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
● Concurrent Deviation
● 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

Unit V: Time Series Analysis:
● 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