Answered: A normal probability plot suggests 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

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A normal probability plot suggests the data could come from a population that is normally distributed. A boxplot does not show any outliers. Does the sample evidence suggest that calcium concentrations have changed since

1990?

Use the

a=0.01

level of significance.

mg
Calcium is essential to tree growth. In 1990, the concentration of calcium in precipitation in Chautauqua, New York, was 0.11 milligram per liter
A random sample of 8 precipitation dates in 2018 results in the following data:
0.234
0.065
0.262
0.120
0.108
0.070
0.183
0.313
%D
A normal probability plot suggests the data could come from a population that is normally distributed. A boxplot does not show any outliers. Does the sample evidence suggest that calcium concentrations have changed since 1990? Use the
a = 0.01 level of significance.
What are the null and alternative hypotheses?
Ho:
H1:
(Type integers or decimals. Do not round.)
Find the test statistic.
to
|(Round to two decimal places as needed.)
Find the P-value.
P-value =
(Round to three decimal places as needed.)
Is there sufficient evidence that calcium concentrations have changed since 1990?
Since P-value
a,
the null hypothesis and conclude that there
sufficient evidence that the calcium level in rainwater has changed.

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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