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Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL PDF Download

Definition

A radar chart is employed to visually illustrate disparities between real and optimal performance or to display diverse data in a two-dimensional chart featuring two or more measurable variables represented on axes originating from a common point.

About Radar Chart

Radar charts, alternatively termed spider charts or web charts, offer a distinctive and efficient method for presenting multivariate data. These charts enable the representation of data points on a circular grid, facilitating the simultaneous comparison of multiple variables. To fully leverage the capabilities of radar charts, it is crucial to comprehend the underlying formulas shaping this unique data visualization. This guide will explore the formulas that animate radar charts, empowering you to maximize the potential of this visualization technique.

Concept of Radar Chart

  • Data Structure: Radar charts utilize a system of axes radiating from a central point, shaping a polygonal form. Each axis is assigned to a distinct variable or category.
  • Data Points: Along each axis, data points are marked, and their distance from the center signifies the value of the corresponding variable.
  • Connecting Lines: Lines link these data points, forming a closed structure often described as "spider webs." This visual representation illustrates the relationships between variables.
  • Normalization: To ensure equitable comparisons, it is common practice to normalize the data. This involves scaling all values to fit within a consistent range, such as 0 to 1.

Solved Examples

Example 1:
Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL

Find the sum of the students in college A in 2002 and college B in 2006?
(a) 50000
(b) 25000
(c) 60000
(d) 63000
Ans: 
(c)
Students in college A in 2002 = 20000
Students in college B in 2006 = 40000
Therefore, sum = 20000 + 40000 = 60000 students.

Example 2:
Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL

Find the percent decrease in college B’s students in the year 2007 as compared to the previous year.
(a) 25%
(b) 21%
(c) 17%
(d) 30%
Ans:
(a)
In the year 2006, the students in college B were: 40
In the year 2007, the students in college B were: 30
Therefore, decrease = 40 – 30 = 10
Thus, percent decrease = 10/40 * 100 = 25%

Example 3:
Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL Find the percent increase in college A’s students in the year 2006 as compared to the previous year.
(a) 25%
(b) 21%
(c) 17%
(d) 16.66%
Ans: 
(d)
In the year 2005, the students in college A were: 30
In the year 2006, the students in college A were: 35
Therefore increase = 35 – 30 =5
Thus, percent increase = 5/30 * 100 = 16.66%

Example 4:
Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGLIf 35% of the students of college B in 2005 were girls, then find the number of boys in the same year?
(a) 11250
(b) 15000
(c) 16250
(d) 17000
Ans: 
(c)
Total students in college B in 2005 were: 25000
Therefore, the number of boys will be 100-35 = 65%
Thus, 65% of 25000 = 65/100 * 25000 = 16250

Example 5:
Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL

Which year has the highest number of difference between the number of students in college A and college B?
(a) 2006
(b) 2007
(c) 2003
(d) 2002
Ans: 
(b)
In 2002 the difference was: 30 – 20 = 10
In 2003: 35 – 25 = 10
In 2004: 45 – 35 = 10
In 2005: 30 – 25 = 5
In 2006: 40 – 35 = 5
In 2007: 45 – 30 = 15
Therefore, the difference was highest in the year 2007.

Example 6:
Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL

Find the average sale of company P, R, and U for the year 2006.
(a) 105.6
(b) 107.69
(c) 102.3
(d) 108.3
Ans:
(d)
In 2006 the sale of company P, R, and U were: 115 + 120 + 90 = 325
Therefore, the average = 325/3 = 108.33

Example 7:
Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL

Total sales of company Q is what percent of company T’s total sales for both 2005 and 2006 together?
(a) 82.12%
(b) 83.6%
(c) 85.5%
(d) 84.21%
Ans:
(d)
Company Q’s sale in 2005 = 85
In 2006 = 75
Company T’s sale in 2005 = 85
In 2006 = 105
Total sale of company Q = 85 + 75 = 160
Total sale of company T = 85 + 105 = 190
Percentage = 160/190 * 100 = 84.21%

Example 8: 

Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL Total sales of company U is what percent of company R’s total sales for both 2005 and 2006 together?
(a) 72.12%
(b) 73.6%
(c) 75.5%
(d) 81%
Ans:
(c)
Company U’s sale in 2005 = 80
In 2006 = 90
Company R’s sale in 2005 = 105
In 2006 = 120
Total sale of company U = 80 + 90 = 170
Total sale of company R = 105 + 120 = 225
Percentage = 170/225 * 100 = 75.5%

Example 9: 

Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL

What percentage of average sale of all 6 companies in 2005 is the average sale in 2006?
(a) 88.5%
(b) 98.5%
(c) 92.6%
(d) 101.2%

Ans: (a)
Average of all the six companies in 2005 = 90 + 85 + 105 + 95 + 85 + 80/ 6
= 540/6 = 90
Average of all the six companies in 2006 = 115 + 75 + 120 + 105 + 105 + 90/6
= 610/6 = 101.66
Percentage = 90/101.66 * 100 = 88.5%

Example 10: 

Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL Find the ratio between total sales of company Q and company S for the year 2005 and 2006.
(a) 7 : 13
(b) 5 : 6
(c) 33 : 40
(d) 19 : 23
Ans:
(c)
Company Q’s sale in 2005 = 80000
In 2006 = 85000
Company S’s sale in 2005 = 95000
In 2006 = 105000
Total sale of Company Q = 80000 + 85000 = 165000
Total sale of Company S = 95000 + 105000 = 200000
Therefore, ratio = 165000/200000 = 33 : 40

The document Solved Examples: Radar Charts | Quantitative Aptitude for SSC CGL is a part of the SSC CGL Course Quantitative Aptitude for SSC CGL.
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FAQs on Solved Examples: Radar Charts - Quantitative Aptitude for SSC CGL

1. What is a radar chart?
Ans. A radar chart, also known as a spider chart or web chart, is a graphical representation of data on a two-dimensional plane. It is used to display multivariate data in the form of a circular grid with multiple axes extending from the center. Each axis represents a different variable, and the data points are plotted on these axes to show the relative values of each variable.
2. How are radar charts useful?
Ans. Radar charts are useful for comparing the relative strengths or performance of multiple variables or data points. They can be used to analyze and visualize data across different categories, such as market share, survey responses, or performance indicators. Radar charts make it easy to identify patterns, trends, and outliers in the data, providing a comprehensive view of the overall performance.
3. Can radar charts handle large datasets?
Ans. While radar charts can handle moderate-sized datasets, they may become cluttered and less effective when dealing with a large number of data points or variables. It is recommended to limit the number of variables and data points in a radar chart to ensure clarity and readability. If the dataset is too large, it might be better to consider alternative visualization techniques, such as bar charts or scatter plots.
4. How do I interpret a radar chart?
Ans. To interpret a radar chart, start by identifying the axes and their corresponding variables. Each axis represents a different variable, and the distance from the center to a data point on that axis indicates the value or level of that variable. The shape formed by connecting the data points can provide insights into the overall pattern or distribution of the data. Higher values on an axis indicate a stronger or better performance in that variable.
5. Are radar charts suitable for all types of data analysis?
Ans. Radar charts are best suited for comparing and analyzing data with multiple variables that have a common measurement scale. They work well for data that can be represented as continuous or ordinal variables. However, radar charts may not be suitable for data with categorical variables or when the data points have a significant variation in their measurement scales. It is important to consider the nature and characteristics of the data before deciding to use a radar chart.
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