Understand Human Wants and It’s Characteristics

In day to day language desire and want mean the same thing. But in economics, they have different meanings. Wants are the basis for human behaviour to buy and consume goods. All the desires and aspirations and motives of humans are known as human wants in economics.

Characteristics of Human Wants

Wants are unlimited

Human wants are countless in number and various in kinds. When one want is satisfied another want crops up. Human wants, multiply with the growth of civilization and development.

Wants become habits

Wants become habits; for example, when a man starts reading a newspaper in the morning, it becomes a habit. The same is the case with drinking tea or chewing pans.

Wants are Satiable

Though we cannot satisfy all our wants, at the same time we can satisfy particular wants at a given time. When one feels hungry, he takes food and that want is satisfied.

Wants are Alternative

There are alternative ways to satisfy a particular want eg. Idly, dosa or chappati.

Wants are Competitive

All our wants are not equally important. So, there is competition among wants. Hence, we have to choose more urgent wants than less urgent wants.

Wants are Complementary

Sometimes, the satisfaction of a particular want requires the use of more than one commodity. Example: Car and Petrol, Ink and Pen.

Wants are Recurring

Some wants occur again and again. For example, if we feel hungry, we take food and satisfy our want. But after some time, we again feel hungry and want food.

Deduction and Induction Methods of Economics

Like any other science, Economics also has its laws or generalisations. These laws, govern the activities in the various divisions of Economics such as Consumption, Production, Exchange anDeduction and Induction Methods of Economicsd Distribution. The logical process of arriving at a law or generalization in science is called its method.

Economics uses two methods: Deduction and Induction. Economists today say both these methods are complementary. Alfred  Marshall has rightly remarked: “Inductive and Deductive methods are both needed for scientific thought, as the right and left foot are both needed for walking”.

Deductive Method of Economic Analysis

The deductive method is also named an analytical or abstract method. It consists of deriving conclusions from general truths; it takes few general principles and applies them to draw conclusions. The classical and neoclassical school of economists notably, Ricardo, Senior, J S Mill, Malthus, Marshall, Pigou, applied the deductive method in their economic investigations.

Steps of Deductive Method

Step 1: The analyst must have a clear and precise idea of the problem to be inquired into.
Step 2: The analyst clearly defines the technical terms used in the analysis. Further, assumptions of the theory are to be precise.
Step 3: Deduce the hypothesis from the assumptions taken.
Step 4: Hypotheses should be verified through direct observation of events in the real world and through statistical methods. (eg) There exists an inverse relationship between price and demand of a good.

Inductive Method of Economic Analysis

The inductive method, also called the empirical method, is adopted by the “Historical School of Economists”. It involves the process of reasoning from particular facts to a general principle. Economic generalizations are derived in this method, on the basis of

  • Experimentations
  • Observations
  • Statistical methods

Steps of Inductive Method

Step 1: Data are collected about a certain economic phenomenon. These
are systematically arranged and the general conclusions are drawn from
Step 2: By observing the data, conclusions are easily drawn.
Step 3: Generalization of the data and then Hypothesis Formulation
Step 4: Verification of the hypothesis (eg. Engel’s law)

According to Engel’s Law “The proportion of total expenditure incurred on food items declines as total expenditure [which is proxy for income] goes on increasing.”

Subsetting vector in R

In R you can subset various objects such as Vector, Matrix and List.

There are three operators that can be used to extract subsets of R objects.
• The[ operator always returns an object of the same class as the original. It can be used to select multiple elements of an object
• The [[ operator is used to extract elements of a list or a data frame. It can only be used to extract a single element and the class of the returned object will not necessarily be a list or data frame.
• The $ operator is used to extract elements of a list or data frame by literal name. Its semantics are similar to that of [[.

Subsetting a Vector

Vectors are basic objects in R and they can be subsetted using the [ operator

Extracting single element

> vowels<-c("a","e","i","o","u")
> vowels[1]            ## Extract the first element
[1] "a"
> x<-vowels[1]        ## Extract the first element as new variable x
> vowels[2]           ## Extract the second element
[1] "e"

Extracting multiple-element

The [ operator can be used to extract multiple elements of a vector bypassing the operator an integer
sequence. Here we extract the first four elements of the vector.

> vowels[1:4]
[1] "a" "e" "i" "o"
> x<-vowels[1:4]

The sequence does not have to be in order; you can specify any arbitrary integer vector.

vowels[c(1, 3, 4)]
[1] "a" "i" "o"
> x<-vowels[c(1, 3, 4)]

We can also pass a logical sequence to the [ operator to extract elements of a vector that satisfy a given condition. For example, here we want the elements of vowels that come lexicographically after the letter “a”.

