Question

Question 3: Creating, modifying, and evaluating a variable Also, who are we kidding: while these are conceptual questions, they, too, are also coding questions! (a) You are studying the ages of students when they enroll at NYU (sorry to our non-NYU students for our NYU-centric-ness). You have a sample of five students. Three are 18, one is 17, and one is 19. Create a variable named ages that holds these values in a Numpy array in the order listed here. In): ages - (b) During your research, you discover that the age of the 17-year-old student was accidentally recorded incorrectly, and they are actually 18 years old. Write one line of code that edits ages to reflect this correction by changing the appropriate element. In 1: (c) Accidentally recording the wrong information, as was done in the previous question, is an example of what kind of measurement error? Type the letter of the option that represents your answer. A. Selection B. Random C. Operationalization D. Exclusion E. None of the above In )3e_answer - X

Answer 1

Solution -

(i) ages = np.array([18, 18, 18, 17, 19])

(ii) ages[3] = 18 (Changing the 4th array element which is at 3rd position in the array)

Explanation (just for understanding purpose) -

import numpy as np ages = np.array([18, 18, 18, 17, 19]) print ("Check array: ", ages) print ("****** *****") ages [3] - 18 print ("After changes: ", ages)

Output -

Check array: [18 18 18 17 19] After changes: [18 18 18 18 19]

(iii) Option E - None of the above ( as it is gross error)

(iv) Option B- It would bias the data downwards -- the ages in your sample would likely be lower than they really are

(as the students will not be willing admit that they got into NYU with higher ages)

(v) Option B Operationalize

(vi) Option C - Capture (i.e obtaining the measurable variable that is used for your research)

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