Free PCAD – Certified Associate Data Analyst with Python Practice Questions

Sample Practice Questions

Try these 10 sample questions from the PCAD – Certified Associate Data Analyst with Python practice bank. Each includes the answer and explanation. Continue with the interactive practice above to review the full question set.

1. 1An analyst wants interview participants to describe their reasons for abandoning an application in their own words. Which question format produces the requested qualitative data?

   1. A. An open-ended question inviting a personal explanation
   2. B. A closed-ended question offering predefined reasons
   3. C. A numeric rating question using a five-point scale
   4. D. A binary choice question recording yes or no

   Answer: A

   Explanation: CDC states, "Qualitative questions are open-ended, that is, the respondent provides a response in his or her own words." An open-ended explanation captures the requested reasons without restricting responses to preset categories.

   Reference: Data Collection Methods for Program Evaluation: Interviews — Page 1, What is an interview?

2. 2What list does list(range(2, 8, 2)) produce in Python 3?

   1. A. [2, 4, 6, 8]
   2. B. [0, 2, 4, 6]
   3. C. [2, 4, 6]
   4. D. [2, 3, 4, 5, 6, 7]

   Answer: C

   Explanation: The tutorial states, "The given end point is never part of the generated sequence". Starting at 2 and stepping by 2 yields 2, 4, 6; the stop value 8 is excluded.

   Reference: Python Tutorial: More Control Flow Tools — 4.3 The range() Function

3. 3An income dataset contains a few extremely high observations. An analyst wants a measure of central location that is less affected by those outliers than the arithmetic mean. Which measure fits?

   1. A. The maximum income
   2. B. The income range
   3. C. The median income
   4. D. The income variance

   Answer: C

   Explanation: The statistics documentation states, "The median is a robust measure of central location and is less affected by the presence of outliers." The maximum, range, and variance are not robust measures of central location.

   Reference: Python Standard Library: statistics — Function details, median

4. 4Which statement correctly distinguishes a pandas Series from a pandas DataFrame?

   1. A. A Series is two-dimensional; a DataFrame is one-dimensional
   2. B. A Series has no labels; a DataFrame cannot hold labels
   3. C. A Series holds only strings; a DataFrame holds only numbers
   4. D. A Series is one-dimensional; a DataFrame has rows and columns

   Answer: D

   Explanation: The guide defines "Series: a one-dimensional labeled array" and "DataFrame: a two-dimensional data structure". This distinguishes their dimensionality while allowing labels and multiple data types.

   Reference: 10 minutes to pandas — Basic data structures in pandas

5. 5An analyst wants to display the distribution of individual delivery times by dividing the numerical time axis into bins and showing the count in each bin. Which plot directly provides this representation?

   1. A. A scatterplot
   2. B. A correlation heatmap
   3. C. A histogram
   4. D. A time-series line plot

   Answer: C

   Explanation: The seaborn guide describes a histogram with "the count of observations falling within each bin" shown by bar height. That matches a univariate binned frequency distribution rather than paired observations, correlations, or values over time.

   Reference: Visualizing distributions of data — seaborn Tutorial — Plotting univariate histograms

6. 6A research team requires every interviewer to use exactly the same open-ended questions and probes in exactly the same order. Which interview approach matches that protocol?

   1. A. Informal conversational interviewing
   2. B. Semi-structured interviewing
   3. C. Standardized open-ended interviewing
   4. D. Unstructured exploratory interviewing

   Answer: C

   Explanation: CDC describes standardized open-ended interviews: "The interviewer is not allowed flexibility in the wording or order." This matches a fixed protocol; semi-structured and informal approaches permit variation.

   Reference: Data Collection Methods for Program Evaluation: Interviews — Page 1, three approaches to qualitative interviews

7. 7What value is printed by this Python code? count = 0 for value in [2, -1, 3]: if value < 0: continue count += value print(count)

   1. A. 5
   2. B. 4
   3. C. 2
   4. D. 0

   Answer: A

   Explanation: The tutorial says, "The continue statement continues with the next iteration of the loop". The negative value skips the addition, while 2 and 3 are added, producing 5. A break at the negative value would instead leave 2.

   Reference: Python Tutorial: More Control Flow Tools — 4.4 break and continue Statements

8. 8A dataset has Pearson's r = -0.92 between two nonconstant numerical variables. Which interpretation is supported by that value?

   1. A. A strong negative linear association
   2. B. A weak positive linear association
   3. C. An absence of any possible association
   4. D. A proven negative causal effect

   Answer: A

   Explanation: The documentation says Pearson r "takes values between -1 and +1. It measures the strength and direction of a linear relationship." A value close to -1 indicates a strong negative linear association; correlation alone does not establish causation.

   Reference: Python Standard Library: statistics — Function details, correlation

9. 9A DataFrame df has a sorted integer index [10, 20, 30, 40]. Which index labels are selected by df.loc[20:30]?

   1. A. [20]
   2. B. [20, 30]
   3. C. [30, 40]
   4. D. [10, 20, 30]

   Answer: B

   Explanation: The guide states, "For label slicing, both endpoints are included". loc therefore selects the rows labeled 20 and 30. It interprets the bounds as labels rather than positional offsets.

   Reference: 10 minutes to pandas — Selection by label

10. 10An analyst has paired numerical measurements of advertising spend and revenue for individual stores and wants each store to appear as one point. Which plot is appropriate for examining the relationship?

    1. A. A scatterplot of spend against revenue
    2. B. A histogram of revenue alone
    3. C. A boxplot summarizing spend alone
    4. D. A bar chart of the overall revenue total

    Answer: A

    Explanation: The seaborn guide says a scatterplot "depicts the joint distribution of two variables using a cloud of points, where each point represents an observation". Each store has a pair of values, so plotting those pairs preserves the relationship.

    Reference: Visualizing statistical relationships — seaborn Tutorial — Relating variables with scatter plots