Satyagopal Mandal
Department of Mathematics
University of Kansas
Office: 502 Snow Hall  Phone: 785-864-5180
  • e-mail: mandal@.ku.edu
  • © Copy right Laws Apply, 2001.

    Multimedia Statistics
    Supported by the Faculty Fellowship program, Fall 2001, CTE, University of Kansas

    Illustrations:
    1. Tossing Experiment with a Jayhawk-Wildcat coin.
    Probability Density Functions:
    1. Bell Shape Curve
    2. Normal- graph
    3. t-Distribution - graph
    4. Chi-Square - graph
    Probability Computation :
    1. Normal - Probability
    2. Standard Normal
    3. Example 10 : Solution
    4. Example 11 : Solution
    5. t-Distribution - Probability
    6. Chi-Square - Probability
    7. Exponential - Probability
    Inverse Probability Computation :
    1. Inverse Standard Normal Distribution
    2. Inverse t-Distribution
    3. Inverse Chi-Square - Distribution
    Chapter 1: Basic Language
    1. Example 1 : Solution
    2. Example 2 : Solution
    3. Example 3 : Solution
    4. Example 4 : Solution
    Chapter 2: Measure of central tendency
    1. Example 1 : Solution
    2. Example 2 : Solution
    3. Example 3 : Solution
    4. Example 4 : Solution
    5. Example 6 : Solution
    6. Example 7 : Solution
    7. Example 8 : Solution
    8. Example 9 : Solution
    9. Example 11 : Solution
    10. Example 12 : Solution
    11. Example 13 : Solution
    12. Example 14 : Solution
    13. Example 16 : Solution
    14. Example 17 : Solution
    15. Example 18 : Solution
    16. Example 19 : Solution
    Chapter 3: Probability
    1. Example 1 : Solution
    2. Example 2 : Solution
    3. Example 3 : Solution
    4. Example 4 : Solution
    5. Example 5 : Solution
    6. Example 6 : Solution
    7. Example 7 : Solution
    8. Example 8 : Solution
    9. Example 9 : Solution
    10. Example 10 : Solution
    11. Example 11 : Solution
    12. Example 12 : Solution
    13. Example 13 : Solution
    14. Example 14 : Solution
    15. Example 15 : Solution
    16. Example 15 : Solution
    17. Example 16 : Solution
    18. Example 17 : Solution
    19. Example 18 : Solution
    20. Example 19 : Solution
    21. Example 20 : Solution
    22. Example 21 : Solution
    23. Example 22 : Solution
    24. Example 23 : Solution
    Chapter 4: Random variables
    1. Example 1 : Solution
    2. Example 2 : Solution
    3. Example 3 : Solution
    4. Example 4 : Solution
    5. Example 6 : Solution
    6. Example 7 : Solution
    7. Example 8 : Solution
    8. Example 9 : Solution
    Chapter 5: Continuous random variables
    1. Example 1 : Solution
    2. Example 2 : Solution
    3. Example 3 : Solution
    4. Example 4 : Solution
    5. Example 5 : Solution
    6. Example 6 : Solution
    7. Example 7 : Solution
    8. Example 8 : Solution
    9. Example 9 : Solution
      Cut Off points
    10. Example 10 : Solution
    11. Example 11 : Solution
    12. Example 12 : Solution
    13. Example 13 : Solution
      Normal aproximation to binomial
    14. Example 14 : Solution
    15. Example 15 : Solution
    16. Example 16 : Solution
    17. Example 17 : Solution
    18. Example 18 : Solution
    19. Example 19 : Solution
    20. Example 20 : Solution
    21. Example 21 : Solution
    22. Example 22 : Solution
    23. Example 23 : Solution
    Chapter 6: Sampling distribution
    1. Example 1 : Solution
    2. Example 2 : Solution
    3. Example 3 : Solution
    4. Example 4 : Solution
    5. Example 5 : Solution
    Chapter 7: Estimation
      Section 1 : Z-interval for mean
    1. Example 1 : Solution
    2. Example 2 : Solution
    3. Example 3 : Solution
    4. Example 4 : Solution
    5. Example 5 : Solution
      Section 2 : t-interval for mean
    6. Example 6 : Solution
    7. Example 7 : Solution
    8. Example 8 : Solution
    9. Example 9 : Solution
    10. Example 10 : Solution
    11. Example 11 : Solution
      Section 3: Confidence interval for variance
    12. Example 12 : Solution
    13. Example 13 : Solution
    14. Example 14 : Solution
      Section 4: Confidence interval for p
    15. Example 15 : Solution
    16. Example 16 : Solution
    17. Example 17 : Solution
    18. Example 18 : Solution
    19. Example 19 : Solution
    Chapter 8: Compare two populations
      Section 1 : Z-interval for difference of mean
    1. Example 1 : Solution
    2. Example 2 : Solution
    3. Example 3 : Solution
      Section 2:t-interval for difference of means
    4. Example 1 : Solution
    5. Example 2 : Solution
    6. Example 3 : Solution
    7. Example 4 : Solution
      Section 3 : Confidence Interval for difference of proportions
    8. Example 1 : Solution
    9. Example 2 : Solution
    10. Example 3 : Solution

    Chapter 9: Hypothesis Testing

      Section 2 : Z-Test for mean
    1. Example 1 : Solution
    2. Example 2 : Solution
    3. Example 3 : Solution
      Section 3 : t-Test for mean
    4. Example 4 : Solution
    5. Example 5 : Solution
    6. Example 6 : Solution
    7. Example 7 : Solution
    8. Example 8 : Solution
      Section 4: Testing hypotheses for variance
    9. Example 9 : Solution
    10. Example 10 : Solution
    11. Example 11 : Solution
      Section 5: 1-Proportion Z-test for p
    12. Example 12 : Solution
    13. Example 13 : Solution
    14. Example 14 : Solution
    15. Example 15 : Solution
      Section 6 : Z-Test for difference of mean
    16. Example 16 : Solution
    17. Example 17 : Solution
    18. Example 18 : Solution
      Section 7:t-interval for difference of means
    19. Example 19 : Solution
    20. Example 20 : Solution
    21. Example 21 : Solution
    22. Example 22 : Solution
      Section 9 : Z-Test for difference of proportions
    23. Example 23 : Solution
    24. Example 24 : Solution
    25. Example 25 : Solution