Exercise 4.2 class 8 solution

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Exercise 4.2 class 8 solution-graphical method of representing the data.

Graphical methods are a powerful way to represent data visually, making it easier to understand patterns, trends, and relationships within the data. Here are some common graphical methods for representing data:

Bar Chart: Bar charts are used to display categorical data. The categories are shown on the horizontal axis (x-axis), and the frequency, count, or values are represented by bars on the vertical axis (y-axis). Bar charts can be either horizontal or vertical.

Histogram: A histogram is used to represent the frequency distribution of continuous data. It divides the data into intervals (bins) on the x-axis and shows the frequency or count of data points falling within each interval on the y-axis. Histograms are useful for visualizing the shape of the data distribution.1

Line Chart: Line charts are used to show trends and changes in data over time. They connect data points with lines, making it easy to see how values evolve. They are commonly used in time series analysis.

Pie Chart: A pie chart is a circular chart that divides a whole into sectors or “slices” to represent the proportions of different categories within the whole. It is often used to show the composition of a whole in terms of percentages.

The choice of graphical method depends on the nature of the data, the research questions, and the insights you want to gain from the data. Different types of data may be best suited to different types of graphs or charts.

Exercise 4.2 class 8 solution – histogram

A histogram is a graphical representation of the distribution of a dataset, particularly used for displaying the frequency or count of data points within specific intervals or bins. It’s a commonly used tool in statistics and data analysis to understand the shape, central tendency, and variability of a dataset. Here’s how to create and interpret a histogram:

Creating a Histogram:

1. Data Collection: Gather your dataset, which may consist of a series of measurements on a continuous scale.
2. Data Range Determination: Determine the range of values in your dataset. This defines the lower and upper bounds of the data.
3. Class Intervals (Bins): Divide the data range into non-overlapping intervals or bins. The width and number of intervals depend on your preferences and the characteristics of the data. Common methods for determining class intervals include the square root method, Sturges’ rule, and Scott’s normal reference rule.
4. Frequency Count: Count how many data points fall within each interval. This count represents the frequency for that interval.
5. Graphical Representation: Create a bar chart where the x-axis represents the intervals (bins), and the y-axis represents the frequency of data points within each interval. Each interval is represented as a bar, and the height of the bar corresponds to the frequency.

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Exercise 4.2 class 8 solution – solution pdf

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