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| Section | Weight | Objectives |
|---|---|---|
| Python Basics for Data Analysis | 32.5% | - Built-in modules for data work
|
| Data Visualization and Communication | 20% | - Principles of effective data visualization
|
| Working with Data and Performing Simple Analysis | 25% | - Data cleaning and preparation
|
| Introduction to Data and Data Analysis Concepts | 22.5% | - Definition and classification of data
|
Question 1
Which of the following code snippets will output Truefor both printfunctions by correctly identifying the type of each variable and performing valid operations?
A.
B.
C.
D. 
Question 2
You are writing a function to validate battery voltage readings. The rules are:
- If the reading is "MISSING"or None, return "Missing".
- If the value is below 2.5or above 4.2, return "Outlier".
Otherwise, return "Normal".
Which version correctly implements this logic using the most robust conditional and nested structures? Select the best answer.
A.
B.
C.
D. 
Question 3
Which task is traditionally or typically performed by a data analyst, and not by a data scientist or analytics specialist? Select the best answer.
A. Developing machine learning algorithms to predict user behavior.
B. Creating summary tables and charts to describe patterns in historical data.
C. Designing a data pipeline to ingest and process real-time sensor data.
D. Recommending pricing strategies using predictive modeling and A/B testing.
Question 4
How do the analysis and visualization stages of the data lifecycle typically work together?
A. Analysis summarizes archived data, and visualization transforms it into structured tables for storage.
B. Analysis identifies patterns and insights in processed data, which are then communicated through visualizations for informed decision-making.
C. Analysis produces charts and graphs, while visualization interprets the data to detect outliers.
D. Analysis retrieves raw inputs from dashboards, while visualization uses that input to clean the data.
Question 5
You are given the following list of daily step counts:
steps = [8230, 9020, 7640, 8760, 10020, 2546, 9817]
Your task is to calculate:
- the standard deviation of the step counts,
- the average rounded up to the nearest whole number, and
- the median of the step counts.
Which code snippet correctly performs all three tasks? Select the best answer.
import statistics
A. import math
print(math.stdev(steps))
print(statistics.mean(steps))
print(statistics.median(steps))
import statistics
B. import math
print(statistics.variance(steps))
print(math.ceil(sum(steps) / len(steps)))
print(math.floor(statistics.median(steps)))
import statistics
C. import math
print(statistics.stdev(steps))
print(math.ceil(statistics.mean(steps)))
print(statistics.median(steps))
D. import math
print(statistics.stdev(steps))
print(round(math.mean(steps)))
print(math.median(steps))
import statistics
Solutions:
| Question 1 Answer: D | Question 2 Answer: C | Question 3 Answer: B | Question 4 Answer: B | Question 5 Answer: C |
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