Unit 1: Data preprocessing and visualization - Practice Quiz

BTY587 — Data Analysis And Simulations 60 Questions
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1 Which of the following is an example of categorical (qualitative) data?

types of data Easy
A. Temperature in Celsius
B. Height of a person in cm
C. Number of cars sold
D. Blood type of a patient

2 Data that can only take specific separate values, such as the number of students in a class, is called:

types of data Easy
A. Ordinal data
B. Continuous data
C. Discrete data
D. Nominal data

3 A ranking of customer satisfaction as poor, average, good, excellent is an example of which data type?

types of data Easy
A. Nominal data
B. Interval data
C. Ratio data
D. Ordinal data

4 Which scale of measurement has a true zero point?

types of data Easy
A. Interval scale
B. Ordinal scale
C. Ratio scale
D. Nominal scale

5 Replacing a missing numeric value with the average of the available values is known as:

dealing with missing data Easy
A. Encoding
B. Normalization
C. Mean imputation
D. Deletion

6 Removing all rows that contain any missing values is referred to as:

dealing with missing data Easy
A. Mean imputation
B. Listwise deletion
C. Standardization
D. Interpolation

7 In many datasets, missing values are commonly represented by which of the following?

dealing with missing data Easy
A. Median
B. Mean
C. NaN
D. Mode

8 Which technique estimates a missing value using neighboring known data points, often in a sequence?

dealing with missing data Easy
A. Deletion
B. Binning
C. Interpolation
D. One-hot encoding

9 A scatter plot is primarily used to show the relationship between:

scatter plot Easy
A. A single category
B. Two numeric variables
C. Frequencies of a category
D. One variable over time only

10 In a scatter plot, if points rise together from lower-left to upper-right, the relationship is:

scatter plot Easy
A. Perfectly random
B. No correlation
C. Positive correlation
D. Negative correlation

11 Each individual point in a scatter plot represents:

scatter plot Easy
A. A category label
B. The mean of the dataset
C. One observation with two values
D. A single frequency count

12 A histogram is mainly used to display the:

histogram Easy
A. Relationship between two variables
B. Change of trend over regions
C. Ranking of categories
D. Distribution of a numeric variable

13 The intervals into which data is grouped in a histogram are called:

histogram Easy
A. Nodes
B. Points
C. Cells
D. Bins

14 How does a histogram differ from a bar chart?

histogram Easy
A. Histograms only show categories
B. Histograms cannot show frequencies
C. Histogram bars are for continuous data and touch
D. Histogram bars always have gaps

15 Group plots are most useful for:

group plots Easy
A. Showing a single value only
B. Reducing dimensions
C. Encoding missing data
D. Comparing data across multiple groups

16 A grouped bar chart is typically used to compare:

group plots Easy
A. A single continuous distribution
B. Correlation between two variables
C. Values across categories and subgroups
D. Missing value counts only

17 The line inside the box of a box plot represents the:

box plots Easy
A. Median
B. Mean
C. Maximum
D. Range

18 In a box plot, points that fall far outside the whiskers are typically identified as:

box plots Easy
A. Medians
B. Outliers
C. Quartiles
D. Modes

19 The height of the box in a box plot represents the:

box plots Easy
A. Total range
B. Standard deviation
C. Interquartile range (IQR)
D. Mean value

20 What is the main goal of dimensionality reduction?

dimensionality reduction Easy
A. Delete all missing values
B. Reduce the number of features while keeping key information
C. Increase the number of features
D. Sort data alphabetically

21 A dataset records customer satisfaction as Poor, Average, Good, and Excellent. Which data type best describes this variable?

types of data Medium
A. Continuous numerical
B. Nominal categorical
C. Discrete numerical
D. Ordinal categorical

22 Temperature measured in degrees Celsius is an example of which measurement scale?

types of data Medium
A. Ordinal scale
B. Nominal scale
C. Interval scale
D. Ratio scale

23 You encode the number of children per household as . How should this variable be classified?

types of data Medium
A. Discrete numerical
B. Continuous numerical
C. Nominal categorical
D. Ordinal categorical

24 A numerical column has a strongly right-skewed distribution with several outliers, and about 5% of values are missing. Which imputation choice is most appropriate?

dealing with missing data Medium
A. Impute with the median
B. Impute with the mean
C. Delete all rows with any missing value
D. Replace missing values with zero

25 Values are missing more often for low-income respondents who chose not to report income. This missingness mechanism is best described as:

dealing with missing data Medium
A. Structurally missing
B. Missing Not At Random (MNAR)
C. Missing At Random (MAR)
D. Missing Completely At Random (MCAR)

26 A feature is missing in 78% of records and is weakly related to the target. What is usually the most sensible action?

dealing with missing data Medium
A. Impute with the column mean
B. Fill all missing entries with the mode
C. Impute using KNN on the few present values
D. Drop the entire column

27 A scatter plot of two variables shows points tightly clustered along a line that falls from top-left to bottom-right. What does this indicate?

scatter plot Medium
A. No correlation
B. Strong negative correlation
C. Strong positive correlation
D. A perfect nonlinear relationship

