Question 1

Identify data required to be maintained to perform the following services:
a) Declare exam results and print e-certificates
b) Register participants in an exhibition and issue biometric ID cards
c) To search for an image by a search engine
d) To book an OPD appointment with a hospital in a specific department

Accepted Answer

a) Data required: Student details (name, roll number, exam scores, grades), exam results database, certificate templates, digital signatures for e-certificates.

b) Data required: Participant details (name, contact info, photo), biometric data (fingerprints or iris scans), registration ID, event details.

c) Data required: Image metadata (tags, descriptions), image database, keywords, indexing data for search engine.

d) Data required: Patient details, hospital departments, doctor schedules, appointment slots, patient medical history. — For each service, the data needed corresponds to the entities involved and the operations to be performed. For exam results, student and exam data are essential. For exhibition registration, participant and biometric data are needed. Image search requires metadata and indexing. OPD booking needs patient and hospital scheduling data.

Question 2

A school having 500 students wants to identify beneficiaries of the merit-cum means scholarship, achieving more than 75% for two consecutive years and having family income less than 5 lakh per annum. Briefly describe data processing steps to be taken by the to beneficial prepare the list of school.

Accepted Answer

Step 1: Data Collection - Collect student academic records for the last two years and family income details.
Step 2: Data Cleaning - Verify data accuracy and completeness.
Step 3: Data Filtering - Select students with more than 75% marks in both years.
Step 4: Income Filtering - From the filtered students, select those with family income less than 5 lakh per annum.
Step 5: List Preparation - Prepare the final list of beneficiaries based on the above criteria.
Step 6: Verification and Approval - Verify the list and approve for scholarship disbursement. — The process involves collecting relevant data, cleaning it, applying the merit and means criteria sequentially, and preparing the final beneficiary list.

Question 3

A bank ‘xyz’ wants to know about its popularity among the residents of a city ‘ABC’ on the basis of number of bank accounts each family has and the average monthly account balance of each person. Briefly describe the steps to be taken for collecting data and what results can be checked through processing of the collected data.

Accepted Answer

Data Collection Steps:
- Define the data required: number of accounts per family, average monthly balance per person.
- Design data collection tools such as surveys or use bank records.
- Collect data from residents or bank databases.
- Organize data by family and individual.

Data Processing and Results:
- Calculate average number of accounts per family.
- Calculate average monthly balance per person.
- Analyze distribution of accounts and balances.
- Identify popular banking products or services.
- Assess market penetration and customer base strength. — Collecting accurate data on accounts and balances helps the bank analyze its popularity and customer engagement in the city. Processing this data reveals trends and areas for improvement.

Question 4

Identify type of data being collected/generated in the following scenarios:
a) Recording a video
b) Marking attendance by teacher
c) Writing tweets
d) Filling an application form online

Accepted Answer

a) Recording a video - Unstructured data (video files).

b) Marking attendance by teacher - Structured data (attendance records, usually yes/no or present/absent).

c) Writing tweets - Semi-structured data (text with hashtags, mentions).

d) Filling an application form online - Structured data (form fields with specific data types). — Data types depend on format and organization. Videos are unstructured, attendance is structured, tweets are semi-structured due to metadata, and forms are structured.

Question 5

Consider the temperature (in Celsius) of 7 days of a week as 34, 34, 27, 28, 27, 34, 34. Identify the appropriate statistical technique to be used to calculate the following:
a) Find the average temperature.
b) Find the temperature Range of that week.
c) Find the standard deviation temperature.

Accepted Answer

Given temperatures: 34, 34, 27, 28, 27, 34, 34

(a) Average temperature (Mean):
Mean = (34 + 34 + 27 + 28 + 27 + 34 + 34) / 7 = 218 / 7 ≈ 31.14°C

(b) Temperature Range:
Range = Maximum - Minimum = 34 - 27 = 7°C

(c) Standard Deviation:
Step 1: Calculate mean = 31.14
Step 2: Calculate squared deviations:
(34 - 31.14)^2 = 8.18
(34 - 31.14)^2 = 8.18
(27 - 31.14)^2 = 17.14
(28 - 31.14)^2 = 9.86
(27 - 31.14)^2 = 17.14
(34 - 31.14)^2 = 8.18
(34 - 31.14)^2 = 8.18
Sum = 76.86
Step 3: Variance = 76.86 / 7 ≈ 10.98
Step 4: Standard deviation = √10.98 ≈ 3.31°C — Mean is sum of values divided by count. Range is difference between max and min values. Standard deviation measures spread of data around mean, calculated by square root of average squared deviations.

Question 6

A school teacher wants to analyse results. Identify the appropriate statistical technique to be used along with its justification for the following cases:
a) Teacher wants to compare performance in terms of division secured by students in Class XII A and Class XII B where each class strength is same.
b) Teacher has conducted five unit tests for that class in months July to November and wants to compare the class performance in these five months.

Accepted Answer

a) Appropriate technique: Comparative analysis using bar charts or pie charts for categorical data (divisions). Justification: Divisions are categorical data; comparing frequency distribution across two classes helps analyze performance.

b) Appropriate technique: Line graph or trend analysis of average marks over five months. Justification: Unit test scores are numerical data over time; trend analysis shows performance progression. — Different data types require different statistical techniques. Categorical data (divisions) are best compared using frequency charts; numerical time-series data are analyzed using line graphs.

