AD-302 Probability and Statistics for Data Science Notes
5 notes for Probability and Statistics for Data Science, unit by unit.
Notes for AD-302
- Unit 1 · Short notes Data Science and Statistics Fundamentals Data Science: Introduction and Data Science Life Cycle · Statistics: Descriptive and Inferential Statistics · Measures of central tendency: Arithmetic Mean, Median, Mode, Geometric Mean, Harmonic Mean, Partition values · Measures of dispersion: Range, Quartile Deviation, Mean deviation, Standard Deviation, Variance, Coefficient of Dispersion
- Unit 2 · Short notes Probability Theory and Distribution Shape Measures Skewness, Kurtosis, Moments; measures of skewness and kurtosis · Theory of probability: definition of probability, events, sample space, laws of addition and multiplication, conditional probability · Independent and dependent events, Bayes’ theorem, mathematical expectations, moment generating functions
- Unit 3 · Short notes Theoretical Distributions and Curve Fitting Discrete distributions: Binomial distribution and Poisson distribution · Continuous distributions: Rectangular (uniform) distribution and Normal distribution · Curve fitting: Methods of least squares, fitting a straight line and a parabola
- Unit 4 · Short notes Correlation and Regression Analysis Correlation: Pearson correlation coefficient, rank correlation, lines of regression · Multiple and partial correlation
- Unit 5 · Short notes Hypothesis Testing and Significance Tests Testing of hypothesis: null and alternative hypotheses, Type I and Type II errors, level of significance, power of the test · Tests of significance: chi‑square distribution, tests of variance and goodness‑of‑fit, t‑distribution, F‑distribution, Z‑distribution and related tests
More for AD-302
Other 3rd semester AD subjects
- AD-301 Technical Communication
- AD-303 Data Structures
- AD-304 Artificial Intelligence
- AD-305 Object Oriented Programming & Methodology
- AD-306 Computer Workshop/Introduction to Python-I