Answered: A company manufactures light bulbs. The…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Related questions

Question

A company manufactures light bulbs. The company wants the bulbs to have a mean life span of

994

hours. This average is maintained by periodically testing random samples of

light bulbs. If the t-value falls between

−t0.99

and

t0.99,

then the company will be satisfied that it is manufacturing acceptable light bulbs. For a random sample, the mean life span of the sample is

1002

hours and the standard deviation is

hours. Assume that life spans are approximately normally distributed. Is the company making acceptable light bulbs? Explain.

A company manufactures light bulbs. The company wants the bulbs to have a mean life span of 994 hours. This
average is maintained by periodically testing random samples of 25 light bulbs. If the t-value falls between - to.99 and
to.99, then the company will be satisfied that it is manufacturing acceptable light bulbs. For a random sample, the
mean life span of the sample is 1002 hours and the standard deviation is 22 hours. Assume that life spans are
approximately normally distributed. Is the company making acceptable light bulbs? Explain.
The company
making acceptable light bulbs because the t-value for the sample is t =
(Round to two decimal places as needed.)
and to.99
-0.
=

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.

Expert Solution