Which algorithm is best suited for a binary classification problem, such as predicting whether an email is spam or not?

Principal Component Analysis (PCA)

A data analyst is building a classifier to predict customer churn. The dataset has 10,000 records with a churn rate of 8%. To evaluate model generalization, the analyst splits the data into training and test sets. Which approach is most appropriate?

Use all data for training and evaluate on the same data.

Use stratified splitting to preserve the 8% churn proportion in both training and test sets.

Perform a random 80/20 split without any stratification.

Split the data so that the test set contains only churn cases.

A data analyst has a pandas DataFrame `df` with a column `age`. They want to compute the standard deviation and interquartile range (IQR) of this column. Which code snippet accomplishes this?

np.std(df['age']) and np.percentile(df['age'], 50)

df['age'].var() and df['age'].median()

df['age'].std() and df['age'].quantile(0.75) - df['age'].quantile(0.25)

df['age'].describe() and df['age'].mad()

Python InstitutePCAD - Certified Associate in Data Analytics with Python

Domain 4Objective 2

Statistical Methods and Machine Learning PCAD-31 Practice Questions (Page 4)

Part of the Data Analysis and Modeling domain, which accounts for 18.8% of the PCAD-31 exam. Python Institute does not publish an official question count, but from its 60-minute exam (~25–40 total, ~5–5 in this domain), expect 3–3 from this objective — we provide 30 practice questions to prepare you well beyond it. (estimate)

30questions here

6free pages

9concepts

18.8%of the exam

Questions 16–20

16foundation · easy
Which plot is most appropriate to visualize the distribution of a single numeric variable and identify potential outliers?
Select an answer first
17foundation · easy
Which algorithm is best suited for a binary classification problem, such as predicting whether an email is spam or not?
Select an answer first
18application · medium
A data analyst is building a classifier to predict customer churn. The dataset has 10,000 records with a churn rate of 8%. To evaluate model generalization, the analyst splits the data into training and test sets. Which approach is most appropriate?
Select an answer first
19foundation · easy
Which regression metric measures the average absolute difference between predicted and actual values?
Select an answer first
20application · medium
A data analyst has a pandas DataFrame `df` with a column `age`. They want to compute the standard deviation and interquartile range (IQR) of this column. Which code snippet accomplishes this?
Select an answer first

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Statistical Methods and Machine Learning PCAD-31 Practice Questions (Page 4)

Questions 16–20

Which plot is most appropriate to visualize the distribution of a single numeric variable and identify potential outliers?

Which algorithm is best suited for a binary classification problem, such as predicting whether an email is spam or not?

A data analyst is building a classifier to predict customer churn. The dataset has 10,000 records with a churn rate of 8%. To evaluate model generalization, the analyst splits the data into training and test sets. Which approach is most appropriate?

Which regression metric measures the average absolute difference between predicted and actual values?

A data analyst has a pandas DataFrame `df` with a column `age`. They want to compute the standard deviation and interquartile range (IQR) of this column. Which code snippet accomplishes this?

Keep studying — Data Analysis and Modeling