检索结果 - "central tendency"

Statistics / 由 Spiegel, Murray R.

书本目录: “...The mean, median, mode, and other measures of central tendency -- Index, or subscript, notation -- Summation notation -- Averages, or measures of central tendency -- The arithmetic mean -- The median -- The mode -- The empirical relation between the mean, median, and mode -- The geometric mean G -- The harmonic mean H -- The relation between the arithmetic, geometric, and harmonic means -- The root mean square -- Quartiles, deciles, and percentiles -- Software and measure of central tendency -- 4. ...”
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Understanding statistics / Bruce J. Chalmer

书本目录: “...-- 3 Describing Data for a Single Variable -- 3.1 There are many ways of summarizing a set of data -- 3.2 Often we are interested in the entire population distribution -- 3.3 Some distributions can be approximated by mathematical functions -- 3.4 A histogram and frequency distribution are very useful descriptive tools -- 3.5 In a histogram, area represents relative frequency -- 3.6 The mean, median, and mode are useful for describing central tendency -- 3.7 The range and interquartile range are measures of variability -- 3.8 The standard deviation is the most commonly used measure of variability -- 3.9 The standard deviation is computed differently for samples versus populations -- 4 Some Distributions Used in Statistical Inference -- 4.1 Knowing the sampling distribution of a statistic allows us to draw inferences from sample data -- 4.2 The standard normal distribution is used to find areas under any normal curve -- 4.3 The binomial distribution is used for variables that count the number of yeses -- 4.4 To calculate binomial probabilities, we need to find the probability of each possible outcome -- 4.5 We next find the number of relevant outcomes and multiply it by the probability of each relevant outcome -- 4.6 Binomial probabilities can be computed from a general formula and are also available in tables -- 4.7 A binomial distribution with large n and moderate p is approximately normal -- 5 Interval Estimation -- 5.1 The standard error of a statistic is the standard deviation of its sampling distribution -- 5.2 The CLT can be applied to draw inferences about the population mean -- 5.3 If we know...”

Understanding statistics / Bruce J. Chalmer 由 CHALMER, Bruce J.

书本目录: “...-- 3 Describing Data for a Single Variable -- 3.1 There are many ways of summarizing a set of data -- 3.2 Often we are interested in the entire population distribution -- 3.3 Some distributions can be approximated by mathematical functions -- 3.4 A histogram and frequency distribution are very useful descriptive tools -- 3.5 In a histogram, area represents relative frequency -- 3.6 The mean, median, and mode are useful for describing central tendency -- 3.7 The range and interquartile range are measures of variability -- 3.8 The standard deviation is the most commonly used measure of variability -- 3.9 The standard deviation is computed differently for samples versus populations -- 4 Some Distributions Used in Statistical Inference -- 4.1 Knowing the sampling distribution of a statistic allows us to draw inferences from sample data -- 4.2 The standard normal distribution is used to find areas under any normal curve -- 4.3 The binomial distribution is used for variables that count the number of yeses -- 4.4 To calculate binomial probabilities, we need to find the probability of each possible outcome -- 4.5 We next find the number of relevant outcomes and multiply it by the probability of each relevant outcome -- 4.6 Binomial probabilities can be computed from a general formula and are also available in tables -- 4.7 A binomial distribution with large n and moderate p is approximately normal -- 5 Interval Estimation -- 5.1 The standard error of a statistic is the standard deviation of its sampling distribution -- 5.2 The CLT can be applied to draw inferences about the population mean -- 5.3 If we know...”

Schaum's Outline of Probability and Statistics, 4th Edition : 897 Solved Problems + 20 Video 由 SPIEGEL, M.

书本目录: “...Covariance Correlation Coefficient Conditional Expectation, Variance, and Moments Chebyshev's Inequality Law of Large Numbers Other Measures of Central Tendency Percentiles Other Measures of Dispersion Skewness and Kurtosis Chapter 4 Special Probability Distributions The Binomial Distribution Some Properties of the Binomial Distribution The Law of Large Numbers for Bernoulli Trials. ...”