Sampling Methods and Data Transformations Quiz

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Questions and Answers

Which property distinguishes a ratio attribute from other types of attributes?

  • Distinctness only
  • Distinctness, order, and addition
  • All four properties of distinctness, order, addition, and multiplication (correct)
  • Distinctness and order

What type of values do continuous attributes have?

  • Real numbers (correct)
  • Finite or countably infinite set
  • Integer values
  • Binary values

Which measure represents the middle value of a dataset?

  • Trimmed mean
  • Mean
  • Mode
  • Median (correct)

What is the empirical formula relating mean, mode, and median?

<p>$mean - mode = 3 \times (mean - median)$ (D)</p>
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Which type of attribute has distinctness and order properties but not addition?

<p>Ordinal attribute (A)</p>
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What distinguishes a discrete attribute from a continuous attribute?

<p>Having a finite or countably infinite set of values (B)</p>
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Which of the following statements about Euclidean distance is true?

<p>It is a special case of the Minkowski distance when the parameter $r$ is set to 2. (A)</p>
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In the context of dissimilarity measures, what is the significance of the upper limit?

<p>It varies depending on the dissimilarity measure used. (D)</p>
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Which of the following statements about the Minkowski distance is incorrect?

<p>It is only applicable to data with numerical attributes. (A)</p>
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Which of the following is a common property of distance measures like the Euclidean distance?

<p>The distance between two data objects is always greater than or equal to zero. (B)</p>
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In the context of dissimilarity measures, what does it mean when the dissimilarity between two data objects is low?

<p>The two data objects are highly similar or alike. (D)</p>
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Which of the following statements about the Minkowski distance is correct?

<p>It reduces to the Manhattan distance when the parameter $r$ is set to 1. (A)</p>
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In sampling with replacement, what is the key difference compared to sampling without replacement?

<p>The same object can be picked up more than once (D)</p>
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What is the key characteristic of stratified sampling?

<p>Splitting the data into several partitions and then drawing random samples from each partition (A)</p>
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What is the purpose of mapping data to a new space, such as through Fourier or wavelet transforms?

<p>To transform the data into a new representation that may reveal patterns or structures not visible in the original space (B)</p>
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What is the key difference between discretization using class labels and discretization without using class labels?

<p>Discretization using class labels divides the data into equal frequency bins, while discretization without class labels divides the data into equal interval width bins (A)</p>
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What is the purpose of attribute transformation, such as using simple functions like $x^k$, $\"\log(x)\"$, $e^x$, or $|x|$?

<p>To map the values of an attribute to a new set of replacement values, where each old value is identified with one of the new values (B)</p>
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If the income range is $12,000 to $98,000, and we want to normalize it to the range [0.0, 1.0], what is the normalized value of $73,600?

<p>0.716 (C)</p>
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