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Revision Notes: Statistics: Graphical Representation | Mathematics Class 10 ICSE PDF Download

Statistical data can be represented graphically by several ways.

  • A histogram is a graphical representation of a frequency distribution (in continuous form) in the form of rectangles with class intervals as bases and corresponding frequencies as heights, with no gap between any two successive rectangles.
  • Frequency polygons are another way of displaying data using straight line segments.
  • The cumulative frequency is the accumulated or sum of frequencies up to a particular point. A table showing the cumulative frequencies is called a cumulative frequency distribution.
  • Grouped data are also represented by a curve called ogive or cumulative-frequency curve.
  • Construction of Cumulative Frequency Curve or an ogive:
    i. Construct a cumulative frequency table
    ii. Mark the actual class limits along x-axis
    iii. Mark the cumulative frequencies of respective classes along y-axis
    iv. Plot the points corresponding to cumulative frequency at each upper limit point.
    v. Join the points plotted by a free hand curve.
  • An ogive is always started from a point on x-axis representing the lower limit of the first class and is terminated at the upper limit of the last class.
  • An ogive is always a rising curve.

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FAQs on Revision Notes: Statistics: Graphical Representation - Mathematics Class 10 ICSE

1. What are the different types of graphical representations in statistics?
Ans. The different types of graphical representations in statistics include bar graphs, histograms, line graphs, pie charts, and scatter plots. Each type serves a unique purpose: bar graphs help in comparing quantities, histograms are used for frequency distribution, line graphs display trends over time, pie charts show proportions, and scatter plots illustrate relationships between two variables.
2. How do you interpret a bar graph?
Ans. To interpret a bar graph, observe the height or length of each bar, which represents the value of the data category it corresponds to. Check the scales on the axes—usually, the vertical axis shows the value while the horizontal axis displays categories. Compare the bars to understand differences in quantities among the categories.
3. What is the importance of using graphs in statistics?
Ans. Graphs are important in statistics because they provide a visual representation of data, making it easier to identify trends, patterns, and relationships. They help in summarizing large amounts of information succinctly and can enhance understanding and communication of data findings to various audiences.
4. How do you create a pie chart?
Ans. To create a pie chart, first, gather the data you want to represent. Calculate the total of all the data points, then determine the angle for each category by using the formula (Category Value / Total Value) × 360°. Draw a circle and divide it into slices according to the calculated angles, labeling each section with its corresponding category.
5. What precautions should be taken while representing data graphically?
Ans. When representing data graphically, ensure accuracy in scales and measurements to avoid misrepresentation. Use appropriate types of graphs for the data being presented, and label axes and data points clearly. Avoid clutter and ensure the graph is easy to read. It's also important to provide context and source for the data to maintain credibility.
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