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Charts and graphs in Statistics

charts and graphs

Charts and graph in statistics

The statistical data in statistics is shown by charts, diagrams, and graphs for getting quick information. Charts and graphs of statistical data are catchy and time saver for collecting the information. The charts and graphs of statistics give us full information about the statistical data at a glance. The statistical charts are also known as pictographs. There are a number of ways of showing charts and graphs in the statistics. Here in this site, you are going to get the knowledge about all types of charts and graphs in statistics. These charts and graphs of statistics are widely used in science, maths, economics, political science, social science, and in media. Before we start the topic types of graphs in statistics, first we have to discuss some of the statistical terms as follows.

You can study here charts and graph in statistics,definition of statistics,application of statistics,difference between raw data and organized data,frequency distribution table,types of statistical data,individual series,descreet series,continuous series,class mark,commulative frequency,graphical representation of the data,bar graph,pie chart,histogram,frequency polygon,ogive,simple bar diagram,subdivided bar diagram,percentage bar diagram.

charts and graphs

 

 

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Definition- Statistics is the science of collecting, organizing, presenting, analyzing, and interpreting numerical data for the purpose of assisting in making an effective decision.

Application- The use of statistical data is executed in making the decision as after the extraction of the data. Statistics is used in the field of finance, economics, commercial field, business, science, etc.

It is mostly used in managing the government allocation of the budget in different fields and in the company’s sales, purchases, profit, loss, and predictions.

Mean, Mode and Median

 

Charts and Graphs used in Statistics

Data– Data is the collection of facts and figures of information such as the name of students, marks obtained by the students, the population of a country, temperatures of days within a weak of a particular place, etc. Data is of two kinds

Raw Data- The unorganized data is known as raw data as an example the marks out of hundred of few students are given bellow.

45, 70, 60, 30, 45, 75, 80, 98,56, 30,70

Organized data – The data is formed by extracting the raw data to make it meaningful is known as organized data.

The above raw data is arranged in the following way

 

Marks of students Number of students
45 2
70 1
60 2
30 1
75 1
80 1
98 1
56 1

 

Frequency of data- The number of times a particular quantity repeats in a given data is known as the frequency of the data. As an ex. In the above-mentioned data 45 is repeated two times so, the frequency of observation 45 is 2.

Frequency distribution table-This is an organized form of data in which the quantity and corresponding frequency is also mentioned.

Type of statistical data –The statistical data is collected from different sources through experiments, surveys, and analyses.

There are mainly two types of statistical data based on the sources wherefrom it is taken

  • Primary statistical data
  • Secondary statistical data

The statistical data is classified into two types based on the extent of values of the quantity

  • Qualitative statistical data
  • Quantitative statistical data

Primary statistical data- Primary data is the data which is obtained by the investigator or researcher by the method of direct interview, surveys, and experiments on which statistical operations have not been applied. As an example, the decimal census collected by directly surveying door to door.

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Secondary statistical data – Secondary statistical data is the data that is collected from other sources like Indian statistical organizations, ministry or another department. The secondary data is also collected from the magazine and newspaper. This is the data on which statistical operations are done for making a decision.

Qualitative statistical data –The qualitative statistical data is represented by words only, as an example chapter of a book, observation of things good, bad, worse, etc.

Quantitative statical data –The Quantitative statical data is represented by the numerals, as an example the weights of 5 students, marks of 6 students, etc.

The series of statistical data is classified into three types

Individual series –The series of statistical data in which observation is given without showing their frequencies. As an example the weight of 5 persons given bellow.

68 kg, 50kg, 70kg, 80kg, 50kg

Discreet series –The series of the data in which observations are shown with their corresponding frequencies.

Continuous series –  The statistical data is given in the form of intervals. As an example, the marks of 50 students in a test is given below. It is also called grouped frequency distribution.

Marks of student 40 – 50 50 – 60 60 – 70 70 – 80
Number of students 5 10 30 5

 

Limits – In the class interval 40 – 50, the lower limit is 40 and the upper limit is 50

Class Mark- The midpoint of the class interval is known as the class mark, the class mark of the class interval is calculated as follows.