> l<-vowels > "a"
> l

Another, more compact, way to do this would be to skip the creation of a logical vector and just subset the vector directly with the logical expression.

vowels1<-vowels[vowels > "a"]
> vowels1
[1] "e" "i" "o" "u"

In the next post let us see how to subset a matrix and list.

Important and Basic Terms in Accounting

Are you learning accounts? Have you ever puzzled after looking at the financial statements of a company? In this post, you will learn some key terms that will ease your understanding of accounting and Profit & Loss, Balance sheet.


Entity means a reality that has a definite individual existence. Business entity means a specifically identifiable business enterprise like Departmental Stores, Jewellers, BHEL Limited, etc. An accounting system is always devised for a specific business entity (also called an accounting entity).


An event involving some value between two or more entities. It can be a purchase of goods, receipt of money, payment to a creditor, incurring expenses, etc. It can be a cash transaction or a credit transaction.


Assets are the economic resources of an enterprise that can be usefully expressed in monetary terms. Assets are items of value used by the business in its operations. For example, a Logistics company owns a fleet of trucks, which is used by it for delivering goods; the trucks, thus, provide economic benefit to the enterprise. This item will be shown on the asset side of the balance sheet of the Logistics company. Assets can be broadly classified into two types: current and Non-current.


Liabilities are obligations or debts that an enterprise has to pay at some time in the future. They represent creditors’ claims on the firm’s assets. Both small and big businesses find it necessary to borrow money at one time or the other and to purchase goods on credit. Departmental Store, for example, purchases goods for Rs.1,00,000 on credit for a month from XYZ Foods on March 25, 2021. If the balance sheet of Departmental Store is prepared as of March 31, 2021, XYZ Foods will be shown as creditors on the liabilities side of the balance sheet. If Departmental Store takes a loan for a period of three years from SBI Bank, this will also be shown as a liability in the balance sheet of Departmental Store. Liabilities are classified as current and non-current


Amount invested by the owner in the firm is known as capital. It may be brought in the form of cash or assets by the owner for the business entity capital is an obligation and a claim on the assets of the business. It is, therefore, shown as capital on the liabilities side of the balance sheet.


Sales are total revenues from goods or services sold or provided to customers. Sales may be cash sales or credit sales.


These are the amounts of the business earned by selling its products or providing services to customers, called sales revenue. Other items of revenue common to many businesses are commission, interest, dividends, royalties, rent received, etc. Revenue is also called income.


Costs incurred by a business in the process of earning revenue are known as expenses. Generally, expenses are measured by the cost of assets consumed or services used during an accounting period. The usual items of expenses are depreciation, rent, wages, salaries, interest, cost of heater, light and water, telephone, etc.


Spending money or incurring liability for some benefit, service or property received is called expenditure. Purchase of goods, purchase of machinery, purchase of furniture, etc. are examples of expenditure. If the benefit of expenditure is exhausted within a year, it is treated as an expense (also called revenue expenditure). On the other hand, the benefit of an expenditure lasts for more than a year, it is treated as an asset (also called capital expenditure) such as the purchase of machinery, furniture, etc.


The excess of revenues of a period over its related expenses during an accounting year is profit. Profit increases the investment of the owners.


A profit that arises from events or transactions which are incidental to business such as the sale of fixed assets, winning a court case, appreciation in the value of an asset.


The excess of expenses of a period over its related revenues is termed as a loss. It decreases in owner’s equity. It also refers to money or money’s worth lost (or cost incurred) without receiving any benefit in return, e.g., cash or goods lost by theft or a fire accident, etc. It also includes a loss on sale of fixed assets.


Discount is the deduction in the price of the goods sold. It is offered in two ways. Offering deduction of an agreed percentage of list price at the time selling goods is one way of giving a discount. Such a discount is called ‘trade discount’. It is generally offered by manufacturers to wholesalers and by wholesalers to retailers. After selling the goods on a credit basis the debtors may be given a certain deduction in the amount due in case if they pay the amount within the stipulated period or earlier. This deduction is given at the time of payment on the amount payable. Hence, it is called a cash discount. Cash discount acts as an incentive that encourages prompt payment by the debtors.


The documentary evidence in support of a transaction is known as a voucher. For example, if we buy goods for cash, we get a cash memo, if we buy on credit, we get an invoice; when we make a payment we get a receipt and so on.


