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3. Nominal variables are like labels or categories like car brands or seasons.
4. Interval level data shares similarities with ordinal data as it maintains a clear order, but it differs in
that the differences between values can be measured.
5. Mode represents the sum of all values in a dataset divided by the number of values.
6. Data points with a low standard deviation are near to the mean.
7. Matplotlib is non-customisable, giving users little control over the appearance of their plots.
8. Scatterplot is referred to as horizontal bar chart.
SECTION B (Subjective Type Questions)
A. Short answer type questions.
1. Define testing data.
2. What are the levels of measurement of ordinal data?
3. What is a pie chart? Explain with example.
4. Which command will you use to install Matplotlib library?
5. Define matrix.
B. Long answer type questions.
1. Discuss different sources of secondary data.
2. What is structured, semi-structured and unstructured data? Give examples.
3. Explain the Data Transformation process.
4. Explain any four applications of matrices in AI.
5. List down any four differences between training data and testing data.
C. Competency-based/Application-based questions: #Coding & Computational Thinking
1. Computer science teacher in Gyan Vidya School invited students to try data visualisation for the following data. Can
you suggest a suitable method for visualising this data. Also give the Python code required for the same.
Max. Temperature
Month
(°C)
Jan 19.50
Feb 23.00
Mar 27.95
Apr 34.97
May 37.66
Jun 36.26
Jul 32.90
Aug 31.77
Sep 31.73
Oct 30.92
Nov 27.33
Dec 22.77
Average 29.73
2. Your teacher has asked you to compare the test scores of two classes to understand which class has more consistent
performance. Class A's test scores are [85, 90, 92, 88, 91], and Class B's test scores are [78, 82, 85, 79, 81]. Calculate
the variance and standard deviation for both classes to determine which class has more consistent scores.
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