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