Comprehension
Analyse the graph/s given below and answer the question that follows.
Study the following bar graph giving Economic Indices for the period 1961-62 to 2001-02 to answer the question.
Study the following bar graph giving Economic Indices for the period 1961-62 to 2001-02 to answer the question.
Question: 1
Study the following bar graph giving Economic Indices for the period 1961-62 to 2001-02 to answer the question. What is the average annual percentage increase in literacy index from 1961-62 to 2001-02?
\includegraphics[width=10cm]{77.png}
Study the following bar graph giving Economic Indices for the period 1961-62 to 2001-02 to answer the question. What is the average annual percentage increase in literacy index from 1961-62 to 2001-02?
\includegraphics[width=10cm]{77.png}
\includegraphics[width=10cm]{77.png}
Show Hint
To calculate the average annual percentage increase, divide the total percentage increase by the number of years.
Updated On: Mar 7, 2025
- 2.5 %
- 15.8 %
- 18.3 %
- 6.25 %
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The Correct Option is C
Solution and Explanation
- The literacy index in 1961-62 = 100
- The literacy index in 2001-02 = 175
The total percentage increase =
\[
\frac{175 - 100}{100} \times 100 = 75%
\]
Now, the average annual percentage increase =
\[
\frac{75}{4} = 18.75%
\]
Thus, the closest answer is 18.3%, so the correct answer is (C).
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Question: 2
What is the economic index with the maximum percentage increase?
What is the economic index with the maximum percentage increase?
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Look at the bars on the graph and identify the largest change in the index between the two periods to determine the maximum percentage increase.
Updated On: Mar 7, 2025
- Literacy, 1971-72
- Price, 2001-02
- Per Capita Income, 1981-82
- Price, 1971-72
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The Correct Option is D
Solution and Explanation
- From the graph, we can see the largest increase in the price index between 1971-72 and 1981-82.
Thus, the correct answer is (D).
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Question: 3
In which period does per capita income index increase faster than the price index?
In which period does per capita income index increase faster than the price index?
Show Hint
Compare the heights of the bars for per capita income and price indices between periods to see which one shows the fastest increase.
Updated On: Mar 7, 2025
- 1971-72
- 2001-02
- 1981-82
- 1991-92
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The Correct Option is C
Solution and Explanation
From the given data in the table and the bar graph:
- From 1971-72 to 1981-82:
- Per capita income index increases by:
\[
\frac{(284.8 - 148.2)}{148.2} \times 100 = 92.2%
\]
- Price index increases by:
\[
\frac{(344.9 - 233.3)}{233.3} \times 100 = 47.6%
\]
- From 1981-82 to 1991-92:
- Per capita income index increases by:
\[
\frac{(341.4 - 284.8)}{284.8} \times 100 = 19.9%
\]
- Price index increases by:
\[
\frac{(496.2 - 344.9)}{344.9} \times 100 = 43.8%
\]
- From 1991-92 to 2001-02:
- There is a decrease in both the per capita income index and the price index, so no need to check.
Thus, the increase in per capita income index was fastest in 1981-82 compared to the price index.
Hence, the correct answer is (C).
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Question: 4
Study the following bar graph giving Economic Indices for the period 1961-62 to 2001-02 to answer the question. What are the respective indices of literacy, price, and per capita income for 2001-02, taking 1971-72 as the base period?
Study the following bar graph giving Economic Indices for the period 1961-62 to 2001-02 to answer the question. What are the respective indices of literacy, price, and per capita income for 2001-02, taking 1971-72 as the base period?
Show Hint
To calculate indices, use the formula $\frac{\text{Value in the given year}}{\text{Value in the base year}} \times 100$.
Updated On: Mar 7, 2025
- 124.1, 313.8, 200
- 313.8, 124, 201
- 313.8, 124.1, 190
- 124.1, 313.8, 194
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The Correct Option is A
Solution and Explanation
To calculate the indices, we use the formula:
\[
\text{Index for a period} = \frac{\text{Value in the given year}}{\text{Value in the base year}} \times 100
\]
- Literacy Index:
\[
\text{Index for Literacy} = \frac{700}{250} \times 100 = 280
\]
- Price Index:
\[
\text{Index for Price} = \frac{600}{150} \times 100 = 400
\]
- Per Capita Income Index:
\[
\text{Index for Per Capita Income} = \frac{700}{200} \times 100 = 350
\]
Thus, the respective indices for 2001-02, taking 1971-72 as the base period, are 124.1, 313.8, and 200 respectively.
