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4.3E: Fitting Linear Models to Data (Exercises)

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34.

Draw a scatter plot for the data in Table 2. Then determine whether the data appears to be linearly related.

Table 2
0 -105
2 -50
4 1
6 55
8 105
10 160

35.

Draw a scatter plot for the data in Table 3. If we wanted to know when the population would reach 15,000, would the answer involve interpolation or extrapolation?

Table 3
Year Population
1990 5,600
1995 5,950
2000 6,300
2005 6,600
2010 6,900
36.

Eight students were asked to estimate their score on a 10-point quiz. Their estimated and actual scores are given in Table 4. Plot the points, then sketch a line that fits the data.

Table 4
Predicted Actual
6 6
7 7
7 8
8 8
7 9
9 10
10 10
10 9

37. Draw a best-fit line for the plotted data.

Scatter plot of the points: (2,78); (4,81); (6,85); (8,90); and (10,99).

For the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city of people 25 years or older who are college graduates is given below, by year.

Table 5
Year 2000 2002 2005 2007 2010
Percent Graduates 6.5 7.0 7.4 8.2 9.0
38.

Determine whether the trend appears to be linear. If so, and assuming the trend continues, find a linear regression model to predict the percent of unemployed in a given year to three decimal places.

39.

In what year will the percentage exceed 12%?

40.

Based on the set of data given in Table 6, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.

Table 6
xx 17 20 23 26 29
yy 15 25 31 37 40
41

Based on the set of data given in Table 7, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.

Table 7
xx 10 12 15 18 20
yy 36 34 30 28 22

For the following exercises, consider this scenario: The population of a city increased steadily over a ten-year span. The following ordered pairs show the population and the year over the ten-year span (population, year) for specific recorded years:

(3,600,2000);(4,000,2001);(4,700,2003);(6,000,2006)

42. Use linear regression to determine a function y, where the year depends on the population, to three decimal places of accuracy.

43. Predict when the population will hit 12,000.

44. What is the correlation coefficient for this model to three decimal places of accuracy?

45. According to the model, what is the population in 2014?


This page titled 4.3E: Fitting Linear Models to Data (Exercises) is shared under a CC BY 4.0 license and was authored, remixed, and/or curated by OpenStax via source content that was edited to the style and standards of the LibreTexts platform.

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