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In [ ]: We obtained an array with N = 10 values, scattered about a mean of 25 (mm). Let's calculate the mean, standard deviation, standard deviation of the mean and 20-uncertainty &L of these numbers. In the following code, do these steps: • In the first cell, add a brief comment that explains what each statement does. Start each comment with a # sign. • In the second cell, delete the raise Not ImplementedError() code line and print the standard deviation and 20-uncertainty on the screen (follow the example for mean_L) In ] v mean_L = np.mean (L) print("Mean length: ", mean_L) stddev_L = np.std (L, ddof=1) stddev_mean_L = stddev_L/np.sqrt(N) uncertainty_L = 2*stddev_mean_L # YOUR CODE HERE raise NotImplementedError() #calculates the mean of L In the above code, the green expressions on the right hand side, such as np.mean, np. std and np.sqrt are functions built into the numpy package of

In [ ]: We obtained an array with N = 10 values, scattered about a mean of 25 (mm). Let's calculate the mean, standard deviation, standard deviation of the mean and 20-uncertainty &L of these numbers. In the following code, do these steps: • In the first cell, add a brief comment that explains what each statement does. Start each comment with a # sign. • In the second cell, delete the raise Not ImplementedError() code line and print the standard deviation and 20-uncertainty on the screen (follow the example for mean_L) In ] v mean_L = np.mean (L) print("Mean length: ", mean_L) stddev_L = np.std (L, ddof=1) stddev_mean_L = stddev_L/np.sqrt(N) uncertainty_L = 2*stddev_mean_L # YOUR CODE HERE raise NotImplementedError() #calculates the mean of L In the above code, the green expressions on the right hand side, such as np.mean, np. std and np.sqrt are functions built into the numpy package of

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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In [ ]: We obtained an array with N = 10 values, scattered about mean of 25 (mm). Let's calculate the mean, standard deviation, standard deviation of the mean and 20-uncertainty SL of these numbers. In the following code, do these steps: • In the first cell, add a brief comment that explains what each statement does. Start each comment with a # sign. • In the second cell, delete the raise Not ImplementedError() code line and print the standard deviation and 20-uncertainty on the screen (follow the example for mean_L) mean_L = np.mean (L) print("Mean length: ", mean_L) stddev_L = np. std (L, ddof=1) stddev_mean_L = stddev_L/np.sqrt(N) uncertainty_L = 2*stddev_mean_L In [ ] V #YOUR CODE HERE raise NotImplementedError() #calculates the mean of L In the above code, the green expressions on the right hand side, such as np.mean, np. std and np.sqrt are functions built into the numpy package of Python. The names on the left hand side are variable names invented by me.
Transcribed Image Text:In [ ]: We obtained an array with N = 10 values, scattered about mean of 25 (mm). Let's calculate the mean, standard deviation, standard deviation of the mean and 20-uncertainty SL of these numbers. In the following code, do these steps: • In the first cell, add a brief comment that explains what each statement does. Start each comment with a # sign. • In the second cell, delete the raise Not ImplementedError() code line and print the standard deviation and 20-uncertainty on the screen (follow the example for mean_L) mean_L = np.mean (L) print("Mean length: ", mean_L) stddev_L = np. std (L, ddof=1) stddev_mean_L = stddev_L/np.sqrt(N) uncertainty_L = 2*stddev_mean_L In [ ] V #YOUR CODE HERE raise NotImplementedError() #calculates the mean of L In the above code, the green expressions on the right hand side, such as np.mean, np. std and np.sqrt are functions built into the numpy package of Python. The names on the left hand side are variable names invented by me.
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In this question we have to write a code which should involves calculating statistical properties of an array L containing 10 values, where these values are scattered around a mean of 25 mm.

We have to calculate the mean, standard deviation, standard deviation of the mean, and the 2σ-uncertainty (δL) of these values using Python and the numpy package.

Let's code and hope this helps if you have any queries please utilize threaded questions feature.

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