Ncert Books Class 9 Maths Chapter 14 Free Download
Ncert Books Class 9 Maths Chapter 14 Free Download
FAQs on Ncert Books Class 9 Maths Chapter 14 Free Download
1. What are some frequently asked 3-mark and 5-mark important questions from Statistics Class 9 for the CBSE 2025-26 exams?
For the CBSE 2025-26 exams, important questions from Statistics typically cover:
- 3-Mark Questions: Constructing a frequency distribution table from raw data, calculating the mean or median of ungrouped data, and drawing a simple bar graph.
- 5-Mark Questions: Drawing a histogram (both with uniform and varying class widths), drawing a frequency polygon (sometimes superimposed on a histogram), and problems involving finding a missing value when the mean is given.
2. What type of important questions are asked from the graphical representation of data in Chapter 14?
Graphical representation is a high-weightage topic in the Class 9 Maths exam. Important questions include:
- Constructing a histogram for a continuous frequency distribution.
- Constructing a histogram for a distribution with unequal class intervals, which requires adjusting the lengths of the rectangles.
- Drawing a frequency polygon for a given data set, either with or without constructing a histogram first.
- Interpreting data from a given bar graph or histogram to answer specific questions.
3. From the measures of central tendency, which topic holds more weightage in exams: mean, median, or mode?
In Class 9, questions on calculating the mean, median, and mode of ungrouped data are all considered important. However, problems involving the median are often considered slightly more complex as they test conceptual clarity, especially when dealing with an even number of observations. You can expect direct calculation questions on all three for 2 or 3 marks.
4. How does a histogram differ from a bar graph, and why is this a common source of error in exams?
This is a crucial distinction frequently tested in exams. A bar graph represents discrete or categorical data, and its bars are separated by uniform gaps. In contrast, a histogram represents continuous data grouped in class intervals, and its adjacent bars have no gaps. A common error is leaving gaps between the bars of a histogram or using a histogram for non-continuous data, which can lead to a loss of marks.
5. Why is it important to adjust the frequency when drawing a histogram with unequal class widths?
In a histogram, the area of each rectangle must be proportional to the frequency of its class interval, not just its height. When class widths are equal, height is directly proportional to frequency. However, with unequal widths, this is not true. We must calculate the adjusted frequency to modify the bar heights, ensuring the areas correctly represent the data distribution. This is a key concept tested in higher-order thinking skills (HOTS) questions.
6. In what scenario would a frequency polygon be more useful than a histogram for analysing data trends?
A frequency polygon is particularly useful when you need to compare the distributions of two or more data sets on the same graph, for example, comparing the performance of students in two different sections. Plotting two histograms on the same axes can be cluttered and difficult to interpret, whereas two frequency polygons can be easily overlaid and compared to analyse trends and differences more clearly.
7. Are questions on the difference between primary and secondary data important for the Class 9 exam?
Yes, while calculation-based problems carry more marks, you can expect 1- or 2-mark questions that test your understanding of fundamental concepts. An important question could be to define primary and secondary data with examples or to classify a given data collection scenario as either primary or secondary. This tests the foundational knowledge of the chapter as per the NCERT syllabus.
8. What is the most common mistake students make when finding the median of an ungrouped data set?
The most frequent error is forgetting to arrange the data in ascending or descending order before applying the median formula. The median is the value of the middle observation only after the data has been sorted. Another common pitfall is incorrectly applying the formula for an even number of observations, where the median is the average of the two middle terms, i.e., the average of the (n/2)th and (n/2 + 1)th terms.











