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A.
na.rm = TRUE
B.
missing = FALSE
C.
drop = TRUE
D.
complete = 1
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Correct Answer: A. na.rm = TRUE
Explanation:
Setting na.rm to TRUE removes NA values for the calculation.
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A.
A vector with missing values removed
B.
The mean of nonmissing values
C.
A count of unique values
D.
A logical vector indicating which elements of x are missing
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Correct Answer: D. A logical vector indicating which elements of x are missing
Explanation:
is.na() tests each element for the NA missing-value marker.
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A.
==
B.
%in%
C.
<-
D.
:
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Correct Answer: C. <-
Explanation:
The assignment operator stores the value on the right in the name on the left.
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A.
A 3-by-3 matrix
B.
A numeric vector containing 2, 4, and 6
C.
A logical comparison
D.
A character factor
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Correct Answer: B. A numeric vector containing 2, 4, and 6
Explanation:
The c() function combines its arguments into a vector.
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A.
str()
B.
plot()
C.
rm()
D.
setwd()
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Correct Answer: A. str()
Explanation:
The str() function gives a compact description of an object's components and types.
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A.
The first three elements of x
B.
All elements except the third
C.
The length of x
D.
The third element of x
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Correct Answer: D. The third element of x
Explanation:
Square brackets select elements by position or condition.
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A.
An atomic vector
B.
A scalar constant
C.
A data frame
D.
A single factor level
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Correct Answer: C. A data frame
Explanation:
A data frame organizes observations in rows and variables in columns.
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A.
A data frame
B.
An atomic vector
C.
A list
D.
A formula object
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Correct Answer: B. An atomic vector
Explanation:
An atomic vector contains values of one common type, such as numeric or character.
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A.
Simpson's paradox
B.
The central limit theorem
C.
Perfect multicollinearity
D.
Random number seeding
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Correct Answer: A. Simpson's paradox
Explanation:
Simpson's paradox occurs when an aggregate association differs from subgroup associations.
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A.
It is only used after all analysis is complete
B.
It replaces statistical reasoning
C.
It is required only for image data
D.
It supports both discovery during analysis and communication of findings
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Correct Answer: D. It supports both discovery during analysis and communication of findings
Explanation:
Visualizations help analysts inspect data and detect patterns during exploration.
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A.
Randomness
B.
Statistical power
C.
Legibility
D.
Sampling independence
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Correct Answer: C. Legibility
Explanation:
Legibility concerns whether text and marks can be perceived without confusion.
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A.
They eliminate the need for data cleaning
B.
They enable consistent comparison across subsets using repeated scales
C.
They combine all variables into one number
D.
They guarantee equal variances
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Correct Answer: B. They enable consistent comparison across subsets using repeated scales
Explanation:
Small multiples repeat the same chart design for different groups or periods.
