Python Institute PCED-30-01 Practice Exams
Last updated on Oct 22,2026- Exam Code: PCED-30-01
- Exam Name: Certified Entry-Level Data Analyst with Python
- Certification Provider: Python Institute
- Latest update: Oct 22,2026
Which Python library is commonly used for data manipulation and analysis in data pre-processing?
- A . NumPy
- B . Matplotlib
- C . Seaborn
- D . Pandas
Which of the following is a common approach for data modeling?
- A . Linear regression
- B . K-means clustering
- C . Principal component analysis (PCA)
- D . Random forest
What is the output of the following code snippet? “`python a = [1, 2, 3] b = a b.append(4) print(a) “`
- A . [1, 2, 3]
- B . [1, 2, 3, 4]
- C . [1, 2, 3, 4, 4]
- D . [1, 2, 3, 3]
What is the purpose of feature scaling in data analysis and modeling?
- A . To normalize the range of independent variables
- B . To make the model more interpretable
- C . To increase the number of features
- D . To improve the model’s accuracy
What type of plot is best used for showing the relationship between two continuous variables?
- A . Bar chart
- B . Line plot
- C . Scatter plot
- D . Pie chart
What is the result of the following expression in Python: 5 // 2?
- A . 2.5
- B . 2
- C . 3
- D . 2.0
In statistical analysis, what does p-value represent?
- A . The probability of committing a Type I error
- B . The probability of committing a Type II error
- C . The level of confidence in the hypothesis test
- D . The probability of getting the observed data if the null hypothesis is true
What is the process of collecting raw data from various sources before it is cleaned and transformed for analysis?
- A . Data Visualization
- B . Data Mining
- C . Data Acquisition
- D . Data Modeling
In data analytics, what does the term "feature engineering" refer to?
- A . Creating new features from existing data
- B . Removing features from the dataset
- C . Engineering the physical features of the data
- D . Analyzing features in detail
What is the primary goal of data preprocessing in the context of data analysis?
- A . To manipulate the data to achieve desired outcomes
- B . To analyze the data for insights and patterns
- C . To prepare the data for statistical analysis and modeling
- D . To visualize the data effectively for communication