Ability to apply various statistical tools and techniques in the process of business analytics

1. Statistics for Business
Analytics

2. • Central Tendencies & dispersion
• Measures of Association
• Sampling distribution
• Hypothesis testing
• Simple linear regression
• Categorical data analysis
• Analysis of Variance (ANNOVA)
• Non parametric tests

3. Central Tendencies (Measures of location)
(centering of set location)
• Mean (Average)
• Mode (Largest frequency)
• Median (Middle value)
• Geometric Mean (Growth rates)

5. Application of Central Tendencies
Mean: To know average;
• Salary of employees
• Performance of employees
• Performance of players
• Performance of industry
• Prices of products/services

6. • Median:
• Mainly used in qualitative cases like honesty, intelligence, ability, etc.
• These are also suitable for the problems of distribution of income, wealth investment,
etc.
• Mode:
• To know most sold size/ quantity/ price/ color/ brand etc., of product or service.
• To know most favorite actor/ actress/ villain/ movie/ serial/ city/ state/ country etc.
• Geometric Mean:
• Growth rates in financial data

7. Measures of Dispersion (Variability)
• Range (Maximum value – Minimum value)
• Variance ( Deviation from the mean)
• Standard deviation (how spread out a data set is)
• Coefficient of Variation (how large the standard deviation is relative to the
mean)

8. Application of Dispersion (Variability)
• Range: difference in maximum and minimum prices/ quantities of products/
services/ share prices/ property rates/demand/ supply etc.
• Variance: to find the standard deviation , beta, hypothesis testing and for many
more statistical calculations.
• Standard deviation:
• To measure the risk of a stock or a stock portfolio.
• In manufacturing it is used as a way of quality control
• In polls and surveys it can be used to measure the level of confidence of our results.
• Coefficient of Variation: To measure and manage investment risks.

9. Measures of Association
• Covariance (To measure the extent to which two random variables change)
• Correlation (To measure the change in one item may result in the change in
another item)

10. Application of Association
• Covariance can tell how the two variables (stocks/ products/ services/
employees performance/ demand-supply etc.) move together.
• Correlation provides additional information by telling you the degree to
which both variables (stocks/ products/ services/ employees performance/
demand-supply etc.) move together.