Engineering Mathematics-II (BSC-201)
Program: B.Tech Computer Science and Engineering (Artificial Intelligence and Machine Learning)
Category: Basic Science Course
Semester: 2
Credits: 5
L-T-P: 3- 2- 0
Description
Instructor

Dr. Ashish Kumar

Assistant Professor
Department Of Applied Sciences
Course Outcomes
  • To understand probability and random variables and various discrete and continuous probability distributionsand their properties
  • Calculate probabilities, and derive the marginal and conditional distributions of bivariate random variables
  • Analyse statistical data using measures of central tendency, dispersion and location
  • Understand and discuss the issues surrounding sampling and significance
  • Develop analytical skills in structuring and interpreting the business problems statistically
Resources
Course Handout Lesson Plan Syllabus
Evaluation Scheme
Sessional_1 10
Assignment 20
Sessional_2 10
Attendance 10
Total Internal 50
Total External 100
Overall Total 150
Course Materials

Unit 1

Theory of Computation
Axioms of Probability
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Bernoulli trials
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Binomial distribution
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Conditional probability
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Discrete random variables
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Expectation, Variance and moments of discrete random variables
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Joint and Marginal distribution of discrete random variables
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Multinomial distribution
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Poisson distribution
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Probability mass function
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Probability spaces
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Unit 2

Theory of Computation
Chebyshev's Inequality
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Introduction to Continuous Random Variables
Bayes' theorem
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Bivariate distributions
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Conditional density
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Continuous random variables
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Distribution functions
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Expectation of continuous random variables
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Exponential distribution
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Gamma distribution
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Marginal density
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Normal distribution
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Probability density functions
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Variance of continuous random variables
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Unit 3

Correlaion & Regression
Central tendency
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Coefficient of regression
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Correlation coefficients
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Kurtosis and Coefficient of kurtosis
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Lines of regression
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Mean, median, and mode
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Measures of dispersion
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Quartile deviation
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Rank correlation methods
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Skewness and Karl Pearson's coefficient of skewness
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Unit 4

Statistics-I
Concept of Test Statistic
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Errors in Hypothesis Testing
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Introduction to Statistical Hypothesis
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Null and Alternative Hypotheses
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Paired t-Test
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t-Test for Difference of Means (Independent Samples)
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t-Test for Single Mean
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t-Test: Introduction and Conditions
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Z-Test for Difference of Means
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Z-Test for Single Mean
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Z-Test: Introduction and Conditions
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Unit 5

Statistics-II
Assumptions and Application of F-Test
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Assumptions and Limitations of Chi-Square Test
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Chi-Square Test for Goodness of Fit
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Chi-Square Test for Independence of Attributes
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F-Test for Equality of Two Variances
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Introduction to Chi-Square Test
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Introduction to F-Test
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PPT
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Question Bank
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