Gurmeet Kaur, Soumya Sharma, Rachan Sareen Business Statistics

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Unit I – Introduction to Business Statistics

1. Nature and Scope of Statistics

   • Definition and functions of statistics

   • Importance in business and economics

   • Types of statistical methods: descriptive & inferential

2. Classification and Tabulation of Data

   • Types of data: qualitative vs. quantitative

   • Frequency distribution

   • Construction of tables and classification of data

3. Diagrammatic and Graphical Presentation

   • Bar diagrams, pie charts, histograms

   • Frequency polygons and ogives

   • Graphs for time series data

Unit II – Measures of Central Tendency and Dispersion

4. Measures of Central Tendency

   • Arithmetic mean, median, mode

   • Weighted and geometric means

   • Merits, demerits, and uses in business

5. Measures of Dispersion

   • Range, interquartile range, variance, standard deviation

   • Coefficient of variation

   • Application in risk and business comparison

6. Skewness and Kurtosis

   • Meaning and measurement

   • Karl Pearson and Bowley’s measures

   • Interpretation of skewed data

Unit III – Probability and Probability Distributions

7. Basic Probability Concepts

   • Definitions and types of probability

   • Addition and multiplication rules

   • Conditional probability and Bayes’ Theorem

8. Theoretical Distributions

   • Binomial distribution

   • Poisson distribution

   • Normal distribution and its business applications

Unit IV – Correlation and Regression

9. Correlation Analysis

   • Types of correlation: positive/negative, linear/non-linear

   • Karl Pearson’s coefficient

   • Spearman’s rank correlation

10. Regression Analysis

    • Linear regression: estimation and interpretation

    • Regression equations and lines

    • Business forecasting using regression

Unit V – Index Numbers and Time Series Analysis

11. Index Numbers

    • Meaning, types, and uses

    • Construction of price and quantity index numbers (Laspeyres, Paasche, Fisher)

    • Cost of living index and wholesale price index

12. Time Series Analysis

    • Components: trend, seasonal, cyclical, irregular

    • Methods of measuring trend: moving average, least squares

    • Forecasting and business planning

Unit VI – Sampling and Hypothesis Testing

13. Sampling Techniques

    • Census vs. sample survey

    • Probability and non-probability sampling methods

    • Sampling and non-sampling errors

14. Hypothesis Testing

    • Basic concepts: null and alternative hypothesis, significance level

    • Type I and Type II errors

    • Z-test, t-test, chi-square test (introductory level)

Unit VII – Use of Statistics in Business Decision-Making

15. Decision-Making Under Uncertainty

    • Role of statistics in managerial decisions

    • Application in marketing, finance, HR, and production

16. Introduction to Statistical Software (Optional Chapter)

    • Brief overview of Excel/SPSS/Power BI for statistical analysis

    • Data visualization and interpretation