28 You want to visualize the relationship between two numeric variables while also encoding a third numeric variable. Which scatter plot enhancement is most appropriate?

scatter plot Medium
A. Increase the marker transparency uniformly
B. Vary the marker size (bubble chart)
C. Add horizontal grid lines
D. Sort the points along the x-axis

29 In a large scatter plot, many points overlap and hide the true density of data. Which technique best addresses this overplotting?

scatter plot Medium
A. Reduce the axis range
B. Change the marker color to red
C. Remove the axis labels
D. Use transparency (alpha blending)

30 A histogram built with too many narrow bins appears jagged and noisy. What is the primary effect of increasing the bin width?

histogram Medium
A. It changes the total count of observations
B. It converts the histogram into a box plot
C. It smooths the distribution but may hide fine detail
D. It always reveals more detail in the data

31 A histogram shows most values bunched on the left with a long tail extending to the right. How is this distribution described?

histogram Medium
A. Left-skewed (negatively skewed)
B. Right-skewed (positively skewed)
C. Uniform
D. Symmetric

32 Which statement correctly distinguishes a histogram from a bar chart?

histogram Medium
A. A histogram requires sorted data, while a bar chart does not
B. A histogram displays continuous data in bins, while a bar chart displays categorical counts
C. A histogram can only show two variables, while a bar chart shows one
D. A histogram always has gaps between bars, unlike a bar chart

33 You want to compare the distribution of test scores across five different schools on a single figure. Which grouped visualization is most suitable?

group plots Medium
A. Side-by-side box plots grouped by school
B. A single scatter plot of all scores
C. A pie chart of average scores
D. A single histogram of all scores combined

34 A faceted (small-multiples) plot arranges several subplots that share the same axes. What is its main advantage?

group plots Medium
A. It combines all groups into one aggregated curve
B. It reduces the total number of data points shown
C. It automatically removes outliers from each panel
D. It allows direct visual comparison across subgroups on identical scales

35 When using a grouped bar chart to compare two categories across several months, what does color (hue) typically encode?

group plots Medium
A. The order of the months on the x-axis
B. The total sum across all months
C. The confidence interval of each bar
D. The category being compared within each month

36 In a standard box plot, the length of the box itself represents which quantity?

box plots Medium
A. The full range (max min)
B. The mean absolute deviation
C. The interquartile range ()
D. The standard deviation

37 Using the common rule, a point is flagged as an outlier if it lies:

box plots Medium
A. More than two bin widths from the mode
B. Below or above
C. Below the median by more than one standard deviation
D. Outside the range to

38 A box plot has , median , and . What does the position of the median inside the box suggest?

box plots Medium
A. The data has no variability
B. The data is left-skewed
C. The data is perfectly symmetric
D. The data is right-skewed

39 In Principal Component Analysis (PCA), the first principal component is chosen so that it:

dimensionality reduction Medium
A. Minimizes the number of features in the dataset
B. Aligns exactly with the original first feature axis
C. Maximizes the correlation between original features
D. Captures the direction of maximum variance in the data

40 Why is it generally recommended to standardize features before applying PCA?

dimensionality reduction Medium
A. To increase the number of principal components
B. To prevent features with larger scales from dominating the components
C. To guarantee the data becomes perfectly normal
D. To remove all correlations before analysis

41 A researcher encodes customer satisfaction as where the gaps between adjacent levels are not guaranteed to be equal. A colleague computes the arithmetic mean and standard deviation of this variable. What is the most defensible critique?

types of data Hard
A. The variable is ratio, so a geometric mean should have been used instead
B. The variable is ordinal, so the mean and SD assume interval spacing that may not hold
C. The variable is interval, so only the mode is a valid summary statistic
D. The variable is nominal, so even the median is undefined for it

42 Temperature in Celsius and temperature in Kelvin describe the same physical quantity. Which statement correctly distinguishes their measurement scales?

types of data Hard
A. Both are ratio scales, so ratios are meaningful in either scale
B. Both are interval scales, so ratios are meaningless in either scale
C. Celsius is ratio and Kelvin is interval, so ratios are meaningful only in Celsius
D. Celsius is interval and Kelvin is ratio, so ratios are meaningful only in Kelvin

43 In a dataset, income is missing more often for high earners because wealthy respondents decline to answer. The missingness depends on the unobserved income value itself. This mechanism is best classified as:

dealing with missing data Hard
A. MNAR (Missing Not At Random)
B. MAR (Missing At Random)
C. MCAR (Missing Completely At Random)
D. Ignorable missingness under listwise deletion

44 A data scientist replaces all missing values in a feature with the column mean before computing the sample variance. What is the primary distortion introduced?

dealing with missing data Hard
A. The correlation with other variables increases artificially
B. The variance is systematically overestimated because imputed values inflate the range
C. The variance is systematically underestimated because imputed values add no spread
D. The mean shifts toward the imputed values, biasing central tendency

