Business Statistics

Introduction
• Definition of Statistics, Importance, Limitations and Scope of Statistics,
• Types and Source of Data,
• Methods of Data Collection
• Classification and Tabulation of Data
• Measures of Central Tendency
• Mathematical averages including arithmetic mean, geometric mean and harmonic mean.
• Positional Averages Mode and Median (and other partition values including quartiles, deciles, and percentiles)

• Absolute and relative measures of dispersion
• Range, quartile deviation, mean deviation, standard deviation, and their coefficients, Properties of standard deviation/variance
• Skewness
• Meaning, Measurement using Karl Pearson and Bowley’s measures

• Correlation Analysis
• Meaning of Correlation: simple, multiple and partial; linear and non-linear, Correlation and Causation,
• Scatter diagram, Pearson’s co-efficient of correlation; calculation and properties
• Correlation and Probable error;
• Rank Correlation
• Regression Analysis:
• Principle of least squares and regression lines,
• Regression equations and estimation;
• Properties of regression coefficients;
• Relationship between Correlation and Regression coefficients;
• Standard error of the estimate

Meaning and uses of index numbers;
• Construction of index numbers: fixed and chain base: univariate and composite. Aggregative and average of relatives – simple and weighted
• Tests of adequacy of index numbers,
Base shifting, splicing and deflating.
• Problems in the construction of index numbers;

Components of time series;
• Additive and multiplicative models;
• Trend analysis: Fitting of trend line using principle of least squares
• Moving averages;
• Seasonal variations: Calculation of Seasonal Indices using Simple averages, Ratio-to-trend, and Ratio-to-moving averages methods.
• Uses of Seasonal Indices