The manufacturer of LED lights would like to include as part of their advertising the number of hours an LED is expected to work. A sample of 20 lights revealed the following number of hours worked. 2698 2628 2474 2895 2672 2675 2486 2852 2733 26552765 2794 2486 2627 2624 2785 2692 2654 2518 2650 Draw normal probability plot for the above data and make comment.Assuming given data to be approximately normally distributed, Construct 90%, 95% and 99% confidence intervals for the mean number of hours that the LED lights of this brand has worked.Construct 90%, 95% and 99% confidence intervals for the standard deviation of the number of hours that the LED lights of this brand worked.

Name: The manufacturer of LED lights would like to include as part of their
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Description: The manufacturer of LED lights would like to include as part of their advertising the number of hours an LED is expected to work. A sample of 20 lights revealed the following number of hours worked. 2698 2628 2474 2895 2672 2675 248

1. The normal probability plot for the given data is

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MATLAB: An Introduction with Applications

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The manufacturer of LED lights would like to include as part of their advertising the number of hours an LED is expected to work. A sample of 20 lights revealed the following number of hours worked.

2698 2628 2474 2895 2672 2675 2486 2852 2733 2655

2765 2794 2486 2627 2624 2785 2692 2654 2518 2650

Draw normal probability plot for the above data and make comment.
Assuming given data to be approximately normally distributed, Construct 90%, 95% and 99% confidence intervals for the mean number of hours that the LED lights of this brand has worked.
Construct 90%, 95% and 99% confidence intervals for the standard deviation of the number of hours that the LED lights of this brand worked.

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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