Unit I Introduction 

  • Basic concepts of statistics
  • Terminologies associated with statistics such as populations and samples
  • Variables (Dependent and independent only)
  • Types and sources of data, Descriptive and inferential statistics
  • Data processing (editing and coding)
  • Applications of statistics in business and management.

Unit II Describing Data: Graphs and Tables 

  • Method of forming Class Interval
  • Data array
  • Stem and leaf Display
  • Frequency tables, Histograms
  • Polygon
  • Cumulative Polygon
  • Scatter plots
  • Simple Bar and Pie charts
  • Cross tabulation

Unit III Describing Data: Summary Measures 

  • Central Location: Arithmetic Mean, Median, and Mode
  • Non Central Location Partition Values: Quartiles, Deciles and Percentiles
  • Dispersion: Range, Interquartile range, Variance, Standard deviation, Coefficient of variation, Index for qualitative variation (IQV)
  • Shape: Crude measure (comparison of mean, median, and mode), five-number summary, Box plot
  • Inequality Measure: Gini concentration ratio

Unit IV Basics of Probability Theory

  • Basic concepts
  • Counting rule
  • Objective and subjective probability
  • Marginal and joint Probability
  • Addition rule
  • Conditional probability
  • Multiplication rules
  • Bayes’ Theorem.

Unit V Probability Distributions 

  • Discrete probability distribution (Binomial and Poisson distribution and mean and standard deviation of their distributions)
  • Continuous probability distribution: Normal distribution, Normal approximation of Binomial and Poisson distribution

Unit VI Estimation and Hypothesis Testing 

  • Concept of estimation
  • Confidence intervals
  • confidence intervals for means and proportions ( one sample case only )
  • Test of significance
  • p-value approach to hypothesis testing
  • the connection between confidence intervals and hypothesis testing
  • comparing two means (two-sample z and t-test procedures)
  • comparing two proportions.