Statistics II (STA215) — Notes, Syllabus & Past Questions

Inferential statistics, regression analysis, and hypothesis testing for data science.

Core Course6 Chapters
Chapter 111 Pages

Sampling Distribution and Estimation

Sampling distribution, sampling distribution of mean and proportion, Central Limit Theorem, Concept of inferential Statistics, Estimation, Methods of estimation, Properties of good estimator.

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Chapter 225 Pages

Testing of hypothesis

Types of statistical hypotheses, Power of the test, concept of p-value and use of p -value in decision making, steps used in testing of hypothesis.

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Chapter 342 Pages

Non parametric test

Parametric vs. non-parametric test, Needs of applying non-parametric tests, One-sample test: Run test, Binomial test, Kolmogorov-Smirnov test, Two independent sample test: Median test.

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Chapter 419 Pages

Multiple correlation and regression

Multiple and partial correlation, Introduction of multiple linear regression, Hypothesis testing of multiple regression, Test of significance of regression, Test of individual regression coefficient.

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Chapter 525 Pages

Design of experiment

Experimental design, Basic principles of experimental designs, Completely Randomized Design (CRD), Randomized Block Design (RBD), ANOVA table, Efficiency of RBD relative to CRD.

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Chapter 616 Pages

Stochastic Process

Definition and classification, Markov Process: Markov chain, Matrix approach, SteadyState distribution, Counting process: Binomial process, Poisson process, Simulation of stochastic process.

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Related Study Resources for Statistics II (STA215)

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