• Matrix Algebra
  • Matrices Introduction
  • Defferent Types of matrices

 

• Addition, Subtraction and Multiplication of Matrices, Symmetric and Skew Symmetric matrix, Determinant of a Matrix, Inverse of a Matrix, Rank of a Matrix
  • Matrix algebra
    • Addition, subtraction and multiplication of matrices
    • Symmetric and skew Symmetric matrices
    • Determinant of a matrix
    • Inverse of a matrix
    • Rank of a matrix

 

• Solution of Simultaneous Equation using Matrices
  • Solution of Simultaneous linear equations using matrices
  • Matrix inversion method
  • Cramer’s rule

 

• Measures of Central Tendency – Mean, Median, Mode
  • Descriptive statistics
  • Measures of Central Tendency
    • Mean
    • Median
    • Mode
  • Advantages and disadvantages of– Mean, Median, Mode

 

• Descriptive Statistics– Measures of Dispersion
  • Descriptive Statistics
    • Measures of Dispersion
    • Range
    • Quartile Deviation
    • Mean Deviation
    • Standard deviation
    • variance

     

• Theory of Correlation: Meaning of Correlation, Simple Correlation, Co-efficient, Rank Correlation.
  • Correlation
    • Introduction
    • Types
    • Coefficient of correlation
    • Measurement of correlation
    • Scatter Diagram
    • Karl Pearson’s coefficient of correlation
    • Rank correlation
    • Coefficient  of Variation
    • Properties of correlation coefficient

 

• Regression Analysis
  • Regression –Introduction and definition
  • Types of regression
  • Line of best fit
  • Regression equations
  • Properties of regression lines and regression coefficients
  • Standard error of estimate
  • Simple linear regression
  • Problems based on linear regression

 

• Probability: Random Experiment, Sample Space and Events, Addition and Multiplication theorems
  • Probability
    • Definitions –random experiment, sample space events etc.
    • Statement of Addition theorem and multiplication theorems
    • Problems based on the above theorems
    • Conditional probability

 

• Bayes Theorems and its Applications
  • Probability
    • Inverse Probability
    • Bayes theorem and its applications in business

       

• Random Variable and Probability Distribution: Binomial, Poisson, Normal
  • Random Variable & Probability Distributions
    • Discrete and continuous random variable
    • Probability Distributions continuous and discrete
    • Binomial distribution
    • Poisson distribution
    • Normal Distribution
    • Uniform Distribution
    • Problems based on the above

 

• Concepts of Population, Sampling Etc.
  • Survey and sampling
    • Population and universe
    • Sampling
    • Sample
    • Types of Sampling
    • Steps in sampling

 

• Test of Significance
  • Test of Significance
    • Introduction –Hypothesis testing
    • Assumptions about parametric and non-parametric tests
    • Hypothesis –Null and Alternate Hypothesis
    • Hypothesis testing process
    • Type 1 and Type 2 Errors
    • Level of significance and rejection region

 

• Non Parametric Tests
  • Non Parametric Test
    • Mann-Whitney U test
    • Kolmogorov-Smirnov Z test
    • Chi square test