Skip to main content

B. Com. I Practical No. 3 :Diagrammatic representation of data by using Pie Diagram and Bar Diagrams.

Practical No. 3 :Diagrammatic representation of data by using Pie Diagram and Bar Diagrams.

Diagrammatic Presentation.

We have observed the classification and tabulation method. We use this method to take a lot of information and make it fit into a small table. The reason we do this is to make the information more organized and easier to understand.

Tabulation helps us arrange data neatly so that it's not messy and confusing. tabulation is a way to make big files of information look neat and tidy in a table.  but better and beautiful way to represent data using diagrams and graphs.

the diagram and graph have some advantages because that used to visualise the data. that helps to understand and give information easily to any common man or any one, following are the some  advantages of diagram and graph. 

I. Advantages

i. Data Representation: Diagrams and graphs are excellent for presenting data visually, making trends, comparisons, and statistical information easier to understand.

ii. Simplification: Diagrams take complex ideas and simplify them into visual representations that are easier to grasp. the both diagrams and graphs are so simple that even an ordinary man also will understand properly. 

iii. Clarity: Visualizing information through diagrams can make it clearer and more understandable. Diagrams show relationships, connections, and patterns that might be hard to explain with words alone.

iv. Memory Aid: Visuals are often easier to remember than written or spoken words. hence diagram and graph are remember quickly.  they remember longer. 

v. Graphs help in analysis: using graph the data can be analysed with minimum calculations. from the graph we can find median, mode, quartiles etc.

II. Guidelines for drawing diagrams.

i. Title: For each chart give clear and concise title, the title gives exact idea about the diagram or chart.

ii. Simplicity: The diagrams should be simple, and  that are understand anyone. create each chart  must be simple to understand.

iii. Scale: for diagram like bar diagram choose suitable scale. e.g. the scale must be multiple of 5 or 10. i.e. 5, 10, 15, 20. .....or 10, 20, 30, 40,.........etc.

iv. Attractive: The chart should be clean and attractive. 

Types of Diagram. 

i. One- Dimensional Diagram - Bar Diagram

ii. Two- Dimensional Diagram - Pie -chart

i. Bar Diagram: 

the bar diagram is the most common type of diagram, and it is simple diagram. In bar diagram the variable represented by thick bars with uniform width. and the height of the bar is proportional to the value of that variable. the bars are separated by uniform distance. means that the bar are differ by only height. bars are draw vertically as well as horizontally. but vertical bars are more attractive and vertical bar are popular. this bar diagrams are easily understood to every one.

In a Simple bar diagram we represent only one variable. e.g. to use bar diagram representing the class-wise student strength:

Class

Student Strength

Class 1

27

Class 2

34

Class 3

25

Class 4

45

Class 5

26

 bar diagram is


for drawing bar diagram simply put or select the value in below 
Enter Value Tab to get bar diagram, this is used to check your bar diagram is correct or not.

2. Pie-Diagram:

Pie-Diagram is a circular chart that can be used to represent data as slice of a Pie. When we are interested to represent more that three or four variable the bar-diagram is more complex and it doesn’t give proper visualization of data to understand. That case we use Pie-chart is a circle that divided into sections or slices. And the area on each section is proportional to the size or the value of the variable.

For constructing the Pie-Chart the circle is divided into section is  proportional to the angle at the center of circle. We draw a angle at the center that proportional to the value of variable or data. The angle is calculated as  

e.g. to Draw a Pie-Diagram to represent the following data. For Family expenditure in percentage.

Items

Family expenditure %

Cloths

27

Food

35

Rent

18

Other

20

First we find the angles for Items.

Here total expenditure of family is = 100






the pie-chart is 


Example2: Draw a Pie-Diagram to represent the following data. Data of year wise products of certain company.

Year

Products

1998

15

1999

78

2000

89

2001

125

2002

87

 

First we find the angles for each year.

