Suppose we are about to draw a sample from a normally distributed population, and find a confidence interval for the population mean. Which one of the following statements is true? Question 23 options: If we use a z value when calculating the interval, when we should be using t, the resulting interval will be wider than it should be. If the sample size is large (n > 30, say), we should always use the z method rather than the t approach. All else being equal, the larger the sample size the larger the margin of error. 95% of the observations in the sample will fall within the 95% confidence interval we calculate. A 95% confidence interval will be wider than the corresponding 90% interval calculated on the same data.

Answered: uppose we are about to draw a sample…

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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Suppose we are about to draw a sample from a normally distributed population, and find a confidence interval for the population mean. Which one of the following statements is true?

Question 23 options:

	If we use a z value when calculating the interval, when we should be using t, the resulting interval will be wider than it should be.
	If the sample size is large (n > 30, say), we should always use the z method rather than the t approach.
	All else being equal, the larger the sample size the larger the margin of error.
	95% of the observations in the sample will fall within the 95% confidence interval we calculate.
	A 95% confidence interval will be wider than the corresponding 90% interval calculated on the same data.

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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