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| Section | Weight | Objectives |
|---|
| Topic 1: Introduction to Data and Data Analysis Concepts | 22.5% | - Definition and classification of data
- 1. Process of turning raw data into insights
- 2. Difference between data, information, and knowledge
- 3. Role of data in decision-making and business
- Data types and measurement scales
- 1. Qualitative vs quantitative data
- 2. Nominal, ordinal, interval, ratio scales
- Basic statistical concepts
- 1. Population, sample, variable, observation
- 2. Descriptive vs inferential statistics
- Data lifecycle and ethical considerations
- 1. Data collection, storage, processing, usage, and sharing
- 2. Privacy, security, bias, and fairness in data
|
| Topic 2: Data Visualization and Communication | 20% | - Principles of effective data visualization
- 1. Clarity, simplicity, and accuracy
- 2. Choosing appropriate chart types
- Creating basic visualizations
- 1. Line charts, bar charts, histograms, pie charts
- 2. Using text and simple plotting tools
- Interpreting and presenting results
- 1. Reporting findings clearly and concisely
- 2. Deriving conclusions and insights
|
| Topic 3: Working with Data and Performing Simple Analysis | 25% | - Data acquisition and loading
- 1. Importing data from external sources
- 2. Reading text, CSV, and structured files
- Data aggregation and grouping
- 1. Summarizing and grouping datasets
- Data cleaning and preparation
- 1. Formatting and standardizing values
- 2. Handling missing values, duplicates, and errors
- 3. Filtering, sorting, transforming data
- Exploratory data analysis
- 1. Identifying patterns, trends, and outliers
- 2. Calculating mean, median, mode, range, variance, standard deviation
|
| Topic 4: Python Basics for Data Analysis | 32.5% | - Introduction to NumPy
- 1. Arrays, basic operations, indexing, slicing
- Core Python syntax and data types
- 1. Variables, numbers, strings, booleans
- 2. Lists, tuples, sets, dictionaries
- Built-in modules for data work
- 1. math, statistics, datetime, collections, csv
- Control flow and functions
- 1. Conditional statements, loops, iteration
- 2. Basic exception handling
- 3. Defining and calling functions, parameters, return values
|
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Python Institute PCED - Certified Entry-Level Data Analyst with Python Sample Questions (Q46-Q51):
NEW QUESTION # 46
An online retailer collects customer reviews, order transaction logs, and product ratings.
Which of the following correctly classifies these types of data? Select the best answer.
- A. Product ratings are quantitative and structured; customer reviews are qualitative and unstructured; transaction logs are structured and quantitative
- B. Product ratings are quantitative and unstructured; customer reviews are structured and qualitative; transaction logs are quantitative and unstructured.
- C. Product ratings are qualitative and unstructured; customer reviews are quantitative and structured; transaction logs are semi-structured and qualitative.
- D. Product ratings are qualitative and structured; customer reviews are qualitative and unstructured; transaction logs are quantitative and semi-structured.
Answer: A
Explanation:
Product ratings are numeric values stored in fixed fields, making them quantitative and structured.
Customer reviews are free-text responses, which are qualitative and unstructured. Transaction logs consist of organized records with defined fields such as order ID, date, and amount, making them structured and quantitative.
NEW QUESTION # 47
A teacher wants to compare the number of students in different school clubs:

Which type of chart would be most appropriate to show this comparison? Select the best answer.
- A. Pie chart
- B. Bar chart
- C. Line chart
- D. Bubble chart
Answer: B
Explanation:
A bar chart is best for comparing quantities across distinct categories, such as the number of students in each club, because it clearly shows differences in counts side by side.
NEW QUESTION # 48
The following chart shows how a student spends 24 hours in a day:

Which statements are most accurate? (Choose two.)
- A. Leisure accounts for a moderate portion of the student's daily schedule, larger than commuting but smaller than the time spent at school.
- B. More time is spent commuting than on leisure.
- C. Sleep and school take up the majority of time in a day.
- D. School and homework together take up half of the day's time.
- E. Leisure and meals combined equal the time spent at school.
- F. Commuting is the second most time-consuming activity.
Answer: A,C
NEW QUESTION # 49
A Python script evaluates the expression len(" "). The programmer assumes it might be zero because it looks empty. What will the actual result be?
Answer: D
Explanation:
A space is still a valid character in a string. Therefore, the string contains one character, and len("
") returns 1 instead of 0.
NEW QUESTION # 50
A list is defined as [1, 2, 3]. The programmer uses the method .append([4, 5]). What will the resulting list look like after execution?
- A. Error
- B. [1,2,3,4,5]
- C. [4,5,1,2,3]
- D. [1,2,3,[4,5]]
Answer: D
Explanation:
The append() method adds its argument as a single element. Therefore, the list [4, 5] is added as one nested list, resulting in [1, 2, 3, [4, 5]].
NEW QUESTION # 51
......
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