For the data on lead levels in the sea, calculate :the mean;the mode;the median;the standard deviation;the range. Draw a histogram of the distribution of lead levels in the seawater samples listed in Table 10.4. Use class intervals of 10ppm (i.e., 0–10, 11–20 etc.).Present your histogram with proper captions and interpret the results of your graph. Table 10.4 Lead levels (ppm) in samples of seawater101311244527253225729456051142930228456.275143222812334226212.

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For the data on lead levels in the sea, calculate : the mean; the mode; the median; the standard deviation; the range.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.6: Summarizing Categorical Data

Problem 31PPS

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Concept explainers

Estimation

A new framework of data analysis where the new statistical methods are used for interpreting the results and analyzing the data is known as estimation in statistics.

Question

For the data on lead levels in the sea, calculate :
the mean;
the mode;
the median;
the standard deviation;
the range.

Draw a histogram of the distribution of lead levels in the seawater samples listed in Table 10.4. Use class intervals of 10ppm (i.e., 0–10, 11–20 etc.).

Present your histogram with proper captions and interpret the results of your graph.

Table 10.4 Lead levels (ppm) in samples of seawater
10
13
11
24
45
27
25
32
25
7
29
45
60
51
14
29
30
22
8
45
6.
27
51
43
22
28
12
33
42
26
21
2.

Definition Definition Measure of central tendency that is the value that occurs most frequently in a data set. A data set may have more than one mode if multiple categories repeat an equal number of times. For example, in a data set with five item—3, 5, 5, 29, 473—the mode is 5 because it occurs twice and no other value occurs more than once. On a histogram or bar chart, the element with the highest bar represents the mode. Therefore, the mode is sometimes considered the most popular option. The mode is useful for nominal or categorical data (e.g., the most common color car that users purchase), but it is problematic for continuous data because it is more likely not to have any value that is more frequent than the other.

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