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Data Handling - Construction and Interpretation of Bar Graphs and Double Bar Graphs

Grade 7ICSE

Review the key concepts, formulae, and examples before starting your quiz.

🔑Concepts

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A Bar Graph is a pictorial representation of numerical data using rectangular bars of equal width. These bars can be oriented vertically or horizontally, where the visual height of a vertical bar or the length of a horizontal bar is directly proportional to the numerical value it represents.

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The graph is constructed on two perpendicular lines called axes. The horizontal axis (xx-axis) typically represents categorical variables like names, months, or subjects, while the vertical axis (yy-axis) represents the numerical frequencies or quantities.

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Choosing an appropriate Scale is essential for fitting data accurately on the graph paper. The scale is the ratio of the actual data to the units on the grid; for example, setting 1 unit=10 students1 \text{ unit} = 10 \text{ students} determines how the yy-axis is graduated and labeled.

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For a bar graph to be accurate, all bars must have the same width, and the gaps between consecutive bars must be uniform. This visual consistency ensures that comparisons are based solely on the heights or lengths of the bars.

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A Double Bar Graph is used to compare two different sets of data for the same categories simultaneously. Visually, this is achieved by placing two bars representing different groups side-by-side for each category on the xx-axis, allowing for immediate side-by-side comparison.

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A Legend or Key is a small box included in the graph area that explains the visual coding used, especially in double bar graphs. It uses different colors or shading patterns (such as a solid blue bar for 'Year 1' and a striped red bar for 'Year 2') to distinguish between the two data series.

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Interpretation involves reading the top edge of a bar across to the yy-axis to determine its value. Visually, the tallest bar represents the maximum value or the most frequent category, while the shortest bar represents the minimum value.

📐Formulae

Mean (Average)=Sum of all observationsTotal number of observations\text{Mean (Average)} = \frac{\text{Sum of all observations}}{\text{Total number of observations}}

Range=Maximum Value−Minimum Value\text{Range} = \text{Maximum Value} - \text{Minimum Value}

Height of a Bar (in units)=Value of DataValue of 1 Unit on Scale\text{Height of a Bar (in units)} = \frac{\text{Value of Data}}{\text{Value of 1 Unit on Scale}}

Scale=Maximum Data ValueNumber of units available on the axis\text{Scale} = \frac{\text{Maximum Data Value}}{\text{Number of units available on the axis}}

💡Examples

Problem 1:

The number of books sold by a library in four days is: Monday: 4545, Tuesday: 3030, Wednesday: 5555, and Thursday: 4040. If the graph is drawn with a scale of 1 unit=5 books1 \text{ unit} = 5 \text{ books}, calculate the height of the bar for Wednesday and find the range of books sold.

Solution:

  1. To find the height of the bar for Wednesday: Height=Value for WednesdayScale=555=11 units\text{Height} = \frac{\text{Value for Wednesday}}{\text{Scale}} = \frac{55}{5} = 11 \text{ units}
  2. To find the range: Range=Maximum Value−Minimum Value=55−30=25 books\text{Range} = \text{Maximum Value} - \text{Minimum Value} = 55 - 30 = 25 \text{ books}

Explanation:

The height of the bar is calculated by dividing the data value by the chosen scale. The range provides the difference between the highest and lowest values in the data set.

Problem 2:

In a double bar graph comparing the marks of Rahul in Term 1 and Term 2: Maths (Term 1: 8080, Term 2: 9090), Science (Term 1: 7575, Term 2: 8585), and English (Term 1: 7070, Term 2: 6565). Calculate the total marks for Term 2 and the improvement in Maths.

Solution:

  1. Total marks for Term 2: 90(Maths)+85(Science)+65(English)=24090 (\text{Maths}) + 85 (\text{Science}) + 65 (\text{English}) = 240
  2. Improvement in Maths: Term 2−Term 1=90−80=10 marks\text{Term 2} - \text{Term 1} = 90 - 80 = 10 \text{ marks}

Explanation:

For a double bar graph, we extract the values for one specific data series (Term 2) by identifying its corresponding bars using the legend, and then sum them. Improvement is the positive difference between the two terms.