A scientist claims that pneumonia causes weight loss in mice. The table attached here shows the weights(in grams) of six mice before infection and two days after infection. At α = 0.01, is there enough evidence to support the scientist’s claim? Assume the samples are random anddependent, and the population is normally distributed.MouseWeight (Before)Weight (After)121.521.3223.823.8322.922.7420.820.7521.321.2621.721.7Calculate dbar (sample mean of the differences)and Sd(sample standard deviation of the differences) and decide whether to reject or fail to reject the null. Interpret the results in context of the claim and show all work.

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Description: A scientist claims that pneumonia causes weight loss in mice. The table attached here shows the weights(in grams) of six mice before infection and two days after infection. At α = 0.01, is there enough evidence to support the scientist’s claim? Assu

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MATLAB: An Introduction with Applications

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ISBN:9781119256830

Author:Amos Gilat

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A scientist claims that pneumonia causes weight loss in mice. The table attached here shows the weights(in grams) of six mice before infection and two days after infection. At α = 0.01, is there enough evidence to support the scientist’s claim? Assume the samples are random anddependent, and the population is normally distributed.

Mouse	Weight (Before)	Weight (After)
1	21.5	21.3
2	23.8	23.8
3	22.9	22.7
4	20.8	20.7
5	21.3	21.2
6	21.7	21.7

Calculate dbar (sample mean of the differences)and Sd(sample standard deviation of the differences) and decide whether to reject or fail to reject the null. Interpret the results in context of the claim and show all work.

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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