Practice Free PCED-30-01 Exam Online Questions
Which of the following Python libraries is commonly used for data manipulation and analysis?
- A . Pandas
- B . Matplotlib
- C . NumPy
- D . Scikit-learn
What is the primary purpose of data visualization in the field of data analytics?
- A . To make data look visually appealing
- B . To communicate insights and trends in data effectively
- C . To confuse the audience with complex charts
- D . To simply represent data without any analysis
What is the goal of data modeling in the field of data analytics?
- A . To organize data
- B . To analyze data
- C . To make predictions based on data
- D . To clean data
What is the purpose of feature scaling in data pre-processing?
- A . To create new features from existing ones
- B . To reduce the number of features in a dataset
- C . To eliminate outliers from the data
- D . To standardize the range of features
Which type of correlation coefficient indicates a strong positive linear relationship between two variables?
- A . -1.0
- B . 1.0
- C . 0.5
- D . 0.0
When communicating data analysis results to a less technical audience, which type of visualization is generally recommended for its simplicity and ease of understanding?
- A . Line chart
- B . Heatmap
- C . Scatter plot
- D . Bar chart
What is the result of the following Python code? “`python a = 10 b = 5 result = a % b print(result) “`
- A . 2
- B . 5
- C . 0
- D . 1
Which of the following correlation coefficients indicates a perfect negative linear relationship between two variables?
- A . 0.75
- B . -0.50
- C . 0
- D . -1
What does the ‘range()’ function in Python do?
- A . Generates a list of numbers starting from 1
- B . Generates a list of numbers with a specified start and end values
- C . Returns the length of a string
- D . Performs a mathematical operation on a list of numbers
What is the term used to describe the process of scaling numerical features to a standard range in data pre-processing?
- A . Feature Engineering
- B . Data Normalization
- C . Data Augmentation
- D . Data Wrangling