45 Compared to single imputation, why does multiple imputation with imputed datasets produce more valid standard errors?

dealing with missing data Hard
A. It always reduces total variance by averaging out random noise across datasets
B. It replaces missing values with the most frequent observed value times
C. It guarantees unbiased estimates even under MNAR mechanisms
D. It incorporates between-imputation variance, reflecting uncertainty about the missing values

46 Two variables have Pearson correlation , yet a scatter plot shows a clear parabolic pattern. What is the correct interpretation?

scatter plot Hard
A. A log transform of both axes would restore a high linear
B. A strong nonlinear relationship exists that Pearson's fails to capture
C. The variables are statistically independent since
D. The scatter plot must contain a data entry error

47 When plotting 500,000 points where many overlap, a scatter plot becomes a solid ink blob (overplotting). Which technique best preserves density information?

scatter plot Hard
A. Use a 2D density/hexbin plot mapping counts to color intensity
B. Connect the points with lines sorted by x-value
C. Plot only the first 100 rows to reduce clutter
D. Increase the marker size so points are easier to see individually

48 A histogram of the same data looks unimodal with 10 bins but bimodal with 40 bins. What does this most likely indicate?

histogram Hard
A. The 10-bin version is always correct because fewer bins reduce error
B. Bin width strongly affects the visual, and the extra modes may be noise or genuine structure needing further checks
C. Histograms are unreliable and a pie chart should be used instead
D. The data are definitively bimodal since more bins reveal more truth

49 Using the Freedman–Diaconis rule, bin width is . For a sample with and , what is the approximate bin width?

histogram Hard
A.
B.
C.
D.

50 A right-skewed variable is plotted as a histogram, then re-plotted after a transform. What effect is most expected in the transformed histogram?

histogram Hard
A. The left tail is stretched, increasing the skew further
B. The number of modes always increases after the transform
C. The distribution becomes exactly uniform across all bins
D. The right tail is compressed, making the distribution appear more symmetric

51 You facet (small-multiple) a scatter plot by a categorical grouping variable across 6 panels. What is the key advantage of a shared common axis range across all panels?

group plots Hard
A. It removes the need to label the axes on individual panels
B. It forces every group to display the same number of points
C. It guarantees each panel uses the maximum possible resolution
D. It allows direct visual comparison of magnitudes and positions across groups

52 A grouped (clustered) bar chart shows category means for three groups but omits any uncertainty indicators. What is the most serious analytical limitation?

group plots Hard
A. Bar charts cannot represent means, only counts, so the plot is invalid
B. Clustered bars always exaggerate the largest group's value
C. Differences between group means cannot be judged for significance without variability information
D. The chart implies a time ordering that does not exist

53 Using the standard rule with and , at what upper value does a point begin to be flagged as an outlier?

box plots Hard
A. Above
B. Above
C. Above
D. Above

54 Two box plots have identical medians, quartiles, and whisker lengths, yet their underlying distributions differ dramatically (one bimodal, one unimodal). What limitation does this reveal?

box plots Hard
A. The two box plots must actually be identical if all summaries match
B. Box plots summarize quantiles and cannot reveal multimodality or internal shape
C. Box plots always misrepresent the median for bimodal data
D. Box plots overstate variability when data are bimodal

55 A notched box plot is used to compare two groups. If the notches of the two boxes do not overlap, the most appropriate conclusion is:

box plots Hard
A. The two distributions must both be perfectly symmetric
B. There is roughly 95% confidence evidence that the true medians differ
C. The two groups have identical medians with certainty
D. The variances of the two groups are proven to be equal

56 Before applying PCA to features measured in wildly different units (e.g., meters and kilograms), why is standardization typically required?

dimensionality reduction Hard
A. PCA maximizes variance, so unstandardized high-variance features dominate the components
B. Standardization makes the covariance matrix singular, simplifying the math
C. PCA requires all features to be strictly positive to compute eigenvalues
D. Without it, PCA cannot handle more than two features at once

57 The eigenvalues of a covariance matrix are . What proportion of total variance is explained by the first two principal components?

dimensionality reduction Hard
A.
B.
C.
D.

58 A key difference between PCA and t-SNE for visualization is that:

dimensionality reduction Hard
A. Both preserve exact pairwise distances identically
B. t-SNE is a linear method and PCA is nonlinear
C. t-SNE preserves local neighborhood structure but distorts global distances and cluster sizes
D. PCA preserves local structure while t-SNE preserves global linear structure

59 When choosing the number of components via a scree plot, the 'elbow' heuristic suggests keeping components:

dimensionality reduction Hard
A. Up to the point where the eigenvalue drop levels off sharply
B. All components until cumulative variance reaches 100%
C. Only those with eigenvalues exactly equal to zero
D. The single component with the smallest eigenvalue

60 In a scatter plot of study hours vs. exam score, adding a third variable (course difficulty) reverses the apparent positive trend within each course subgroup. This is an example of:

scatter plot Hard
A. Overplotting due to too many data points
B. Heteroscedasticity in the residual variance
C. A ceiling effect on the exam score variable
D. Simpson's paradox, where aggregated and subgroup trends conflict