FBISE, NCP & NBF-aligned resources for Classes 9–12
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Computer Chapter 4 : Test #3
1 / 20
A supermarket maintains detailed sales records for several years. Before every religious festival, managers analyze previous sales to estimate which products will be in high demand so they can stock enough inventory in advance. Which feature of data science is mainly being used?
Reasoning: Predictive analysis uses historical data to forecast future demand and trends.
2 / 20
A retail company stores millions of customer transactions in a system where information can be updated, searched, and managed efficiently every day. Analysts later extract only sales records for a marketing study. Which option correctly identifies the storage system?
Reasoning: A database is designed to store, organize, and manage data efficiently.
3 / 20
A researcher exports one year's sales records from a company's database into a CSV file for studying customer purchasing behavior. The exported file contains only the required information for analysis. What is this exported collection called?
Reasoning: A dataset is a collection of related data prepared for analysis.
4 / 20
A bank stores customer account details in a relational database because transactions are updated every second. Later, analysts use one month's transaction records to detect spending patterns. Which statement correctly distinguishes the two collections?
Reasoning: Databases manage operational data, while datasets are prepared for analysis.
5 / 20
A researcher classifies survey participants into the categories "Excellent," "Good," "Average," and "Poor" according to their performance. Although these labels are not numerical, they clearly represent a ranking. Which type of data is being used?
Reasoning: Ordinal data consists of categories arranged in a meaningful order.
6 / 20
A hospital records the blood groups of patients as A, B, AB, and O. These categories help organize patients but cannot be ranked from highest to lowest. Which type of data best describes these values?
Reasoning: Nominal data consists of categories without any natural order.
7 / 20
A company records the number of computers in each department to plan future purchases. Since only whole numbers are possible and fractions have no meaning, which type of quantitative data is represented?
Reasoning: Discrete data consists of countable values that cannot be divided into smaller units.
8 / 20
A weather station measures air temperature every minute throughout the day. The readings may include decimal values and can take any value within a range. Which category best describes this data?
Reasoning: Continuous data can take any value within a given range.
9 / 20
A scientist compares temperatures measured in degrees Celsius. Although the difference between values is meaningful, a reading of 0°C does not indicate the complete absence of temperature. Which measurement scale is represented?
Reasoning: Interval-scaled data has equal intervals but no true zero point.
10 / 20
A manufacturing company records the weight of packaged products before shipment. A package weighing 0 kg means there is no product inside, and comparisons such as "twice as heavy" are meaningful. Which measurement scale applies to this data?
Reasoning: Ratio-scaled data has a true zero and supports meaningful ratio comparisons.
11 / 20
A retail company stores customer purchases, website clicks, product reviews, and payment records collected over several years. The IT team discovers that their traditional database tools cannot efficiently store or process the continuously growing information. Which characteristic of big data is primarily responsible for this challenge?
Reasoning: Volume refers to the enormous amount of data that exceeds the capacity of traditional processing systems.
12 / 20
A traffic monitoring system receives thousands of updates every second from road sensors and GPS devices. To warn drivers about accidents immediately, the incoming information must be analyzed without significant delay. Which characteristic of big data is most important in this situation?
Reasoning: Velocity refers to the speed at which data is generated, received, and processed in real time.
13 / 20
A hospital collects patient records from databases, medical images from scanners, doctors’ handwritten notes, laboratory reports in PDF format, and wearable sensor readings. Before analysis, these different data formats require additional preprocessing. Which characteristic of big data does this example best illustrate?
Reasoning: Variety refers to handling structured, semi-structured, and unstructured data from multiple sources.
14 / 20
An online company gathers millions of customer records every day. During analysis, it discovers that many entries contain duplicate names, incorrect addresses, and incomplete information. To ensure reliable decision-making, the company first improves the quality of its data. Which big data characteristic is being addressed?
Reasoning: Veracity focuses on the accuracy, reliability, and quality of data before analysis.
15 / 20
A business stores enormous amounts of customer information every month. After careful analysis, only a small portion helps increase sales and improve marketing strategies, while the remaining data has little practical use. Which characteristic of big data is highlighted in this situation?
Reasoning: Value emphasizes extracting useful and meaningful information from collected data.
16 / 20
A school maintains student records in tables, receives assignment submissions in PDF format, and collects attendance logs in JSON files generated by an online system. Which option correctly identifies the data type represented by the JSON files?
Reasoning: JSON contains a flexible structure and is classified as semi-structured data.
17 / 20
An internet service provider records server activity every second. The log files contain textual information with inconsistent formatting that can later be organized using specialized software for analysis. Which type of data best describes these server logs?
Reasoning: Quasi-structured data includes inconsistent textual formats such as web server log files.
18 / 20
A technology student studies the evolution of big data and learns that storing rapidly growing datasets became much easier after the introduction of an open-source framework specifically designed for distributed storage and processing. Which technology made this possible?
Reasoning: Hadoop was developed to efficiently store and process very large datasets.
19 / 20
A researcher explains that the rapid growth of online platforms caused organizations to generate data at an unprecedented rate. This increase eventually led to the widespread use of the term "big data" in the early 2000s. Which online services mainly contributed to this growth?
Reasoning: Facebook, YouTube, and similar online services greatly increased data generation.
20 / 20
A manufacturing company connects its machines to the internet so they continuously send performance information. Engineers analyze this live data to predict failures before breakdowns occur and improve production efficiency. Which technology mainly enables this continuous data generation?
Reasoning: IoT devices continuously generate real-time data used for monitoring and predictive analysis.
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