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Chapter 4 Displaying and Summarizing Quantitative Data
Chapter 4 Displaying and Summarizing Quantitative Data

... 2) if the shape is skewed, report the median and IQR; the mean and standard deviation are sensitive to outliers (you can include the mean and standard deviation, but you should point out why the mean and median differ) 3) if the shape is symmetric, report the mean and standard deviation. 4) if there ...
Open Ended
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... d. How can you find the probability of choosing a blue marble? 7. Decide whether each statement is true or false. Justify your answers. a. The probability of an outcome can be 0. b. The probability of an outcome can be 1. c. The probability of an outcome can be greater than 1. 8. Patricia and Jean d ...
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Chapter 13. Binomial Distributions

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Statistics as both a purely mathematical activity and an applied

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THEME: VARIATION ROWS. AVERAGES

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Powerpoint - Marshall University Personal Web Pages

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Probability Distributions - School of Mathematical and Computer

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Slide 17

... Assumptions  independent observations for some tests only  normal distribution not necessary  homogeneity of variance not necessary  appropriate for nominal and ordinal data, may be used for interval or ratio data Irwin/McGraw-Hill ...
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6.1 Discrete and Continuous Random Variables
6.1 Discrete and Continuous Random Variables

... distributions  of  random  variables.  You  can  use  what  you  learned  earlier  to  describe  the  shape  of  a  probability   distribution  histogram.  We’ve  already  seen  examples  of  symmetric  (number  of  heads  in  three  coin ...
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Two-Group Parametric Hypothesis Testing

... This test is appropriate whenever data have been collected in a way that results in the two samples of scores being related to each other. Suppose that Farmer Sol is evaluating the yield of two varieties of cucumbers that produce superior fruits, the SuperCuke and the Cukazilla. He has 12 small plot ...
X - Alan Neustadtl @ The University of MD
X - Alan Neustadtl @ The University of MD

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History of statistics

The History of statistics can be said to start around 1749 although, over time, there have been changes to the interpretation of the word statistics. In early times, the meaning was restricted to information about states. This was later extended to include all collections of information of all types, and later still it was extended to include the analysis and interpretation of such data. In modern terms, ""statistics"" means both sets of collected information, as in national accounts and temperature records, and analytical work which requires statistical inference.Statistical activities are often associated with models expressed using probabilities, and require probability theory for them to be put on a firm theoretical basis: see History of probability.A number of statistical concepts have had an important impact on a wide range of sciences. These include the design of experiments and approaches to statistical inference such as Bayesian inference, each of which can be considered to have their own sequence in the development of the ideas underlying modern statistics.
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