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Shakespeare's comedies /

Subjects: “…Comedy.…”
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Shakespearean comedies by Putatunda, Sarbani

Statistical concepts : a basic program by Amos, Jimmy R.

Table of Contents: “…Frequency distribution Averages Median Mode The normal curve Variability Interpreting test scores Standard score Relationship: correlation coefficient Reliability and validity Inferential statistics Regression Standard error of measurement Diagnostic test and alphabetical index Evaluative data…”

Statistics / by Spiegel, Murray R.

Table of Contents: “…Frequency distributions -- Raw data -- Arrays -- Class intervals and class limits -- Class boundaries -- The size, or width, of a class interval -- The class mark -- General rules for forming frequency distributions -- Histograms and frequency polygons -- Relative-frequency distributions -- Cumulative-frequency distributions and ogives -- Relative cumulative-frequency distributions and percentage ogives -- Frequency curves and smoothed ogives -- Types of frequency curves -- 3. 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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A practical approach to using statistics in health research : from planning to reporting / by Mackridge, Adam

Table of Contents: “…Skewed Data Using Quartiles and the Median; 3.1.3 Polymodal Data Using the Modes; 3.2 Ordinal Data; 3.2.1 Ordinal Scales With a Narrow Range of Possible Values; 3.2.2 Ordinal Scales With a Wide Range of Possible Values. 3.2.3 Dividing an Ordinal Scale Into a Small Number of Ranges (e.g. …”

Business mathematics and statistics / by Francis A.

Table of Contents: “…Statistical measures 6. Arithmetic Mean 7. Median 8. Mode and Other Measures of Location9. Measures of Dispersion and Skewness 10. …”

Understanding statistics / Bruce J. Chalmer

Table of Contents: “…-- 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 by CHALMER, Bruce J.

Table of Contents: “…-- 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…”

Economic valuation with stated preference techniques : a manual

Table of Contents: “…Analysis of contingent valuation data 173 (75) 5.1 Contingent valuation data sets 174 (8) 5.2 Specification of the bid function 182 (9) 5.3 Estimating mean and median WTP 191 (4) 5.4 Models. for testing the validity of WTP values 195 (1) 5.5 Models for benefits transfer exercises 196 (1) 5.6 Conclusions 197 (2) ANNEX 5.1 Econometric estimation of the bid function 199 (25) ANNEX 5.2 Estimating mean and median WTP 224 (24) 6. …”