The Arranging and Collecting Data Class 9 Chapter 2 NCERT Solutions provide detailed and step-by-step answers to all the exercises given in the NCERT textbook. These solutions help students understand how to collect raw data, arrange it systematically, and present it in an organized form such as tables or frequency distribution.
Arranging and Collecting Data Class 9 NCERT Solutions
Objective-Type Questions
1. A school named ABC has recorded the total marks of every student in the class. This is an example of:
a. Qualitative data
b. Quantitative data
c. Both qualitative and quantitative data
d. None of the above
2. A food delivery app has asked for your feedback on the quality of the food. You have written two paragraphs to describe the food. This is an example of:
a. Qualitative data
b. Quantitative data
c. Both qualitative and quantitative data
d. None of the above
3. You need to predict what the temperature will be for next Friday. Which algorithm will you use?
a) Clustering
b) Regression
c) Anomaly detection
d) Binary classification
4. You need to predict if your car tire will last for the next 1000 km. Which algorithm will you use?
a) Clustering
b) Regression
c) Anomaly detection
d) Binary classification
5. Which of the following options are the benefits of big data processing?
a) Business can utilize outside intelligence while making decisions.
b) Improved customer service
c) Better optimal efficiency
d) All of the above
6. The analysis of large amounts of data to see what patterns or other useful information can be found is known as:
a) Data Analysis
b) Information Analytics
c) Big data analytics
d) Data Analytics
7. Big data analysis does the following except:
a) Collects data
b) Spreads data
c) Organizes data
d) Analyzes data
8. Primary data for the research process can be collected through
a) Experiment
b) Survey
c) Both a and b
d) None of the above
9. The advantages of secondary data are low cost, speed, availability, and flexibility.
a) True
b) False
10. The method of getting primary data by watching people is called
a) Survey
b) Informative
c) Observational
d) Experimental
Standard Questions
1. What is the difference between multivariate and univariate data? Give some examples.
Answer: Univariate data means data with only one variable; it does not show the relationships between different things. For example,
- Height of students in a class
- Temperature in one city
- Number of books read by each student
Multivariate data means data with two or more variables; it shows how things are connected or related. For example,
- Umbrella sales increase during the rainy season.
- → Variables: Rainfall and Sales
- A student’s marks may depend on study hours, sleep, and attendance.
- → Variables: Study hours, Sleep, Attendance, Marks
2. What are the common sources of data collection?
Answer: There are two different sources of data collection:
- Primary Source: This data is collected directly, where the data is collected in the form of surveys, interviews, feedback forms, experiments, etc.
- Secondary Source: The data is already recorded and collected from social media, web traffic, sensors, satellites, etc.
3. What are the primary characteristics of Big Data?
Answer: The primary characteristic of big data is
- Volume: This refers to the size of the data. Usually, data sets greater than terabytes and petabytes are called Big Data.
- Variety: Big Data sets are generally collected from a wide range of sources, including transactional databases, sensor data, etc. It could include images, pictures, audio, video, etc.
- Velocity: The rate at which data is generated. Big Data has generally created a rapid speed, resulting in high volumes very soon. For example, social media platforms generate a massive amount of data every minute.
4. What are categorical variables? Give some examples.
Answer: Categorical variables are the data that can be grouped into categories or labels. They are not measured in numbers. For example, city names like Mumbai and Delhi. Colors like red, blue, or green. Gender, like male or female. Dog breeds like beagle, labrador, etc.
5. How is big data used in social media?
Answer: Social media generates a lot of data; this data can track how many likes there are, what comments are written, or how many posts are done. It suggests content based on user behavior, detects trends and viral topics, and helps advertisers target the right audience.
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