Data Science Quiz For Humanities

Test your skills with this interactive data science quiz covering statistics, Python, R, and data analysis. Progress Answered 0 of 15 1Which 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 2What 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 3In Python, which library is most commonly used for data manipulation? matplotlib numpy pandas statsmodels 4Which metric is best for evaluating a classification model on imbalanced data? Accuracy Recall Variance R-squared 5In a linear regression, what does R² represent? Slope of the regression line Variance explained by the model Covariance between variables Degree of overfitting 6In 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 7What does the groupby() function do in pandas? Sorts values by category Applies aggregate operations to subsets of data Removes duplicates Normalizes columns 8What 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 9Feature engineering refers to: Training a model with more iterations Preparing input variables to improve model performance Removing outliers Selecting the best model 10Which visualization is most appropriate for the distribution of a continuous variable? Bar chart Histogram Pie chart Line plot 11A 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 12Which is an advantage of using R for statistical analysis? Native GPU acceleration Strong statistical libraries and ggplot2 Automatic machine learning Faster than Python 13Normalization in data preprocessing means: Converting categorical data to numeric Rescaling values to a standard range like 0–1 Detecting outliers Filling missing values 14Why may historical datasets be biased? They always include all records Selective or incomplete record-keeping Automatic modern data collection Perfect measurement systems 15Which Python function can compute a z-score? pandas.normalize() scipy.stats.zscore() numpy.z() matplotlib.stats() Submit Quiz Try again

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Data Science Quiz For Humanities

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