WORKSHEET
DATASETS
pH data:
The data consist of acidity levels (pH) in 105 samples of rainwater. pH ranges from 0 to 14 and distilled water has pH 7. As the water becomes more acid, the pH goes down. The pH of water is important to environmentalists because of the problem of acid rain.
(From Moore & McCabe, Introduction to the practice of statistics)
Salmon data:
Salmon is born in freshwater rivers and streams and then swim out to the ocean. Researches have studied the growth of freshwater salmon and first year salmon caught in the ocean by measuring the radius of their growth rings.
(From Johnson & Tsui, Statistical reasoning and methods)
Light data:
This dataset is the result of the classic study conducted by Michelson on the speed of light in air in 1879. The response variable is speed of light (in millions of meters per second). The data was included as part of a larger study by Dorsey, Ernest N. (1944) on the velocity of light as reported in the Transactions of the American Philosophical Society.
(From statistical reference datasets)
IQ data:
Displays the IQ scores of 60 fifth grade students.
(From Moore & McCabe, Introduction to the practice of statistics)
Oil data:
How much oil in the wells in a given filed will produce is key information in deciding whether to drill more wells. This dataset contains the amount of oil recovered from 64 wells in the Devonian Richmond Dolomite area of the Michigan basin, in thousands of barrels.
(From Moore & McCabe, Introduction to the practice of statistics)
Emissions data:
This dataset contains the amounts, in grams per mile) of three pollutants (HydroCarbon, Carbon Monoxide and Nitrogen Oxides) in the exhaust of 46 vehicles of the same type measured under standard conditions prescribed by the EPA.
(From Moore & McCabe, Introduction to the practice of statistics)
Test data:
The dataset gives the pretest and posttest scores in Spanish for 20 high school Spanish teachers who attended an intensive summer course in Spanish.
(From Moore & McCabe, Introduction to the practice of statistics)
Data were collected on students taking a course designed to introduce them to a variety of training techniques. The variables are: gender (1=male, 2=female), pretest body fat, posttest body fat, pretest time to run 1.5 miles (seconds), posttest to run 1.5 miles (seconds), pretest to row 2.5Km (seconds), posttest to row 2.5Km (seconds), pretest number of sit-ups completed in 1 minute, posttest number of sit-ups completed in 1 minute.
(From Johnson & Tsui, Statistical reasoning and methods)