A new drug that has been on the market for only a few months is now being recalled because certain people are suffering severe side effects. Which of the following is a possbile statistical explanation from the clinical trials for this observation in the real world? a.The average (mean) effectiveness of the drug was lower than not taking the drug in trials b.The sample of the population in trials was not representative of all people taking the drug. c.The mean and median effectiveness were equal in clinical trials d.The percentage distribution of people taking the drug correctly in trials is normally distributed

Answered: A new drug that has been on the market…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A new drug that has been on the market for only a few months is now being recalled because certain people are suffering severe side effects. Which of the following is a possbile statistical explanation from the clinical trials for this observation in the real world?

	a.	The average (mean) effectiveness of the drug was lower than not taking the drug in trials
	b.	The sample of the population in trials was not representative of all people taking the drug.
	c.	The mean and median effectiveness were equal in clinical trials
	d.	The percentage distribution of people taking the drug correctly in trials is normally distributed

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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