Statistics and Probability (V-U)

• Introduction (V-U)
• Methods of data collection and sampling (V-U)
• Data Representation (V-U)
• Continous variable (V-U)
• Frequency curve and distribution (V-U)
• Histogram (V-U)
• The Central Tendency of a data-set (V-U)
• Median (V-U)
• Geometric mean,Harmonic mean & relationship between them (V-U)
• Measures of Dispersion (V-U)
• Mean Deviation,Standard Deviation and Variance & Coefficient of variation (V-U)
• Chebychev’s Inequality,The Empirical Rule & The Five-Number Summary (V-U)
• Box and Whisker Plot,Pearson’s Coefficient of Skewness (V-U)
• Pearsonian co-efficient of Skewness (V-U)
• Set Theory,Counting Rules (V-U)
• Permutations,Combinations (V-U)
• Definitions of Probability (V-U)
• Relative Frequency, Axiomatic Definition & Laws of Probability (V-U)
• Application of Addition Theorem,Conditional Probability & Multiplication Theorem (V-U)
• Independent and Dependent Events,Multiplication Theorem & Marginal Probability (V-U)
• Bayes’ Theorem,Discrete Random Variable (V-U)
• Graphical Representation of the Distribution Function of a Discrete Random Variable (V-U)
• Chebychev’s Inequality & Concept of Continuous Probability Distribution (V-U)
• Continuous Probability Distribution ,Bivariate Probability Distribution (V-U)
• Distributions BIVARIATE Probability ,Properties of Expected Values in the case of Bivariat (V-U)