}·       {C}

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