scores Move Together?

    Pearson correlation, common samples and noncausal association.

    10 min read

16. Lab 16

    Are Shopping Channels and Membership Independent?

    Expected counts, Pearson chi-square and association size.

    10 min read

17. Lab 17

    Comparing Three Training Formats

    Between/within variation, ANOVA F and adjusted comparisons.

    12 min read

18. Lab 18

    Comparing Ordinal Customer Ratings

    Midranks, ties, rank-sum tests and probability of superiority.

    11 min read

19. Lab 19

    Resampling the Observed Baskets

    Nonparametric bootstrap, Monte Carlo error and percentile intervals.

    11 min read

20. Lab 20

    From a Question to a Statistical Report

    Primary outcomes, missingness, uncertainty and multiple testing.

    12 min read