What you’ll learn
- Random Variables
- Discrete Random Variables and its Probability Mass Function
- Continuous Random Variables and its Probability Density Function
- Cumulative Distribution Function and its properties and application
- Special Distribution
- Two – Dimensional Random Variables
- Marginal Probability Distribution
- Conditional Probability Distribution
- Independent Random Variables
- Function of One Random Variable
- One Function of Two Random Variables
- Two Functions of Two Random Variables
- Statistical Averages
- Measures of Central Tendency (Mean, Median, Mode, Geometric Mean and Harmonic Mean)
- Mathematical Expectations and Moments
- Measures of Dispersion (Quartile Deviation, Mean Deviation, Standard Deviation and Variance)
- Skewness and Kurtosis
- Expected Values of Two-Dimensional Random Variables
- Linear Correlation
- Correlation Coefficient and its properties
- Rank Correlation Coefficient
- Linear Regression
- Equations of the Lines of Regression
- Standard Error of Estimate of Y on X and of X on Y
- Characteristic Function and Moment Generating Function
- Bounds on Probabilities
How to Enroll Master Complete Statistics For Computer Science – I course?
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