Question 7

Suppose annual day of your school is to be celebrated. The school has decided to felicitate those parents of the students studying in classes XI and XII, who are the alumni of the same school. In this context, answer the following questions:
a) Which statistical technique should be used to find out the number of students whose both parents are alumni of this school?
b) How varied are the age of parents of the students of that school?

Accepted Answer

a) Statistical technique: Frequency count or categorical data analysis (using bar chart or pie chart) to find the number of students with both parents as alumni.

b) Statistical technique: Measure of dispersion such as standard deviation or range to analyze variation in parents' ages. — Counting students with both parents alumni is categorical frequency analysis. Variation in age is numerical data dispersion analysis.

Question 8

For the annual day celebrations, the teacher is looking for an anchor in a class of 42 students. The teacher would make selection of an anchor on the basis of singing skill, writing skill, as well as monitoring skill.
a) Which mode of data collection should be used?
b) How would you represent the skill of students as data?

Accepted Answer

a) Mode of data collection: Observation and rating scales or questionnaires to assess each student's skills.

b) Representation of data: Use of categorical or ordinal data scales (e.g., ratings like Excellent, Good, Average) or numerical scores for each skill per student. — Skills are assessed via observation or self-reporting; data can be represented as categorical ratings or numerical scores for comparison.

Question 9

Differentiate between structured and unstructured data giving one example.

The principal of a school wants to do following analysis on the basis of food items procured and sold in the canteen:
a) Compare the purchase and sale price of fruit juice and biscuits.
b) Compare sales of fruit juice, biscuits and samosa.
c) Variation in sale price of fruit juices of different companies for same quantity (in ml).

Create an appropriate dataset for these items (fruit juice, biscuits, samosa) by listing their purchase price and sale price. Apply basic statistical techniques to make the comparisons.

Accepted Answer

Structured data: Data organized in a fixed format, easy to search and analyze. Example: Student marks in a table.
Unstructured data: Data without a predefined format, difficult to analyze directly. Example: Video recordings.

Dataset example:
| Item       | Purchase Price (₹) | Sale Price (₹) |
|------------|--------------------|----------------|
| Fruit Juice| 20                 | 30             |
| Biscuits   | 10                 | 15             |
| Samosa     | 8                  | 12             |

Statistical techniques:
a) Compare purchase and sale price using difference or percentage profit.
b) Compare sales quantities using bar charts or pie charts.
c) Analyze variation in sale price of fruit juices using range or standard deviation if multiple companies' prices are given. — Structured data is organized and easily analyzed; unstructured is not. Creating a dataset helps apply statistical measures like profit calculation, comparison charts, and dispersion measures.

Question 10

Which of the following best describes the difference between data and information?

Accepted Answer

Data is raw facts and figures; information is processed data that is meaningful — Data are raw characters, numbers, or symbols representing values of situations or variables. Information is data that has been processed and analyzed to be meaningful and useful for decision making. Hence, data alone is not sufficient without processing to become information.

Question 11

Identify the structure labelled as 'Data Processing' in Figure 7.1 which shows the basic steps used to process data to get output. The diagram shows four blocks in sequence: Data Input, Data Storage, Data Processing, and Output Generation.

Accepted Answer

The step where data is transformed into meaningful information — In Figure 7.1, Data Processing is the step where the stored data is manipulated or processed using algorithms or software to convert raw data into meaningful information for decision making.

Question 12

Fill in the blank: Data which is organised in rows and columns with well-defined attributes is called _____ data.

Accepted Answer

structured — Structured data is organised in a tabular format with rows and columns where each column represents an attribute and each row represents an observation. This format allows easy storage and processing using spreadsheets or databases.

Question 13

Explain why unstructured data is more difficult to process compared to structured data. Provide two examples of unstructured data.

Accepted Answer

— Unstructured data lacks a fixed format or organization such as rows and columns, making it difficult to store and analyze using traditional database systems. Examples include newspaper pages with varying layouts and email contents with variable length and attachments.

Question 14

Which of the following is NOT an example of data used in decision making?

Accepted Answer

Random thoughts in a diary with no structure — Data used for decision making must be organized or recorded in a way that it can be processed and analyzed. Random unstructured thoughts without any organization do not qualify as useful data.

Question 15

In Table 7.1 showing kitchen items inventory, calculate the total number of items in the inventory by summing the 'Items in Inventory' column.

Accepted Answer

123 — Given: Items in Inventory = 13, 45, 8, 10, 14, 6, 32
Find: Total items in inventory
Formula: Sum of all items
Solution: 13 + 45 + 8 + 10 + 14 + 6 + 32 = 128
Answer: 128 items
Note: Check addition carefully to avoid errors.

Correction: Recalculate sum: 13+45=58, 58+8=66, 66+10=76, 76+14=90, 90+6=96, 96+32=128
Answer: 128 items

Understanding Data

Understanding Data — Study Notes

Introduction to Data

Importance of Data

Types of Data

Practice Questions — Understanding Data

All 13 Chapters in Computer Science