Business Statistics for B.Com Part 1

Study Notes

Business Statistics Notes for B.Com Part 1

Chapter 1: Measures of Central Tendency (Pages 2-23)
- Discusses characteristics of data, including averages (Central Tendency)
- Averages are used to compare populations/samples.
- Key measures include Arithmetic Mean, Geometric Mean, Harmonic Mean, Median, Mode.
Chapter 2 Measures of Dispersion (Pages 24-34)
- Examines the variation among data points.
- Range (difference between highest and lowest values) is a simple but crude measure.
- Other measures (Quartile Deviation, Variance, Standard Deviation) provide more in-depth analysis.
Chapter 3: Measurement of Skewness (Pages 35-37)
- Defines skewness as a measure of asymmetry in a distribution.
- Discusses methods for calculating skewness using different formulas.
Chapter 4: Price Index Numbers (Pages 38-41)
- Discusses various price index calculations (Laspeyre, Paasche, Fisher).
- Explains how to use quantities as weights to determine relevant price changes.
Chapter 5: Simple Linear Regression (Pages 42-45)
- Describes a statistical technique to determine the relationship between two variables (x and y).
- Includes regression equations and coefficients.
Chapter 6: Chi-Square Tests (Pages 46-54)
- Introduces the chi-square distribution, a statistical distribution used for various analyses.
- Discusses its properties, including its use in hypothesis testing about frequencies.
Chapter 7: Counting Techniques (Pages 55-65)
- Explains counting techniques such as permutations and combinations and their applications in probability.
- Tree diagrams for counting outcomes are illustrated.
- Explaining how these rules are applied in different situations (e.g. items being distinct or repeating).
Chapter 8: Probability Theory (Pages 66-70)
- Covers fundamental concepts
- Details axioms, classical/empirical approaches for calculating probability.
Chapter 9: Sampling Distribution (Pages 71-78)
- Introduces population, sample, and sampling methods.
- Explains procedures like simple random, stratified, cluster and systematic sampling.
- Discusses different characteristics, properties of sampling distributions with a focus on mean (expected value and standard error).