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Titlebook: Activity-Based Statistics; Student Guide Richard L. Scheaffer,Ann Watkins,Jeffrey A. Witmer Textbook 1996 Springer Science+Business Media N

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21#
發(fā)表于 2025-3-25 06:21:55 | 只看該作者
https://doi.org/10.1007/978-1-4757-3843-8Simula; Trend; average; boundary element method; correlation; design; form; law of large numbers; learning; r
22#
發(fā)表于 2025-3-25 11:32:11 | 只看該作者
Springer Science+Business Media New York 1996
23#
發(fā)表于 2025-3-25 12:54:32 | 只看該作者
24#
發(fā)表于 2025-3-25 19:35:42 | 只看該作者
Selection of the Significant Variablesthrough your mind? Maybe it’s, “Hmmm, I wonder if these players are really that tall.” Since there is an advantage to having tall basketball players on your team, sometimes these figures are “stretched” a bit toward the larger values. This is an example of bias.Interestingly enough, if the opposing
25#
發(fā)表于 2025-3-25 20:58:59 | 只看該作者
https://doi.org/10.1007/978-94-015-7708-3 size, or if all the trees were the same size? Virtually everything around us is subject to variability. Sometimes variability is good, as in sizes of people, and sometimes it is not so good, as in the diameter of the cylinders in the engine of your car. Since variability is always with us, we must
26#
發(fā)表于 2025-3-26 02:41:30 | 只看該作者
Use of the Results of a Sample Survey to collect family income data from a sample of Americans and then construct a histogram, we would expect the histogram to be skewed to the right. If we think about the type of data we would be likely to obtain, we can say something about the shape of the histogram without actually collecting the da
27#
發(fā)表于 2025-3-26 08:23:01 | 只看該作者
28#
發(fā)表于 2025-3-26 11:13:46 | 只看該作者
Colin Campbell M.Sc., C.Eng., M.I.Mech.Engrsthe same number of french fries intwo orders at McDonald’s, or two scoops of ice cream will not be exactly the same. Therefore, “variability” is present in the outcomes of all repeated actions. ., where measurement plays a role, is a major concern in the real world. The main objective in process con
29#
發(fā)表于 2025-3-26 16:24:32 | 只看該作者
Colin Campbell M.Sc., C.Eng., M.I.Mech.Engrsweather? This question is much debated partly because it is difficult to see long-term trends in data that is subject to many short-term fluctuations (sometimes called “jitters”). Some of the fluctuations can be removed, however, by “smoothing” the data. In this lesson, moving averages will be used
30#
發(fā)表于 2025-3-26 17:38:02 | 只看該作者
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