Data Science Quiz For Humanities

Which of the following best describes a z-score?

A measure of central tendency
The number of standard deviations a value is from the mean
The square of the correlation coefficient
A type of probability distribution

What is the main advantage of using tidy data principles in R?

Increased computation speed
Easier visualization and consistent analysis
Reduced memory usage
Automatically removes missing values

In Python, which library is most commonly used for data manipulation?

matplotlib
numpy
pandas
statsmodels

Which metric is best for evaluating a classification model on imbalanced data?

Accuracy
Recall
Variance
R-squared

In a linear regression, what does R² represent?

Slope of the regression line
Variance explained by the model
Covariance between variables
Degree of overfitting

In historical or humanities datasets, which challenge occurs most frequently?

Excessively large sample sizes
Perfectly standardized variable names
Missing or incomplete records
Highly structured relational databases

What does the groupby() function do in pandas?

Sorts values by category
Applies aggregate operations to subsets of data
Removes duplicates
Normalizes columns

What is the primary purpose of cross-validation?

Increase training accuracy
Test different loss functions
Evaluate a model on unseen data to reduce overfitting
Speed up model training

Feature engineering refers to:

Training a model with more iterations
Preparing input variables to improve model performance
Removing outliers
Selecting the best model

Which visualization is most appropriate for the distribution of a continuous variable?

Bar chart
Histogram
Pie chart
Line plot

A z-score of +2.5 means:

The value is below the mean
The value is 2.5 SD above the mean
The value is an outlier
The standard deviation is 2.5

Which is an advantage of using R for statistical analysis?

Native GPU acceleration
Strong statistical libraries and ggplot2
Automatic machine learning
Faster than Python

Normalization in data preprocessing means:

Converting categorical data to numeric
Rescaling values to a standard range like 0–1
Detecting outliers
Filling missing values

Why may historical datasets be biased?

They always include all records
Selective or incomplete record-keeping
Automatic modern data collection
Perfect measurement systems

Which Python function can compute a z-score?

pandas.normalize()
scipy.stats.zscore()
numpy.z()
matplotlib.stats()

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Data Science Quiz For Humanities

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