Answered: To illustrate the effects of driving…

Holt Mcdougal Larson Pre-algebra: Student Edition 2012

1st Edition

ISBN:9780547587776

Author:HOLT MCDOUGAL

Publisher:HOLT MCDOUGAL

Chapter11: Data Analysis And Probability

Section11.3: Using Data Displays

Problem 1E

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To illustrate the effects of driving under the influence (DUI) of alcohol, a police officer brought a DUI simulator to a local high school. Student reaction time in an emergency was measured with unimpaired vision and also while wearing a pair of special goggles to simulate the effects of alcohol on vision. For a random sample of nine teenagers, the time (in seconds) required to bring the vehicle to a stop from a speed of 60 miles per hour was recorded. Complete parts (a) and (b).

Note: A normal probability plot and boxplot of the data indicate that the differences are approximately normally distributed with no outliers.

(a) Whether the student had unimpaired vision or wore goggles first was randomly selected. Why is this a good idea in designing the experiment?

A.This is a good idea in designing the experiment because the sample size is not large enough.

B. This is a good idea in designing the experiment because it controls for any "learning" that may occur in using the simulator.

C. This is a good idea in designing the experiment because reaction times are different.

(b) Use a 95% confidence interval to test if there is a difference in braking time with impaired vision and normal vision where the differences are computed as "impaired minus normal."

(b) The lower bound is _____?

The upper bound is _____?

(Round to the nearest thousandth as needed.)

A.There is sufficient evidence to conclude there is a difference in braking time with impaired vision and normal vision.

B. There is insufficient evidence to conclude there is a difference in braking time with impaired vision and normal vision.

Data Table
Subject
Normal, X
2 3 4 5 6 7 8 9
4.56 4.31 4.83 4.55 5.00 4.79
1
4.49 4.24 4.58
Impaired, Yi 5.77
5.85
5.45
5.32 5.90 5.49 5.23 5.61 5.63

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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