# Working with Large Data SetsIn Problems, use the technology of your choice to do the following tasks.a. Construct and interpret a scatterplot for the data.b. Decide whether finding a regression line for the data is reasonable. If so, then also do parts (c)–(f).c. Determine and interpret the regression equation. d. Make the indicated predictions.e. Compute and interpret the correlation coefficient.f. Identify potential outliers and influential observations.High Temperature and Precipitation. The National Oceanic and Atmospheric Administration publishes temperature and precipitation information for cities around the world in Climates of the World. Data on average high temperature (in degrees Fahrenheit) in July and average precipitation (in inches) in July for 48 cities are on theWeissStats site. For part (d), predict the average July precipitation of a city with an average July temperature of 83 °F.

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Working with Large Data Sets

In Problems, use the technology of your choice to do the following tasks.

a. Construct and interpret a scatterplot for the data.

b. Decide whether finding a regression line for the data is reasonable. If so, then also do parts (c)–(f).

c. Determine and interpret the regression equation.

d. Make the indicated predictions.

e. Compute and interpret the correlation coefficient.

f. Identify potential outliers and influential observations.

High Temperature and Precipitation. The National Oceanic and Atmospheric Administration publishes temperature and precipitation information for cities around the world in Climates of the World. Data on average high temperature (in degrees Fahrenheit) in July and average precipitation (in inches) in July for 48 cities are on theWeissStats site. For part (d), predict the average July precipitation of a city with an average July temperature of 83 °F.