Here total product is 15+78+89+125+87  = 394







the Pie-Chart is 


Shikshan Prasarak Santha’s

PADMABHUSHAN VASANTRAODADA PATIL MAHAVIDHYALAYA

KAVATHE MAHANKAL

DEPARTMENT OF STATISTICS

B. Com. I: Practical - I

Expt. No. 3                                                                                       Date:    /    / 2025

Title: Diagrammatic representation of data by using Pie Diagram and Bar Diagrams.

Q.1.  Draw a pie diagram for the following expenditure of some families in a year.

Items

Food

Cloths

Rent

Medical care

Other

Expenditure (RS)

945

325

520

210

400

 

Q.2.  Draw a pie diagram for the following data.

Item

Raw Material

labour

Supervisor

office

Other

Expenditure (%)

30

20

10

20

20

Q.3. Following table gives the Birth rates per thousand of different countries.

Country

India

Germany

U.K.

China

Sweden

Birth Rate

34

17

20

40

30

    Represent the above data by a Simple bar diagram.

Q.4  The following table gives data related to production of two items A and B in a factory.

Year

2000

2001

2002

2003

2004

Production of A

200

210

170

180

210

Production of B

150

170

150

160

180

      Represent the data by Sub-divided bar diagram.

Q.5.  Draw a suitable diagram to represent the following data.

Occupation

India

U.S.A

U.K.

Agriculture

71

13

5

Services

15

46

55

Other

14

41

40

 

Q.6. The below table gives data relating to import and export. Represent a data by a Multiple bar diagram.

Year

Export(RS)

Import (RS)

1991

350

250

1992

320

300

1993

310

240

1994

300

210

***


Comments

Popular posts from this blog

MCQ'S based on Basic Statistics (For B. Com. II Business Statistics)

    (MCQ Based on Probability, Index Number, Time Series   and Statistical Quality Control Sem - IV)                                                            1.The control chart were developed by ……         A) Karl Pearson B) R.A. fisher C) W.A. Shewhart D) B. Benjamin   2.the mean = 4 and variance = 2 for binomial r.v. x then value of n is….. A) 7 B) 10 C) 8 D)9   3.the mean = 3 and variance = 2 for binomial r.v. x then value of n is….. A) 7 B) 10 C) 8 D)9 4. If sampl...

Basic Concepts of Probability and Binomial Distribution , Poisson Distribution.

 Probability:  Basic concepts of Probability:  Probability is a way to measure hoe likely something is to happen. Probability is number between 0 and 1, where probability is 0 means is not happen at all and probability is 1 means it will be definitely happen, e.g. if we tossed coin there is a 50% chance to get head and 50% chance to get tail, it can be represented in probability as 0.5 for each outcome to get head and tail. Probability is used to help us taking decision and predicting the likelihood of the event in many areas, that are science, finance and Statistics.  Now we learn the some basic concepts that used in Probability:  i) Random Experiment OR Trail: A Random Experiment is an process that get one or more possible outcomes. examples of random experiment include tossing a coin, rolling a die, drawing  a card from pack of card etc. using this we specify the possible outcomes known as sample pace.  ii)Outcome: An outcome is a result of experi...

Statistical Inference: Basic Terms and Definitions.

  📚📖 Statistical Inference: Basic Terms. The theory of estimation is of paramount importance in statistics for several reasons. Firstly, it allows researchers to make informed inferences about population characteristics based on limited sample data. Since it is often impractical or impossible to measure an entire population, estimation provides a framework to generalize findings from a sample to the larger population. By employing various estimation methods, statisticians can estimate population parameters such as means, proportions, and variances, providing valuable insights into the population's characteristics. Second, the theory of estimating aids in quantifying the estimates' inherent uncertainty. Measures like standard errors, confidence intervals, and p-values are included with estimators to provide  an idea of how accurate and reliable the estimates are. The range of possible values for the population characteristics and the degree of confidence attached to those est...