Cumulative Frequency –The cumulative frequency corresponding to observation is the sum of previous frequencies. As an example cumulative frequency of the above data is given below.

statistics

 

Graphical Representation of the data – The representation of the data through diagrams helps us to visualize the whole meaning of the distribution of frequencies of observations at a single glance. There are various means of representing the data by means of graphs.

  • Bar Graph
  • Pie Chart
  • Histogram
  • Frequency Polygon
  • Ogive

 

Bar Graph –It is the simplest way of representing the numerical data in the form of bars of equal width, the space between the consecutive bars must be the same. The height of the bar shows the value of observations. The numerical data can be represented by the following types of bar diagrams, depending upon the type of data.

Simple bar diagram- When observations are of the same type of data is of single variable then it is better to represent the data by bar diagram. It can be understood by the following example.

Table

Games Table Tennis Volleyball Hockey Basket Ball Cricket
No of students 500 300 350 400 550

 

statistics bar diagram

 

Subdivided bar diagram- Draw a suitable diagram to represent the following information

 

 

Factory

 

 

 

 

Selling price per unit (in Rs)

 

 

 

 

Quantity sold

 

 

Cost of components
 

Wages

 

Material

 

Miscellaneous

 

Total

X 400 20 3200 2400 1600 7200
Y 600 30 6000 6000 9000 21000

 

 

Show the profit and loss also.

We are destined to show expenditures per unit of the item by both the factory. Before we show the above data, let us calculate the cost of wages, material, and miscellaneous per unit of the item.

In case of factory X, total sale of 20 units  = 20  × 400 =  Rs 8000 and total cost of 20 units =Rs 7200

In case of factory Y,total sale of 30 units = 30 × 600 = Rs 18000 and total cost of 20 units = Rs 21000

 

Factory X (20 units) Factory Y   (30 units)
Total cost (Rs) Per unit cost Total cost Per unit cost(Rs)
Wages 3200 160 6000 200
Materials 2400 120 6000 200
Miscellaneous 1600 80 9000 300
Profit/Loss

(8000 −7200)

800

(8000 −7200)

40 −3000

(1800 – 2100)

−100

 

Negative sign shows the loss

asa

 

Percentage bar diagram- Represent the following data by a percentage bar diagram.

Subjects Number of Students
2016-17 2017-18
 Statistics 25 30
Economics 40 42
History 35 28

 

Solutions. Calculating the percentage of the students related to each subject

Subjects 2016-17 2017-18
No of students % of students No of students % of students
Statistics 25 25 30 30
Economics 40 40 42 42
History 35 35 28 28
Total 100 100 100 100

 

asd

 

Pie Chart- The following are the data about the market share of four brands of TV sets sold in Panipat and Ambala. Present the data in the pie chart.

Brand of sets Units sold in Panipat Units sold in Ambala
Samsung 480 625
Akai 360 500
Onida 240 438
Soni 120 312

 

Solution.

Total sets sold in Panipat and  Ambala are 1200 and 1875 respectively. Data are to be represented by two circles whose radii are in the ratio of square roots of total TV sets sold in each city in the ratio of 1: 1. The calculation of the angle of sector corresponding to sales of each brand is given bellow.

 

Brands of sets

Panipat Ambala
Sets sold Sales (Rs) % Angle of sector Sets sold Sales (Rs) % Angle of sector
Samsung 480 40 625 33.3
Akai 360 30 500 26.7
Onida 240 20 438 23.4
Soni 120 10 312 16.6
Total 1200 100 360 1875 100 360

stats

 

Histogram- The histogram is the special case of a bar diagram, it is the bar diagram without a gap between successive rectangle.it is shown by the rectangles of certain height and width. Its height is directly proportional to the frequency and width is the gap between two observations called class interval in such a way that for next rectangle the higher limit of the previous rectangle is the lower limit for the next rectangle.

