JNTUK R19 2-2 Probability and Statistics Material PDF Download

JNTUK R19 2-2 Probability and Statistics Material PDF Download

Students those who are studying JNTUK R19 CSE Branch, Can Download Unit wise R19 2-2 Probability and Statistics Material/Notes PDFs below.

JNTUK R19 2-2 Probability and Statistics Material PDF Download

OBJECTIVES:

• To familiarize the students with the foundations of probability and statistical methods
• To impart probability concepts and statistical methods in various applications Engineering

UNIT-1

Descriptive statistics and methods for data science: Data science – Statistics Introduction – Population vs Sample – Collection of data – primary and secondary data – Type of variable: dependent and independent Categorical and Continuous variables – Data visualization – Measures of Central tendency – Measures of Variability (spread or variance) – Skewness Kurtosis.

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UNIT-2

Correlation and Curve fitting: Correlation – correlation coefficient – rank correlation – regression coefficients and properties – regression lines – Method of least squares – Straight line – parabola – Exponential – Power curves.

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UNIT-3

Probability and Distributions: Probability – Conditional probability and Baye’s theorem – Random variables – Discrete and Continuous random variables – Distribution function – Mathematical Expectation and Variance – Binomial, Poisson, Uniform and Normal distributions.

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UNIT-4

Sampling Theory: Introduction – Population and samples – Sampling distribution of Means and Variance (definition only) – Central limit theorem (without proof) – Introduction to t, 2 and Fdistributions – Point and Interval estimations – Maximum error of estimate.

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UNIT-5

Tests of Hypothesis: Introduction – Hypothesis – Null and Alternative Hypothesis – Type I and Type II errors – Level of significance – One tail and two-tail tests – Tests concerning one mean and two means (Large and Small samples) – Tests on proportions.

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TEXT BOOKS:

1. Miller and Freund’s, Probability and Statistics for Engineers,7/e, Pearson, 2008.
2. S. C. Gupta and V.K. Kapoor, Fundamentals of Mathematical Statistics, 11/e, Sultan Chand & Sons Publications, 2012.

REFERENCE BOOKS:

1. Shron L. Myers, Keying Ye, Ronald E Walpole, Probability and Statistics Engineers and the Scientists,8th Edition, Pearson 2007.
2. Jay l. Devore, Probability and Statistics for Engineering and the Sciences, 8th Edition, Cengage.
3. Sheldon M. Ross, Introduction to probability and statistics Engineers and the Scientists, 4th Edition, Academic Foundation, 2011.
4. Johannes Ledolter and Robert V. Hogg, Applied statistics for Engineers and Physical Scientists, 3rd Edition, Pearson, 2010.

OUTCOMES:

• Classify the concepts of data science and its importance (L4) or (L2)
• Interpret the association of characteristics and through correlation and regression tools (L4)
• Make use of the concepts of probability and their applications (L3)
• Apply discrete and continuous probability distributions (L3)
• Design the components of a classical hypothesis test (L6)
• Infer the statistical inferential methods based on small and large sampling tests (L4)