A farmer wants to test if a new fertilizer will produce more massive crops. In order to do this, he randomly gathers the masses of several types of crops from the last growing season and the current growing season and compares them to see if the current growing season’s crops are more massive. Find the test statistic and degrees of freedom for an appropriate hypothesis test using the data set below. Let the difference d for each crop be computed as d=current year−previous year. Assume that the masses are normally distributed. Round the test statistic to three decimal places. Crop Previous Year Mass (grams) Current Year Mass (grams)Tomato 180.4 182.1Apple 130.9 130.2Potato 162.1 165.7Carrot 61.9 65.1Cucumber 198.4 200.2Onion 108.5 106.1

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Description: A farmer wants to test if a new fertilizer will produce more massive crops. In order to do this, he randomly gathers the masses of several types of crops from the last growing season and the current growing season and compares them to see if the curr

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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A farmer wants to test if a new fertilizer will produce more massive crops. In order to do this, he randomly gathers the masses of several types of crops from the last growing season and the current growing season and compares them to see if the current growing season’s crops are more massive. Find the test statistic and degrees of freedom for an appropriate hypothesis test using the data set below. Let the difference d for each crop be computed as d=current year−previous year. Assume that the masses are normally distributed. Round the test statistic to three decimal places.

Crop Previous Year Mass (grams) Current Year Mass (grams)
Tomato 180.4 182.1
Apple 130.9 130.2
Potato 162.1 165.7
Carrot 61.9 65.1
Cucumber 198.4 200.2
Onion 108.5 106.1

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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