Measures of Dispersion

• Explains the concepts of range, quartile deviation, mean deviation, and standard deviation.

• Introduces the coefficient of variation as a relative measure of dispersion.

• Highlights the importance of dispersion in analyzing the spread of data.

Skewness, Kurtosis, and Moments

• Defines the concepts of skewness and kurtosis in statistical distributions.

• Discusses different measures of skewness for identifying asymmetry.

• Introduces moments and explains their applications in statistical analysis.

Correlation

• Explains the meaning and significance of correlation in data relationships.

• Covers Karl Pearson’s method of correlation.

• Introduces Spearman’s rank correlation for non-parametric data.

• Explains correlation using the scatter diagram method.

Regression Analysis

• Introduces regression lines and equations for predicting values.

• Explains the relationship between correlation and regression.

• Shows how regression is used for making predictions based on data.

Index Numbers

• Defines index numbers and explains their meaning and types such as price index, quantity index, and value index.

• Describes different methods of construction, including Laspeyres, Paasche, and Fisher’s index numbers.

• Highlights the uses of index numbers in economics and business along with their limitations.

Probability Theory

• Introduces the basic concepts and definitions of probability.

• Explains the addition and multiplication rules of probability.

• Provides simple numerical problems based on probability concepts.

Practical Work

• Involves solving numerical problems related to dispersion, correlation, and regression.

• Guides students in constructing index numbers using statistical methods.

• Includes exercises on probability applications.