Course No.
MSO 201a
Probability and Statistics
2016-17-II Semester
Instructor: Dr. Neeraj Misra
FB 515, Department of Mathematics & Statistics
Indian Institute of Technology, Kanpur
Talk: 7087; E-Mail: neeraj@iitk.ac.in
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Module 1
COURSE DETAILS
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Course Details
• This course will be conducted in Flipped Classroom mode.
• Release of Video Lectures: Every Friday evening between three to seven
videos will be released.
• Total duration (per week) of these videos will be between 90-100 minutes
(each video will be of about 10 to 35 minutes duration).
• You are expected to watch these videos at your convenience and come for
discussions in flipped classrooms.
• Flipped classroom: Venue: L7; Days: Mondays; Time 08:00-08:50 Hrs
• Discussion Hour: Venue: L7; Days: Fridays; Time 08:00-08:50 Hrs
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Tutorials
• On Wednesdays; Time: 08:00-08:50 Hrs.
• Whole class is divided into five sections. Each section will be handled by a different
tutor.
• Section 1: Roll numbers 10001-150119; Section 2: Roll Numbers 150120-150368;
• Section 3: Roll Numbers 150369-150596; Section 4: Roll Numbers 150597-151100;
• Venue of tutorials and names of tutors will be announced in course portal.
• Office Hours (if any): To be announced by respective tutors.
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Weightages
• Mid-Semester Examination of 2 Hour Duration (pen and
paper): On 27-02-17 (Mon), carrying 24% weightage;
• End-Semester Examination of 3 Hour Duration (pen and
paper): On 24-04-17 (Mon), carrying 40% weightage;
• Two classroom quizzes of 30 minutes each (pen and paper):
On 04-02-17 (Sat) and 08-04-17 (Sat), each carrying a
weightage of 10%;
• Four online quizzes of 20 minutes each: On 21-01-17 (Sat),
18-02-17 (Sat), 25-03-17 (Sat) and 15-04-17 (Sat)), each
carrying a weightage of 4%.
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Academic Performance Evaluation Scheme
Although the policy of relative grading will be followed for awarding the final
grades, there is a minimum performance requirement for each grade. These
minimum performance requirements are given below:
• A* Grade: 85% Marks
• A Grade: 70% Marks
• B Grade: 55% Marks
• C Grade: 40% Marks
• D Grade: 30% Marks
• E Grade: 20% Marks
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Attendance Policy & Code of Conduct
You are expected to:
• watch the video lectures on regular basis;
• attend all sessions (flipped classrooms, tutorials,
examinations, quizzes) of the course;
• maintain proper decorum and discipline during
flipped classrooms, tutorials and examinations.
Any act of misconduct will be dealt severely.
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Makeup Examination Policy
• Mid-semester examination and quizzes:
Except for serious exigencies (such as
hospitalization during the examination), there
will be no makeup examination.
• End-semester examination:
As per the policy of the institute.
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Text Book
• Introduction to Mathematical Statistics,
Seventh Edition, by Robert V. Hogg, J. W.
McKean, and Allen T. Craig, Pearson
Education, Asia.
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Course Content
• Probability:
Axiomatic definition, Properties, Conditional probability, Bayes rule
and independence of events, Random Variables, Distribution
function, Probability mass and density functions, Expectation,
Moments, Moment generating function, Chebyshev's inequality;
Special distributions: Bernoulli, Binomial, Geometric, Negative
binomial, Hypergeometric, Poisson, Uniform, Exponential, gamma;
Joint distributions, Marginal and conditional distributions,
Moments, Independence of random variables, Covariance,
Correlation, Functions of random variables, Weak law of large
numbers, P Levy's Central limit theorem (IID, finite variance cast),
Normal and Poisson approximations to Binomial.
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• Statistics:
Introduction: Population, sample, parameters;
Point Estimation: Method of moments, MLE, Unbiasedness, Consistency,
Comparing two estimators (relative MSE), Confidence interval estimation
for mean, difference of means, variance, proportions, Sample size problem;
Tests of Hypotheses: N-P lemma, examples of MP and UMP tests, p-value.
Likelihood ratio test, Tests for mean, variance, two sample problems, Tests
for proportions, Relation between confidence interval and tests of
hypotheses. Chi-square goodness of fit tests, Contingency table; SPRT;
Regression Problem; Scatter diagram, Simple linear regression, Least
square estimation, tests for slope and correlation, prediction problem,
Graphical residual analysis, Q-Q plot to test for normality of residuals,
Multiple regression; Analysis of Variance: Completely randomized design
and randomized block design; Quality Control, Shewhart control charts and
cusum charts.
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Abstract of Next Module
• Introduction to probability and Statistics and
their interrelations.
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Thank you for your patience
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