A scientist has a hypothesis that as the number of police cars is increased on a roadway, the proportion of cars speeding decreases. He finds that at police car level X1 (one police car per 100 miles), the proportion of cars speeding is . At police car level X2 (one police car per 50 miles), the proportion of cars speeding is . At police car level X3 (one police car per 25 miles), the proportion of cars speeding is . Should the hypothesis be rejected or should it fail to be rejected?
. Rejected, because the data do not support the hypothesis that as the number of police cars per mile increases, the proportion of cars speeding decreases
. Fail to be rejected, because this was an experimental study and the hypothesis is always confirmed in this form of study
. Fail to be rejected, because the proportion of drivers speeding goes down as the number of police cars per mile on a roadway increases
. Rejected, because one of the limits of an experimental study such as this is that causation cannot be made between the variables
A high school statistics student wants to know if studying all night before an exam (cramming) has better results than studying for 3 days prior to an exam. One hundred students from the high school were selected randomly using a random number generator, and were then sorted into one of two groups. The first group studied all night before the exam. The second group studied the same number of hours, but for 3 days prior to the exam. Both groups were tested on the material and the average scores were compared. Which statistical study did the statistics student most likely use?
. He most likely used an experimental study under controlled circumstances because the treatment was applied to a defined, randomly selected group.
. He most likely used a sample survey that asked students who were willing to share their grades how well they did, and compared the averages of those who crammed for the exam with those who studied for the 3 days leading up to the exam.
. He most likely used an observational study by observing students selected at random, noting whether they were happy as they left the exam and determining whether they crammed for the exam or studied for the 3 days leading up to the exam based on how tired they appeared.
. He most likely used a convenience survey that asked students in the lunch room who had taken the exam if they had crammed for the exam or studied for the 3 days leading up to the exam and then compared their class averages.