It refers to the products in which the business unit is dealing, i.e. in terms of which it is buying and selling or producing and selling. The items that are purchased for use in the business are not called goods. For example, for a furniture dealer purchase of chairs and tables is termed as goods, while for
others it is furniture and is treated as an asset. Similarly, for a stationery merchant, stationery is goods, whereas for others it is an item of expense (not purchases)


Withdrawal of money and/or goods by the owner from the business for personal use is known as drawings. Drawings reduce the investment of the owners.


Purchases are the total amount of goods procured by a business on credit and on cash, for use or sale. In a trading concern, purchases are made of merchandise for resale with or without processing. In a manufacturing concern, raw materials are purchased, processed further into finished goods and then sold. Purchases may be cash purchases or credit purchases.


Stock (inventory) is a measure of something on hand goods, spares and other items in a business. It is called Stock in hand. In a trading concern, the stock on hand is the number of goods that are lying unsold as at the end of an accounting period is called closing stock (ending inventory). In a manufacturing company, closing stock comprises raw materials, semi-finished goods and finished goods
on hand on the closing date. Similarly, opening stock (beginning inventory) is the amount of stock at the beginning of the accounting period.


Debtors are persons and/or other entities who owe to an enterprise an amount for buying goods and services on credit. The total amount standing against such persons and/or entities on the closing date is shown in the balance sheet as sundry debtors on the asset side.


Creditors are persons and/or other entities who have to be paid by an enterprise an amount for providing the enterprise goods and services on credit. The total amount standing to the favour of such persons and/or entities on the closing date is shown in the Balance Sheet as sundry creditors on the liabilities side.

Types or Branches of Accounting

The economic development and technological advancements have resulted in an increase in the scale of operations and the advent of the company form of business organisation. This has made the management function more and more complex and increased the importance of accounting information. This gave rise to special branches of accounting. These are briefly explained below :

Financial accounting: The purpose of this branch of accounting is to keep a record of all financial transactions so that:

  • the profit earned or loss sustained by the business during an accounting period
    can be worked out,
  • the financial position of the business as at the end of the accounting period
    can be ascertained, and
  • the financial information required by the management and other interested
    parties can be provided.

Cost Accounting: The purpose of cost accounting is to analyse the expenditure so as to ascertain the cost of various products manufactured by the firm and fix the prices. It also helps in controlling the costs and providing necessary costing information to management for decision-making.

Management Accounting: The purpose of management accounting is to assist the management in making rational policy decisions and to evaluate the impact of its decisions and actions.

How to Manually Enter Data in R

R is one of the most popular and powerful programming languages used in data analytics.

If you already have your data located in a CSV file or Excel file, you can follow the steps in these tutorials to import it into R:

  • How to Import CSV Files into R
  • How to Import Excel Files into R

However, sometimes you may want to manually enter raw data into R. Let see how to do it

Entering a Vector in R

If you want to enter a single vector of numeric values into Rm, use the following syntax:

#create vector of numbers

#Method 1
numbers <- (1:25)

#Method 2
even <- c(2,4,6,8,10)

#display class of vector

[1] "integer"


[1] "numeric"

#display vector of numeric values

[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25


[1] 2 4 6 8 10

#return fifth element in vector

[1] 5


[1] 10

Use the same syntax to enter a vector of character values as well

#create vector of character values
metal <- c("iron", "silver", "gold", "steel")

#display class of vector

[1] "character"

#display vector of character values

[1] "iron" "silver" "gold" "steel"

Entering a DATAFRAME in R

If you want to create a data frame use the following syntax

#create data frame
football_players <- data.frame(player=c("Salah", "Jesus", "Ozil", "Pepe", "Kane"),
 goals=c(15, 10, 8, 10, 16),
 assists=c(4, 7, 10, 4, 5))

#display data frame

  player goals assists
1 Salah    15    4
2 Jesus    10    7
3 Ozil      8   10
4 Pepe     10    4
5 Kane     16    5

#display class of df

[1] "data.frame"

#return value in third row and second column

[1] 8

Entering a Matrix in R

If you want to create a matrix use the following syntax

#create matrix with two columns and five rows
goals=c(15, 10, 8, 10, 16)

assists=c(4, 7, 10, 4, 5)

#column bind the two vectors together to create a matrix
mat <- cbind(goals, assists)

#display matrix

     goals assists
[1,] 15    4
[2,] 10    7
[3,] 8     10
[4,] 10    4
[5,] 16    5

#display class of mat

[1] "matrix" "array" 

#return value in fourth row and second column
mat[4, 2]


Note: A matrix requires each column to be the same type, unlike data frames.

You learn more about Data analysis using R here.

Different Scale of Measurements – nominal, ordinal, interval and ratio scales

The level or scale of measurement depends on the properties of the data. There are four
types of scales are used in business research. These include nominal, ordinal, interval and ratio scales. Variables can be classified as discrete or continuous.

