College Algebra: Concepts and Contexts by James Stewart, Lothar Redlin, Saleem Watson, Phyllis Panman

By James Stewart, Lothar Redlin, Saleem Watson, Phyllis Panman

This article bridges the space among conventional and reform techniques to algebra encouraging scholars to work out arithmetic in context. It offers fewer issues in larger intensity, prioritizing information research as a origin for mathematical modeling, and emphasizing the verbal, numerical, graphical and symbolic representations of mathematical techniques in addition to connecting arithmetic to genuine existence occasions drawn from the scholars' majors

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The table below gives data for the boiling point of water at different elevations. (a) Use first differences to show that a linear model is appropriate for the data. (b) Find a linear model for the relation between boiling point and elevation. (c) Use the model to predict the boiling point of water at the peak of Mount Kilimanjaro, 19,340 ft above sea level. 0 22. Temperatures on Mount Kilimanjaro Mount Kilimanjaro is the highest mountain in Africa. Its snow-covered peak rises 4800 m above the surrounding plain.

In general, data are simply huge lists of numbers. To make sense of all these numbers, we need to look for patterns or trends in the data. Algebra can help us find and accurately describe hidden patterns in data. In this section we begin our study of data by looking at some of their basic properties. 2 ■ Analyzing One-Variable Data The ages of children in a certain group of preschoolers are 2, 2, 2, 3, 3, 3, 4, 4, 4, 4, 4, 5 This list is an example of one-variable data—only one varying quantity (age) is listed.

C) What pattern or trend do you see in these data? ” We also learn how graphs of two-variable data help us get information about the data. 1. Test your readiness by doing the Algebra Checkpoint at the end of this section. When business people, sociologists, or scientists analyze data, they look for a trend or pattern from which to draw a conclusion about the process they are studying. It is often hard to look at a list of numbers and see any kind of pattern; this is especially true when the lists are huge.

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