Mathematics

Mathematics, 21.07.2019 06:30, jojo8617

You are given the following list of values: 5.8, 6.1, 4.9, 10.9, 0.8, 6.1, 7.4, 10.2, 1.1, 5.2, 5.9 which values are outliers?

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Computers and Technology, 01.10.2019 02:00, cocomelon

Design and implement an algorithm that gets as input a list of k integer values n1, nk as well as a special value sum. your algorithm must locate a pair of values in the list n that sum to the value sum. for example, if your list of values is 3, 8, 13, 2, 17, 18, 10, and the value of sum is 20, then your algorithm would output either of the two values (2, 18) or (3, 17). if your algorithm cannot find any pair of values that sum to the value sum, then it should print the message ‘sorry, there is no such pair of values’. schneider, g.michael. invitation to computer science (p. 88). course technology. kindle edition.

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Computers and Technology, 07.10.2019 23:30, jackson5637

5.16 lab: adjust list by normalizing when analyzing data sets, such as data for human heights or for human weights, a common step is to adjust the data. this can be done by normalizing to values between 0 and 1, or throwing away outliers. for this program, adjust the values by subtracting the smallest value from all the values. the input begins with an integer indicating the number of integers that follow. assume that the list will always contain less than 20 integers. ex: if the input is: 5 30 50 10 70 65 the output is: 20 40 0 60 55 the 5 indicates that there are five values in the list, namely 30, 50, 10, 70, and 65. 10 is the smallest value in the list, so is subtracted from each value in the list. for coding simplicity, follow every output value by a space, including the last one.

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Mathematics, 26.10.2019 00:43, donaji1024perez

In your own words, describe to someone who knows only a little statistics how to recognize when an observation is an outlier. what action(s) should be taken with an outlier? (a) outliers are observed values far from the main group of data. in a histogram they are separated from the others by space. (b) outliers must be looked at in closer context to know how to treat them. if they aremistakes, they might be removed or corrected. if they are not mistakes, you might do the analysis twice, once with and once without the outliers. (c) outliers are observed values far from the main group of data. in a histogram they are separated from the others by space. outliers should be ignored because they can distort any calculations done and are not representative of typical values. (d) outliers are the minimum and maximum values observed in a data set. they should be treated as any other value, as the term "outliers" is just another name for the minimum and maximum.

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You are given the following list of values: 5.8, 6.1, 4.9, 10.9, 0.8, 6.1, 7.4, 10.2, 1.1, 5.2, 5.9...

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