Index Number

 Index Number      Introduction  We seen in measures of central tendency the data can be reduced to a single figure by calculating an average and two series can be compared by their averages. But the data are homogeneous then the average is meaningful. (Data is homogeneous means data in same type). If the two series of the price of commodity for two years. It is clear that we cannot compare the cost of living for two years by using simple average of the price of the commodities. For that type of problem we need type of average is called Index number. Index number firstly defined or developed to study the effect of price change on the cost of living. But now days the theory of index number is extended to the field of wholesale price, industrial production, agricultural production etc. Index number is like barometers to measure the change in change in economics activities.   An index may be defined as a " specialized  average designed to measure the...

B. Com. -I Statistics Practical No. 1 Classification, tabulation and frequency distribution –I: Qualitative data.

  Shree GaneshA B. Com. Part – I: Semester – I OE–I    Semester – I (BASIC STATISTICS PRACTICAL-I) Practical: 60 Hrs. Marks: 50 (Credits: 02) Course Outcomes: After completion of this practical course, the student will be able to: i) apply sampling techniques in real life. ii) perform classification and tabulation of primary data. iii) represent the data by means of simple diagrams and graphs. iv) summarize data by computing measures of central tendency.   LIST OF PRACTICALS: 1. Classification, tabulation and frequency distribution –I: Qualitative data. 2. Classification, tabulation and frequency distribution –II : Quantitative data. 3. Diagrammatic representation of data by using Pie Diagram and Bar Diagrams. 4. Graphical representation of data by using Histogram, Frequency Polygon, Frequency Curve and     Locating Modal Value. 5. Graphical representation of data by using Ogive Curves and Locating Quartile Values....

Method of Moment & Maximum Likelihood Estimator: Method, Properties and Examples.

 Statistical Inference I: Method Of Moment:   One of the oldest method of finding estimator is Method of Moment, it was discovered by Karl Pearson in 1884.  Method of Moment Estimator Let X1, X2, ........Xn be a random sample from a population with probability density function (pdf) f(x, θ) or probability mass function (pmf) p(x) with parameters θ1, θ2,……..θk. If μ r ' (r-th raw moment about the origin) then μ r ' = ∫ -∞ ∞ x r f(x,θ) dx for r=1,2,3,….k .........Equation i In general, μ 1 ' , μ 2 ' ,…..μ k ' will be functions of parameters θ 1 , θ 2 ,……..θ k . Let X 1 , X 2 ,……X n be the random sample of size n from the population. The method of moments consists of solving "k" equations (in Equation i) for θ 1 , θ 2 ,……..θ k to obtain estimators for the parameters by equating μ 1 ' , μ 2 ' ,…..μ k ' with the corresponding sample moments m 1 ' , m 2 ' ,…..m k ' . Where m r ' = sample m...

Time Series

 Time series  Introduction:-         We see the many variables are changes over period of time that are population (I.e. population are changes over time means population increase day by day), monthly demand of commodity, food production, agriculture production increases and that can be observed over period of times known as time series. Time series is defined as a set of observation arranged according to time is called time series. Or a time Series is a set of statistical observation arnging chronological order. ( Chronological order means it is arrangements of variable according to time) and it gives information about variable.  Also we draw the graph of time series to see the behaviour of variable over time. It can be used of forecasting. The analysis of time series is helpful to economist, business men, also for scientist etc. Because it used to forecasting the future, observing the past behaviour of that variable or items. Also planning for future...

Non- Parametric Test: Run Test

Non- Parametric Test  A Non-Parametric tests is a one of the part of Statistical tests that non-parametric test does not assume any particular distribution for analyzing the variable. unlike the parametric test are based on the assumption like normality or other specific distribution  of the variable. Non-parametric test is based on the rank, order, signs, or other non-numerical data. we know both test parametric and non-parametric, but when use particular test? answer is that if the assumption of parametric test are violated such as data is not normally distributed or sample size is small. then we use Non-parametric test they can used to analyse categorical data  or ordinal data and data are obtained form in field like psychology, sociology and biology. For the analysis use the  some non-parametric test that are Wilcoxon signed-ranked test, mann-whiteny U test, sign test, Run test, Kruskal-wallis test. but the non-parametric test have lower statistical power than ...