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Descriptive Statistics

Yuvaraja's College , CEC via Swayam

Description

The course content starts with initial exploration of data, data types, frequency distribution, verity of graphical and diagrammatic representation of data, Graphical summery, purpose and explanation of the distribution of the data, various measures of central tendency, various measures of dispersion, moments, skewness and kurtosis, curve fitting, scatter diagram, correlation and regression, rank correlation, multiple and partial correlation and regression, and coefficient of determination

Electrical Engineering

Syllabus

Week 1:
1. Types of Statistical Data/
2. Primary Data/
3. Secondary Data/
4. Frequency Distribution/

Week 2:
5. Diagrammatic and Grouped data/
6. Stem and Leaf plot/
7. Box Plot/
8. Concept of Central Tendency/

Week 3:
9. Arithmetic Mean/
10. Geometric Mean/
11. Harmonic Mean/
12. Median and Mode/

Week 4:
13. Arithmetic Mean, Weighted Mean, Trimmed Mean, Corrected Mean-Part-1/
14. Arithmetic Mean, Weighted Mean, Trimmed Mean, Corrected Mean-Part-2/
15. Mode, Median and Partition values (Part I)/
16. Mode, Median and Partition values (Part II)

Week 5:
17. Measures of Dispersion/
18. Concept of variation and dispersion/
19. Absolute and Relative Measure of Dispersion (Part-1)/
20. Absolute and relative measures of dispersion (Part -2)

Week 6:
21. Moments/
22. Skewness and Kurtosis and their measures/
23. Problems on Moments, Skewness & Kurtosis

Week 7:
24. Problems on association of attributes/
25. Fitting of curves by least square method/
26. Fitting of Linear curve

Week 8:
27. Fitting of Parabolic curves/
28. Fitting of Exponential curve/
29. Fitting of Geometric Curves

Week 9:
30. Scatter diagram/
31. Product Moment correlation coefficient and its properties/
32. Practical- Problems on product moment correlation co-efficient

Week 10:
33. Rank correlation/
34. Practicals on rank correlation coefficient/
35. Fitting of Linear Regression and Related Results

Week 11:
36. Practicals : Problems on regression of two variables/
37. Multiple correlation and regression in three variables/
38. Measures and related results of multiple and partial correlation and regression in three variables

Week 12:
39. Partial correlation and regression in three variables/
40. Practicals on partial & multiple correlation & regression/
41. Co-efficient of determination