# ECE M148 Homework 1

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ECE M148 Homework 1
Introduction to Data Science

1. Consider the following data set A = {1, 1, 5, 9, 9}. What are the mean and median of
A? Now, consider B = {1, 1, 5, 9, 9, 11}. What are the mean and median of B? Using
the mean and median, compare A and B.
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2. In class, we discussed different ways to sample data. Explain in 1-2 sentences each the
(a) Random sampling
(b) Stratified sampling
(c) Systematic sampling
(d) Cluster sampling
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3. As discussed in class, many real-world datasets will contain missing or null values in
the data. List four different strategies you could reasonably use to address null values.
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4. Consider the following sampling scenarios and determine which type of sampling bias
(a) Bob is a wealthy CEO who thinks taxes are too high. To confirm this hypothesis,
he asks all his wealthy CEO friends their opinion.
(b) Sally is a teacher who wants to know how her class is performing. She sends out
a survey with the following question: ”Do you feel like you will get an A in the
course or are you failing?”
(c) Constantine wants to know people’s opinion about his website. He posts a survey
You may choose among the following options for the type of bias:
i) Response Bias
ii) Voluntary Bias
iii) Convenience Bias
iv) Under-coverage Bias
v) Over-coverage Bias
vi) Non-response bias
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5. Perform KNN Regression on the following data set for different values of K: (x, y) =
{(1, 1),(2, 4),(3.2, 6),(4, 3),(5, 2),(6, 2)}. Start by plotting the given points on a 2-D
grid and then fitting a KNN regressor for the different values of K:
Make sure to draw the regression plot from 0 to 7.
• K = 1
• K = 2
• K = 3
• K = 6
Contrast and compare your findings over various choices of K. Is a larger K always
better? Is K = 1 always better? Why or why not? Comment on what you think about
the KNN performing regression on all x < 1.
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