Statistics and Probability Question Paper

probability-and-statistics





Statistics and Probability

Subject Code Subject Name Credits
MCA105 Statistics And Probability 04
Subject

Code

Subject Name Teaching

Scheme

Credits

Assigned

Theory Pract Tut Theory TW Tut. Total
MCA105 Statistics And Probability 04 04 04
Subject Code Subject Name Examination Scheme
MCA 105 Statistics And Probability Theory Marks TW Pract Oral Total
Internal Assessment End Semester Exam
Test1 (T1) Test2 (T2) Average of T1 & T2
20 20 20 80 100

 Pre-requisites:

Basic Mathematics, combinatorics and calculus Knowledge.

Course Educational Objectives (CEO):

CEO 1 To equip the students with a working knowledge of probability, statistics, and modeling in the presence of uncertainties.
CEO 2 To understand the concept of hypothesis and significance tests
CEO 3 To help the students to develop an intuition and an interest for random phenomena and to introduce both theoretical issues and applications that may be useful in real life.

Course Outcomes: At the end of the course, the students will be able to:

MCA105.1 Distinguish between quantitative and categorical data
MCA105.2 Apply different statistical measures  on data
MCA105.3 Identify, formulate and solve problems
MCA105.4 Classify different types of Probability and their fundamental applications

Syllabus

Sr. No Module Detailed Contents Hours
1 Measures of Central Tendency &Measures of Dispersion Frequency Distribution, Histogram, Stem and leaf diagram, ogives, Frequency Polygon, Mean, Median, Mode, Range, Quartile Deviation, Mean Deviation, Box whisker plot, Standard Deviation, Coefficient of Variation 8
2 Skewness, Correlation & Regression Karl Pearson‟s coefficient of Skewness, Bowley‟s coefficient of Skewness, Scatter Diagram, Karl Pearson‟s coefficient of correlation, Spearman‟s rank correlation coefficient , Linear Regression and Estimation, Coefficients of regression 8
3 Theory of Attributes Classes and Class Frequencies, Consistency of Data, Independence of Attributes, Association of Attributes 4
4 Testing of Hypothesis Hypothesis, Type I and Type II errors. Tests of significance

– Student’s t-test:Single Mean, Difference of means, paired t-test, Chi-Square test:Test of Goodness of Fit, Independence Test

10
5 Introduction to Probability Random experiment, Sample space, Events, Axiomatic Probability, Algebra of events 4
6 Conditional Probability Conditional Probability, Multiplication theorem of Probability, Independent events, Baye‟s Theorem 6
7 Random variables Discrete random variable, Continuous random variable, Two-dimensional random variable, Joint probability distribution, Stochastic independence 7
8 Mathematical Expectation Expected value of a random variable, Expected value of a function of a random variable,Properties of Expectation and Variance, Covariance 5

 

Reference Books:

 

  1. Fundamentals of Mathematical Statistics – 1st Edition S.C.Gupta, V.K.Kapoor , S Chand
  2. Introduction to Probability & Statistics – 4th Edition J.Susan Milton, Jesse C. Arnold Tata McGraw Hill
  3. Fundamentals of Statistics : 7th edition S C Gupta, Himalaya Publishing house
  4. Probability and Statistics with Reliability, Queuing, And Computer Science Applications (English) 1st Edition: Kishore Trivedi, PHI
  5. Schaum‟s Outlines Probability, Random Variables & Random Process 3rd Edition Tata

McGraw Hill

  1. Probability & Statistics for Engineers: Dr J Ravichandran, Wiley
  2. Statistics for Business and Economics: Dr Seema Sharma, Wiley
  3. Applied Business Statistics 7th  Edition Ken Black, Wiley