AD-302 · Probability and Statistics for Data Science/Official Syllabus
Probability and Statistics for Data Science (AD-302) - Official Syllabus
1
Unit 1
Data Science & Statistics Basics
- Data Science: Introduction
- Data Science Life Cycle
- Statistics: Descriptive and Inferential Statistics
- Measures of central tendency: Arithmetic Mean, Median and Mode
- Geometric mean
- Harmonic Mean
- Partition values
- Measures of dispersion: Dispersion, Range
- Quartile Deviation
- Mean deviation
- Standard Deviation
- Variance
- Coefficient of Dispersion
2
Unit 2
Moments and Theory of Probability
- Skewness
- Kurtosis
- Moments
- Measure of skewness and kurtosis
- Theory of probability: Introduction and definition of Probability
- Event
- Sample Space
- Law of addition and multiplication of Probabilities
- Conditional Probability
- Independent and Dependent events
- Bayes’ theorem
- Mathematical Expectations
- Moment generating functions
3
Unit 3
Theoretical Distribution and Curve Fitting
- Theoretical Distribution: Discrete Distribution- Binomial Distribution
- Poisson Distribution
- Continuous Distribution –Rectangular and Normal distribution
- Curve fitting and Methods of Least square
- fitting a Straight line and a Parabola
4
Unit 4
Correlation and Regression
- Correlation
- Coefficient of Correlation
- Rank Correlation
- Lines of Regression
- Multiple and Partial Correlation
5
Unit 5
Testing of Hypothesis and Tests of Significance
- Testing of hypothesis: Null and Alternative hypothesis
- two types of errors
- level of significance and power of the test
- Tests of significance: Chi-square distribution
- test of popular variance and test of goodness of fit
- t, F ,Z distribution and tests based on them
Reference Books
- Fundamentals of Mathematical Statistics — D.N. Elhance — Kitab Mahal, Allahabad
- An outline of Statistical theory, Vol. I — A.M. Goon, M.K. Gupta, B. Dasgupta — World Press — 6th revised edition
- Fundamentals of Mathematical Statistics — S.C. Gupta, V.K. Kapoor — Sultan Chand — 10th Edition
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