Sathyabama Institute of Science and Technology M.Sc - Bioinformatics and Datascience SMT5104 Biostatistics Syllabus

[KunwarR]

Sathyabama Institute of Science and Technology M.Sc - Bioinformatics and Datascience SMT5104 Biostatistics Syllabus

SATHYABAMA INSTITUTE OF SCIENCE AND TECHNOLOGY SCHOOL OF BIO AND CHEMICAL ENGINEERING

SMT5104 BIOSTATISTICS
L T P CREDITS
TOTAL
MARKS
3 0 0 3 100

UNITI
DESCRIPTIVE STATISTICS 9 Hrs. Collection,
Classification and Tabulation of data, Bar diagrams and Pie diagrams, Histogram, Frequency curve and frequency polygon,
Ogives. Mean, median, mode, Standard deviation.

UNIT II CURVE FITTING & CORRELATION AND REGRESSION 9 Hrs. Fitting a straight line and
second degree parabola by Least Squares. Correlation – Scatter diagram – Limits of correlation coefficient – Spearman’s
Rank correlation coefficient – Simple problems – Regression – Properties of Regression coefficients and regression lines.

UNIT III PROBABILITY THEORY & RANDOM VARIABLES 9 Hrs. Probability
theory, Random experiments, Sample Space, Conditional Probability, Baye’s theorem, Random variable, (discrete and
continuous), Probability density function (discrete and continuous), Distribution function (discrete and continuous random
variable).

UNIT IV STANDARD DISTRIBUTION 9 Hrs. Binomial
distribution, Poisson distribution, Geometric Distribution, Uniform distribution, Exponential distribution, Normal distributions.

UNIT V TIME SERIES 9 Hrs.
Component of time series – Measurement of trend – Graphical Method – Semi average method - Moving average method –
Measurement of seasonal variation – Method of simple average method – Ratio Moving average method .

COURSE OUTCOMES:
On completion of the course the student will be able to
CO1: Identify, classify and tabulate the data. Construct various frequency charts. Evaluate the various measures of central
tendency and measures of variation.
CO2 :Evaluate the Karl Pearson’s correlation coefficient, Spearman’s correlation coefficient and Regression Equations.
Explore the relationship between correlation and regression. Fitting of straight line by least squares.
CO3: Understand the basic concepts of probability and enable the students to apply Baye’s theorem using conditional
probability.
CO4: Explain the standard discrete and continuous distributions and enable the students to use these distributions to solve
real time problems.
CO5: It empathizes the students about the importance of Time series and methods of Time series.
CO6 :Explore the various problems involving probability and to evaluate real time problems using the concepts of probability

TEXT / REFERENCE BOOKS
1. David S. Moore, George P. McCabe, Bruce A. Craig. Introduction to the practice of statistics, 7th edition, W.H. Freeman
and Company, New York 2011.
2. PSS Sunder Rao and J. Richard, An introduction to Biostatistics and Research Methods, 5th edition PHI Learning Private
Ltd, New Delhi, 2012.
3. P. R. Vittal, Mathematical Statistics, Margham Publications, Chennai, 2002.
4. J. N. Kapur and H. C. Saxena, Treatment and Content as in Mathematical Statistics, 20th Edition, S. Chand & Co. Ltd.,
New Delhi, 2010.
5. Hogg, R.V. & Craig. A. T., Introduction to Mathematical Statistics, Macmillan, 1998.

END SEMESTER EXAM QUESTION PAPER PATTERN
Max. Marks : 100 Exam Duration : 3 Hrs.
PART A : 6 Questions for 5 Marks each –without choice 30 Marks
PART B : 2 Questions from each unit with internal choice, each carrying 14 marks 70 Marks