Example. Show the following information through a histogram.

The age group 4 – 8 8 – 12 12 – 16 16 – 20
No.of children in school 300 500 200 400

satatistics 4

 

Frequency Polygon –The frequency polygon is one of the ways of showing the frequency distribution of data. In this way, the frequency of data is shown along the y-axis and the class interval of observations are allocated along the x-axis. After doing this mark the midpoints of class interval called class mark. Mark out the corresponding frequency to each class mark in the graph, join all the points through a straight line, the graph obtained is known as a frequency polygon.

Frequency  Curve. If frequency polygon is drawn by the smooth hand then the graph so formed is known as the frequency curve.

Frequency polygon can be drawn with the histogram and without histogram, with the histogram, the midpoints of the width of each rectangle are joined together and thus the graph shown by straight lines so formed is known as a frequency polygon.

ogive

 

Ogive –This is the graph in which cumulative frequencies are shown along the y-axis and class intervals shown along the x-axis. The ogive shows the frequencies distribution under a curve or above a curve known as give. The ogive is of two kinds (a) More than ogive (b) Less than ogive.

 

Ages of persons in a village 0 – 10 10 – 20 20 – 30 30 – 40 40 – 50
Number of persons 100 150 50 50 50

 

Ages of persons in a village Frequency Cumulative frequency
More than Less than
0-10 100 100 400
10-20 150 250 300
20-30 50 300 150
30-40 50 350 100
40-50 50 400 50

ogive 6

 

 

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Chapter 1- Number System Chapter 9-Areas of parallelogram and triangles
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Chapter 3- Coordinate Geometry Chapter 11-Construction
Chapter 4- Linear equations in two variables Chapter 12-Heron’s Formula
Chapter 5- Introduction to Euclid’s Geometry Chapter 13-Surface Areas and Volumes
Chapter 6-Lines and Angles Chapter 14-Statistics
Chapter 7-Triangles Chapter 15-Probability
Chapter 8- Quadrilateral

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Chapter 1-Matter in our surroundings Chapter 9- Force and laws of motion
Chapter 2-Is matter around us pure? Chapter 10- Gravitation
Chapter3- Atoms and Molecules Chapter 11- Work and Energy
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Chapter 5-Fundamental unit of life Chapter 13-Why do we fall ill ?
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Chapter 1-Real number Chapter 9-Some application of Trigonometry
Chapter 2-Polynomial Chapter 10-Circles
Chapter 3-Linear equations Chapter 11- Construction
Chapter 4- Quadratic equations Chapter 12-Area related to circle
Chapter 5-Arithmetic Progression Chapter 13-Surface areas and Volume
Chapter 6-Triangle Chapter 14-Statistics
Chapter 7- Co-ordinate geometry Chapter 15-Probability
Chapter 8-Trigonometry

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Chapter 3- Metals and Non-Metals Chapter 11- Human eye and colorful world
Chapter 4- Carbon and its Compounds Chapter 12- Electricity
Chapter 5-Periodic classification of elements Chapter 13-Magnetic effect of electric current
Chapter 6- Life Process Chapter 14-Sources of Energy
Chapter 7-Control and Coordination Chapter 15-Environment
Chapter 8- How do organisms reproduce? Chapter 16-Management of Natural Resources

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Chapter 1-Sets Chapter 9-Sequences and Series
Chapter 2- Relations and functions Chapter 10- Straight Lines
Chapter 3- Trigonometry Chapter 11-Conic Sections
Chapter 4-Principle of mathematical induction Chapter 12-Introduction to three Dimensional Geometry
Chapter 5-Complex numbers Chapter 13- Limits and Derivatives
Chapter 6- Linear Inequalities Chapter 14-Mathematical Reasoning
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Chapter 1-Relations and Functions Chapter 9-Differential Equations
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Chapter 3-Matrices Chapter 11 – Three Dimensional Geometry
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Chapter 5- Continuity and Differentiability Chapter 13-Probability
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