Clone of 2CSE401 Probability & Statistics

Learning Outcomes: 
Understand all basic fundamentals of Statistics and its application on collected information
Prepare him/her self for making a proper interpretation of system based on parameters of distribution.
Apply knowledge of statistics and Probability to form a mathematical model to ensure conclusive hypothesis for problem.
Syllabus: 
Unit NoTopics
1
Frequency Distribution: 
Collection of data, Classification of data, Class interval, Types of Classes, Class frequency, Class mark, Class Boundaries, Width of a class, Frequency density, Relative frequency, Percentage frequency, Cumulative frequency.
2
Measures Of Central Tendency: 
Introduction, Arithmetic Mean, Simple and weighted for raw data, Discrete frequency distribution, Continuous frequency distribution, Properties of A.M., Merits & De merits of A.M., Median for raw data, Discrete frequency distribution, Continuous frequency distribution, Merits and demerits of Median, Mode for raw data, Merits & demerits of mode.
3
Measures Of Dispersion: 
Introduction, Range, coefficient of range, Quartiles, Quartiles deviations, coefficient of quartile deviations, Mean deviation and coefficient of mean deviation, S.D and variance for all types of frequency distribution, Coefficient of Dispersion, Coefficient of variation.
4
Correlation: 
Definition of Correlation,  Types of Correlation,  Scatter  Diagram Method,  Karl Person’s 
 
Correlation Coefficients, Correlation Coefficients for Bivariate frequency distribution, Probable error for Correlation Coefficients, Rank Correlation Co-efficient.
5
Regression: 
Definition of Regression, Regression lines, Regression Coefficients, Properties of regression Coefficients, and Fitting of regression lines and estimation for Bivariate frequency distribution, Multiple Linear Regression.
6
Probability Theory: 
Introduction, Random Experiment, Sample Space, Events, Complementary Events, Union and Intersection of Two Events, Difference Events, Exhaustive Events, Mutually Exclusive Events, Equally Likely Events, Independent Events, Mathematical & Statistical definition of Probability, Axiomatic definition of probability, Addition Theorem, Multiplication Theorem, Theorems of Probability, Conditional Probability, Inverse Probability.
7
Probability Distributions: Binomial Distribution: 
Introduction, Probability mass function of Binomial distribution, Mean and Variance of Binomial distribution, Properties of Binomial Distribution, Uses of Binomial Distribution. 
Poisson Distribution: 
Introduction, Probability mass function of Poisson distribution, Mean and Variance of Poisson distribution, Properties of Poisson Distribution, Applications of Poisson Distribution. 
Normal Distribution:
Introduction, Probability density function of Normal distribution, Properties of Normal distribution, Importance of Normal Distribution.
Text Books: 
Name : 
Probability, Statistics and Random Process
Author: 
T Veerarajan
TMH
Edition: 
3rd
Reference Books: 
Name: 
Fundamental of Applied Statistic
Author: 
S.C. Gupta
V.K. Kapoor
Publication: 
Sultan Chand Publication
Name: 
Statistical Methods
Author: 
S. P. Gupta
Publication: 
Sultan Chand Publication
Name: 
Business Statistics
Author: 
Prof. H.R. Vyas & Others
Publication: 
B.S. Shah Prakashan
Syllabus PDF: 
AttachmentSize
PDF icon Probability & Statistics.pdf164.93 KB
branch: 
CBA
BDA
MA
Course: 
2016
Stream: 
B.Tech