Regulation: R23 Branch: Information Technology Semester: 2-2

Probability & Statistics

Verified vs. official syllabus Checked 2026-07-01

Subject names, credits, and semester placement are cross-confirmed against JNTUK's own centrally-administered exam records. Detailed unit topics are sourced from an autonomous JNTUK-affiliated college's published syllabus and have not been independently verified against the university's own document -- autonomous colleges may adapt unit-level content locally.

Unit-wise syllabus

UNIT 01

Descriptive Statistics and Methods for Data Science

Data science, statistics introduction, population vs sample, collection of data, primary and secondary data; Types of variable: dependent and independent, categorical and continuous variables; Data visualization; Measures of central tendency, measures of variability, skewness, kurtosis

UNIT 02

Correlation and Regression

Correlation: correlation coefficient, rank correlation; Linear regression: straight line, multiple linear regression; Regression coefficients and properties; Curvilinear regression: parabola, exponential and power curves

UNIT 03

Probability and Distributions

Introduction of probability, addition theorem, conditional probability, Baye's theorem; Random variables: discrete and continuous; Distribution functions: probability mass function, probability density function, cumulative distribution functions; expectation and variance; Binomial, Poisson, uniform and normal distributions

UNIT 04

Sampling Theory

Introduction, population and samples; Sampling distribution of means and variance; Point and interval estimations, maximum error of estimate; Central limit theorem (without proof), estimation using t-test

UNIT 05

Test of Hypothesis

Introduction, hypothesis, null and alternative hypothesis, errors in sampling, level of significance, one-tail and two-tail tests; Test of significance for large samples and small samples; Single and two means, single and two proportions; Student's t-test, F-test, chi-square test