C3OIT PROBABILITY AND STATISTICS 2007 admission Syllabus Third Semester

 C3OIT PROBABILITY AND STATISTICS  ( 2007 admission Syllabus ) Third Semester
Module 1 (21 hrs)
Basic statistical concepts, Types of variables, population and sample, Parameter and statistic, Census versus sampling, Methods of sampling- Random and non random sampling methods.
Frequency distributions- measures of central tendency, m easui-es of dispersion, morn ents, skeess and kurtosis.
Correlation and Regression analysis- Types of Correlation, Methods of studying simple correlation, properties of correlation coefficient.
Module 2(16 hrs)
Different approaches to probability, conditional probability, Addition and multiplication theorems, Baye’ s theorem, simple problems.
Random variables and probability distribution- discrete and continuous- distribution function and its properties(without proof) Extension to bivariate case (elementary concept only)
Module 3(16 hrs)
Expectation and its properties, Mean, variance and moments in terms of expectation, Moment Generation Function and characteristic function simple problem, Standard distribution and statistical inference.
Standard probability distribution- Binomial, Poisson, Uniform and Normal- mean, variance and M.G.F. — problems relating to practical applications.
Module 4(11 hrs)
Central Limit Theorem (without proof) and its applications, Sampling distributions and standard error(concept only), Distribution of the sample mean, t, X2, and F statistic- definition and properties (without proof)
Estimation- Concept of Point and Interval estimation- Point estimate and its properties Test of signilicance- Elementary ideas and simple problems.
Text Book
Probability and Statistics Schaiini’s outline Series.
References
1. Hogg RN. Craig A.L. , Introduction to Mathematical Statistica, American Publishing Co. Pvt. Ltd.
2. Yulg, U.G., Kendoll, M.G; An Introduction to Theory of Statistics, Chailes Griffin & Co. Ltd
3. Draper N.A.,Srnjtli H,; Applied Regression Analysis, John Wiley & Sons, Inc.
4. S.P. Gupta ,Statistical Methods.
5. William Mendenhall, Robert J Beaver, BarbaraM Beaver, Introduction to Probability and Statistics, Thomson 2007.

PARALLEL PROCESSING Question Paper

 G 9692 

B.Sc. (COMPUTER SCIENCE) DEGREE EXAMINATION, JULY 2013 

Sixth Semester 

PARALLEL PROCESSING 

(2007 and 2008 Admissions—Supplementary) 

Time Three Hours                                                                      Maximum : 75 Marks 

Part A 

Answer any five questions. 

Each question carries 3 marks. 

1. What is a multiprocessor system?
2. Write a note on linear pipelining.
3. What are interconnection networks?
4. What is a multiprocessor operating system?
5. What are data flow graphs?
6. List two applications of parallel processing.

(5 x 3= 15 marks) 

Part B 

Answer any four questions. 

Each question carries 5 marks. 

7. How can you achieve parallelism in uniprocessor systems?
8. Describe the working of instruction pipelines.
9. Explain the structure of multiprocessor system.
10. Discuss the multiprocessor programming.
11. What are the advantages of data flow graphs?
12. Explain the inter process communication in multiprocessor systems.

(4 x 5 = 20 marks) 

Part C 

Answer any two questions. 

Each question carries 20 marks. 

13. Describe Feng’s classification of parallel computers.
14. Explain vector processing with an example.
15. Discuss an algorithm for array processors.
16. Explain the architecture of data flow computers.

[2 x 20 = 40 marks]