An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
13th Edition
ISBN: 9781461471370
Author: Gareth James
Publisher: SPRINGER NATURE CUSTOMER SERVICE
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Chapter 4, Problem 7E
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Probability estimation
- It suffices to plug in the parameters and X values in the equation for pk(x).\
- Hence the equation will be
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In a recent study on world happiness, participants were asked to evaluate their current lives on a scale from 0 to 10, where O represents the worst possible life and 10
represents the best possible life. The responses were normally distributed, with a mean of 5.3 and a standard deviation of 1.9. Answer parts (a)-(d) below.
(a) Find the probability that a randomly selected study participant's response was loss than 4.
The probability that a randomly selected study participant's response was lons than 4 is (Round to four decimal placos as needed.)
In linear regression, 8 tells us how meaningful
the corresponding x is in predicting the output.
This means, ......
O if a particular 8-value is very small
compared to others, the corresponding x
plays a little role in predicting the output.
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The task is to implement density estimation using the K-NN method. Obtain an iidsample of N ≥ 1 points from a univariate normal (Gaussian) distribution (let us callthe random variable X) centered at 1 and with variance 2. Now, empirically obtain anestimate of the density from the sample points using the K-NN method, for any valueof K, where 1 ≤ K ≤ N. Produce one plot for each of the following cases (each plotshould show the following three items: the N data points (instances or realizations ofX) and the true and estimated densities versus x for a large number – e.g., 1000, 10000– of discrete, linearly-spaced x values): (i) K = N = 1, (ii) K = 2, N = 10, (iii) K = 10,N = 10, (iv) K = 10, N= 1000, (v) K = 100, N= 1000, (vi) K = N = 50,000. Pleaseprovide appropriate axis labels and legends. Thus there should be a total of six figures(plots),
Chapter 4 Solutions
An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
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