What is a Nominal Scale?

A nominal scale is the simplest type of scale. The numbers or letters assigned to objects serve as labels for identification or classification. For example, names, player list, gender are categorical variables; and one can put the level ‘M’ for Male and ‘F’ for Female, or ‘1’ for male and ‘2’ for female, or ‘1’ for female and ‘2’ for male. Other examples include marital status, religion, race, colour and employment status, and so forth.

What is an Ordinal Scale?

When a nominal scale follows an order then it becomes an ordinal scale. In other words, an ordinal scale arranges objects or categorical variables according to an ordered relationship. Ordinal data are often referred to as ranked data because the data are ordered from highest to lowest, or biggest to smallest.  So, the ranking of nominal scales is an essential prior criterion for ordinal scales. A typical ordinal scale in business research asks respondents to rate career opportunities and company brands as ‘excellent, ‘good’, ‘fair’ or ‘poor’. Other examples would be (i) result of examination: first, second, third classes and fail; (ii) quality of products.

What is an Interval Scale?

The interval scale indicates the distance or difference in units between two events. In other words, such scales not only indicate order but also measure the order or distance in units of equal intervals. It is important to note that the location of the zero points is arbitrary. To take an example, in the price index, the number of the base year is set to be usually 100. Another classic example of an interval scale is the temperature where the initial point is always arbitrary.

What is a Ratio Scale?

Ratio scales have absolute rather than relative quantities. In other words, if an interval scale has an absolute zero then it can be classified as a ratio scale. The absolute zero represents a point on the scale where there is an absence of the given attribute. Ratio data have all four properties of measurement—identity, magnitude, equal unit size, and absolute zero. For examples, age, money and weights are ratio scales because they possess absolute zero and interval properties.

What is Discrete variables and Continuous variables?

Variables can be classified in terms of whether they are discrete or continuous in nature. Based on the level or scale of measurement the variables are classified as nominal, ordinal, interval and ratio scales.

Discrete variables

Discrete variables usually consist of whole number units or categories. They are made up of chunks or units that are detached and distinct from one another. A change in value occurs a whole unit at a time, and decimals do not make sense with discrete scales.

Most nominal and ordinal data are discrete. For example, gender, designation, and Location are discrete scales.

Some interval or ratio data can be discrete. For example, the number of Covid infections reported as a whole number (discrete data), yet it is also ratio data (you can have a true zero and form ratios).

Continuous variables

Continuous variables usually fall along a continuum and allow for fractional amounts. The term continuous means that it “continues” between the whole-number units.

Examples of continuous variables are Age (22.7 years), Height (64.5 inches), and Weight (113.25 pounds). Most interval and ratio data are continuous in nature.

Discrete and continuous data are more important in research design and data presentation.

How to Read and Understand a Journal Article / Research Article?

People new to research often find it hard to read and understand an article. Research articles have a very specific format. They usually have five main sections: Abstract, Introduction, Method, Results, and Discussion. Let’s briefly discuss each section below.


The Abstract is a brief description of the entire research paper. It should not exceed 250 words and ranges between 150- 250 words. The Abstract describes the problem under investigation and the purpose of the study; the participants / Sample and research methodology; the findings, including statistical significance levels; and the conclusions and implications or applications of the study.


The Introduction has three basic components: an introduction to the problem under study; a review of relevant previous research, which cites works that are important and significant for the study; and the purpose and rationale for the study.


The Method section describes exactly how the study was conducted, in sufficient detail that a person who reads the Method section could replicate the study. The Method section is generally divided into subsections. Although the subsections vary across papers, the most common subsections are Sample, Participants, Materials or Apparatus, and Procedure. The Participants subsection includes a description of the participants and how they were obtained. The Materials subsection usually describes any testing materials that were used, such as a particular test or inventory or a type of problem that participants were asked to solve. An Apparatus subsection describes any specific equipment that was used. The Procedure subsection summarizes each step in the execution of the research, including the groups used in the study, instructions given to the participants, the experimental manipulation, and specific control features in the design.


The Results section summarizes the data collected and the type of statistic used to analyze the data. In addition, the results of the statistical tests used are reported with respect to the variables measured and/or manipulated. This section should include a description of the results only, not an explanation of the results. In addition, the results are often depicted in tables and graphs or figures.


The results are evaluated and interpreted in the Discussion section. Typically, this section begins with a restatement of the predictions of the study and tells whether or not the predictions were supported. It also typically includes a discussion of the relationship between the results and past research and theories. Highlight the implications for future research are presented.