Exploratory data analysis and descriptive statistics: Practice Questions — Descriptive Analysis and Visualization (NVIDIA-Certified Associate: Accelerated Data Science)

Practice Questions: Exploratory Data Analysis and Descriptive Statistics

This set of multiple-choice questions is designed to help candidates prepare for the NVIDIA-Certified Associate: Accelerated Data Science exam, focusing on exploratory data analysis (EDA) and descriptive statistics. Each question includes four options, the correct answer, and a brief explanation to reinforce key concepts.

1. Which of the following measures is most appropriate to describe the central tendency of a dataset with significant outliers?

   • A. Mean
   • B. Median
   • C. Mode
   • D. Range

   Answer: B. Median

   Explanation: The median is less affected by outliers than the mean, making it a better measure of central tendency for skewed data or data with outliers.

2. During exploratory data analysis, which plot is best suited to visualize the distribution and identify potential skewness of a continuous variable?

   • A. Scatter plot
   • B. Histogram
   • C. Bar chart
   • D. Box plot

   Answer: B. Histogram

   Explanation: Histograms display the frequency distribution of continuous data and help identify skewness and modality.

3. Which descriptive statistic quantifies the spread of data around the mean?

   • A. Variance
   • B. Median
   • C. Mode
   • D. Interquartile range

   Answer: A. Variance

   Explanation: Variance measures the average squared deviation from the mean, quantifying data spread.

4. In a dataset, the 25th percentile is also known as the:

   • A. Median
   • B. First quartile (Q1)
   • C. Third quartile (Q3)
   • D. Mode

   Answer: B. First quartile (Q1)

   Explanation: The 25th percentile corresponds to the first quartile, marking the value below which 25% of data fall.

5. Which of the following is NOT a typical step in exploratory data analysis?

   • A. Summarizing data using descriptive statistics
   • B. Building a predictive model without checking data quality
   • C. Visualizing data distributions
   • D. Identifying missing values and outliers

   Answer: B. Building a predictive model without checking data quality

   Explanation: EDA focuses on understanding and preparing data, not directly building models without prior data assessment.

6. Which measure is most appropriate to describe the most frequently occurring value in a categorical dataset?

   • A. Mean
   • B. Median
   • C. Mode
   • D. Variance

   Answer: C. Mode

   Explanation: The mode identifies the most common value in a dataset, especially useful for categorical variables.

7. When performing EDA, which plot helps to identify potential outliers and the spread of data simultaneously?

   • A. Scatter plot
   • B. Box plot
   • C. Line chart
   • D. Pie chart

   Answer: B. Box plot

   Explanation: Box plots visually summarize data distribution, showing median, quartiles, and potential outliers.

8. Which descriptive statistic is resistant to extreme values and provides a measure of spread?

   • A. Standard deviation
   • B. Range
   • C. Interquartile range (IQR)
   • D. Mean absolute deviation

   Answer: C. Interquartile range (IQR)

   Explanation: The IQR measures the spread of the middle 50% of data and is robust against outliers.

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