第11章非参数统计法 Nonparametric Statistics
第11章 非参数统计法 Nonparametric Statistics
本章概要 Testing with Rank sum Z Test for Differences in Two Proportions (Independent Samples u x Test for Differences in Two Proportions (Independent Samples) u x Test for Differences in c Proportions (Independent Samples) n x Test of Independence
本章概要 •Testing with Rank Sum • Z Test for Differences in Two Proportions (Independent Samples) 2 Test for Differences in Two Proportions (Independent Samples) 2 Test for Differences in c Proportions (Independent Samples) 2 Test of Independence
常见非参数法 Statistical Procedures for Hypothesis Testing that o Because they are based on Counts or Ran o A Random Sample is still required The Nonparametric Approach Based on a Count the number of times some event occurs a Use the binomial distribution to decide whether this count is reasonable or not under the null hypothesis The Nonparametric Approach Based on o Replace each data value with its rank( a Use formulas and ta bles created for testing ranks
常见非参数法 Statistical Procedures for Hypothesis Testing that do Not Require a Normal Distribution Because they are based on Counts or Ranks A Random Sample is still required The Nonparametric Approach Based on Counts Count the number of times some event occurs Use the binomial distribution to decide whether this count is reasonable or not under the null hypothesis The Nonparametric Approach Based on Ranks Replace each data value with its rank (1, 2, 3, …) Use formulas and tables created for testing ranks
参数法及其效率 Parametric Methods, Efficiency Parametric methods a Statistical procedures that require a completely specified model D e.g. t tests, regression tests, F tests Efficiency D A measure of the effectiveness of a statistical test a Tells how well it makes use of the information in the data D A more-efficient test can achieve the same results with a smaller sample size
参数法及其效率 Parametric Methods, Efficiency Parametric Methods Statistical procedures that require a completely specified model e.g., t tests, regression tests, F tests Efficiency A measure of the effectiveness of a statistical test Tells how well it makes use of the information in the data A more-efficient test can achieve the same results with a smaller sample size
优、缺点 Advantages of Nonparametric Testing d No need to assume normalit n Avoids problems of transformation(e.g, interpretation) D Can be used with ordinal data o Because ranks can be found a Can be much more efficient than parametric methods when distributions are not normal Disadvantage of Nonparametric Testing o Less statistically efficient than parametric methods when distributions are normal Often, this loss of efficiency is slight
优、缺点 Advantages of Nonparametric Testing No need to assume normality Avoids problems of transformation (e.g., interpretation) Can be used with ordinal data ⚫ Because ranks can be found Can be much more efficient than parametric methods when distributions are not normal Disadvantage of Nonparametric Testing Less statistically efficient than parametric methods when distributions are normal ⚫ Often, this loss of efficiency is slight