The following data represent the number of people who had...

The following data represent the number of people who had Internet access in the years 2000 and 2003 by level of education. Data are in thousands of U.S. residents. (a) Construct a relative frequency distribution for 2000 . (b) Construct a relative frequency distribution for 2003 (c) Construct a side-by-side relative frequency bar graph. (d) Compare each year's Internet access. Make some conjectures about the reasons for any differences or similarities (TABLE CAN'T COPY)

The following data represent the number of people who had Internet access in the years 2000 and 2003 by level of education. Data are in thousands of U.S. residents.
(a) Construct a relative frequency distribution for 2000 .
(b) Construct a relative frequency distribution for 2003
(c) Construct a side-by-side relative frequency bar graph.
(d) Compare each year's Internet access. Make some conjectures about the reasons for any differences or similarities
(TABLE CAN'T COPY)

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Key Concepts

Relative Frequency Distribution

A relative frequency distribution shows the proportion of the total for each category by dividing the frequency of each category by the total count. This concept is crucial in turning raw counts into comparable percentages or fractions, making it easier to compare different groups or data sets regardless of their absolute sizes.

Side-by-Side Bar Graph

A side-by-side bar graph is a visual tool used to compare the relative frequencies or proportions of different categories across multiple groups. It allows for a direct visual comparison by placing bars for different groups adjacent to each other, thereby facilitating the identification of trends or differences between the groups.

Data Comparison and Conjecture

Comparing data across different time periods or groups involves examining the relative differences in frequencies or percentages to identify trends, patterns, or anomalies. This concept also includes making informed conjectures or hypotheses about the reasons behind these differences, using context or external factors, even when the data itself does not explicitly reveal causation.

Transcript

00:02 In this problem, we're going to be considering data that represents the number of people who had internet access in the years 2000 and 2003 by level of education.

00:16 So the data we have are in thousands of us residents.

00:21 So in the first part of the question a, we shall construct a relative frequency distribution for the year 2000.

00:28 And so we need to introduce a column there where we shall have a relative frequency.

00:43 That's for the year 2000.

00:48 To get the relative frequency, we must first get the sum of frequencies for that year 2000, which is 90 ,503.

01:04 Next, we divide each category, each frequency by the total.

01:09 So that's 24 ,662 divided by 90 ,500propi from nauv.

01:27 So those are the proportions for different categories.

01:32 In other words, that's a relative frequency distribution for the year 2000, which is needed for part a.

01:41 Now for part b, we want the relative frequency distribution for the year 2003.

01:54 So we also have to introduce a column for the year 2003 and also you have to get the value of the frequency, the total frequency for the year 2003.

02:10 So that means we get the sum frequencies which equals 165 ,899.

02:20 Now for the relative frequencies we divide each of these frequencies by that value of the total frequency 165...

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