Sample CV=5 Population CV= 2.基本概念和知识点 Range,MAD,variance,standard deviation,the coefficient of variance 3.问题与应用 (1)Calculate and interpret the ean-Variance Analy 1.主要内容 Mean-Variance analysis:In some instances,analysis entails comparing two or more data sets that have different means or units of measurement.The coefficient of variation(CV) serves as arelative measure of dispersion and adjusts for differences in the magnitudes of the mean Calculated by dividing a data set's standard deviation by its mean,CV is a unitless measure that allows fordirect comparisons of mean-adjusted dispersion across different data sets. Sample CV Population CV= Sharpe ratio:the extra reward per unit of risk X-R 2.基本概念和知识点 Mean-Variance analysis,Sharpe ratio 3问题与应用 (1)Explain Mean-Varian alysis and the sha Sectio.ChebysheTheorem and the Empirical Rule 1主要内容 Chebyshev'sTheorem As we will see in more detail in later chapters,it is important to be able to use the standard deviation to make statements about the proportion of observations that fall within certain intervals.Fortunately,a Russian mathematician Pavroty Chebyshev(1821-1894)found bounds for the proportion of the data that lie within a specified number of standard deviations from the mean (apply to all data sets) For any set of observations (sample or population),the minimum proportion of the values that lie within k standard deviations of the mean is at least 1-1/k2,where k is any constant 10 10 Standard deviation: the square root of the variance The coefficient of variance Sample CV s x = , Population CV   = 2.基本概念和知识点 Range, MAD, variance, standard deviation, the coefficient of variance 3.问题与应用 (1) Calculate and interpret the range, MAD, variance, standard deviation Section5. Mean-Variance Analysis and the Sharpe Ratio 1.主要内容 Mean-Variance analysis: In some instances, analysis entails comparing two or more data sets that have different means or units of measurement. The coefficient of variation ( CV) serves as a relative measure of dispersion and adjusts for differences in the magnitudes of the means. Calculated by dividing a data set’s standard deviation by its mean, CV is a unitless measure that allows for direct comparisons of mean-adjusted dispersion across different data sets. Sample CV s x = Population CV   = Sharpe ratio: the extra reward per unit of risk I f I x R s − 2.基本概念和知识点 Mean-Variance analysis, Sharpe ratio 3.问题与应用 (1) Explain Mean-Variance analysis and the Sharpe ratio Section6. Chebyshev’s Theorem and the Empirical Rule 1.主要内容 Chebyshev’s Theorem As we will see in more detail in later chapters, it is important to be able to use the standard deviation to make statements about the proportion of observations that fall within certain intervals. Fortunately, a Russian mathematician Pavroty Chebyshev (1821–1894) found bounds for the proportion of the data that lie within a specified number of standard deviations from the mean. (apply to all data sets) For any set of observations (sample or population), the minimum proportion of the values that lie within k standard deviations of the mean is at least 1-1/k2 , where k is any constant