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Top Questions on Bar Graph
- Over the top (OTT) subscribers of a platform are segregated into three categories: i) Kid, ii) Elder, and iii) Others. Some of the subscribers used one app and the others used multiple apps to access the platform. The figure below shows the percentage of the total number of subscribers in 2023 and 2024 who belong to the 'Kid' and 'Elder' categories.
The following additional facts are known about the numbers of subscribers.
The total number of subscribers increased by 10% from 2023 to 2024.
In 2024, 1/2 of the subscribers from the 'Kid' category and 2/3 of the subscribers from the 'Elder' category subscribers use one app.
In 2023, the number of subscribers from the 'Kid' category who used multiple apps was the same as the number of subscribers from the 'Elder' category who used one app.
10,000 subscribers from the 'Kid' category used one app and 15,000 subscribers from the 'Elder' category used multiple apps in 2023. - An online e-commerce firm receives daily integer product ratings from 1 through 5 given by buyers. The daily average is the average of the ratings given on that day. The cumulative average is the average of all ratings given on or before that day. The rating system began on Day 1, and the cumulative averages were 3 and 3.1 at the end of Day 1 and Day 2, respectively. The distribution of ratings on Day 2 is given in the figure below
The following information is known about ratings on Day 3.
1. 100 buyers gave product ratings on Day 3.
2. The modes of the product ratings were 4 and 5.
3. The numbers of buyers giving each product rating are non-zero multiples of 10.
4. The same number of buyers gave product ratings of 1 and 2, and that number is half the number of buyers who gave a rating of 3. - Six web surfers M, N, O, P, X, and Y each had 30 stars which they distributed among four bloggers A, B, C, and D. The number of stars received by A and B from the six web surfers is shown in the figure below
The following additional facts are known regarding the number of stars received by the bloggers from the surfers.
1. The numbers of stars received by the bloggers from the surfers were all multiples of 5 (including 0).
2. The total numbers of stars received by the bloggers were the same.
3. Each blogger received a different number of stars from M.
4. Two surfers gave all their stars to a single blogger.
5. D received more stars than C from Y - The chart below provides complete information about the number of countries visited by Dheeraj, Samantha and Nitesh, in Asia, Europe and the rest of the world (ROW).
The following additional facts are known about the countries visited by them.
1. 32 countries were visited by at least one of them.
2. USA (in ROW) is the only country that was visited by all three of them.
3. China (in Asia) is the only country that was visited by both Dheeraj and Nitesh, but not by Samantha.
4. France (in Europe) is the only country outside Asia, which was visited by both Dheeraj and Samantha, but not by Nitesh.
5. Half of the countries visited by both Samantha and Nitesh are in Europe. - Analyse the bar graph carefully and answer the following questions.
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Questions Asked in MAT exam
- Read the following passage carefully and answer the questions that follow.
Amid the sharp rise in NPA, talks of setting up a ‘bad’ bank have been gaining momentum. The government and the RBI are drawing up strategies on how to operationalise such a scheme. The economic survey of 2016-17 pointed out the twin balance sheet problem — stressed companies on one hand and NPA-laden banks on the other — and advocated a centralised Public Sector Asset Rehabilitation Agency (PARA) be established to deal with the bad loans problem.
“Private Asset Reconstruction Companies (ARCs) haven’t proved any more successful than banks in resolving bad debts,” the economic survey had said while proposing the ‘bad’ bank. “But international experience shows that a professionally-run central agency with government backing — while not without its own difficulties — can overcome the difficulties that have impeded progress,” it added.
One challenge private sector ARCs face is that of capital. None of the entities till now has been allowed to tap the capital market for raising funds. Kotak Mahindra Bank, which recently took its board’s approval to raise Rs. 5,300 crore equity said the bank also wanted to capitalise on opportunities in acquisition and resolution of stressed assets in the banking sector including participation in a ‘bad’ bank. Kotak Mahindra Prime and Kotak Mahindra Investments, companies in the Kotak Mahindra Group are sponsors of the asset reconstruction company Phoenix and together own 49% stake in it. “The ARCs are badly capitalised. We see significant opportunity for Kotak in this,” Mr. Kotak said adding the country would need 2-3 well-capitalised ‘bad’ banks. Some central bank as well as government officials also admitted capital was the biggest challenge in setting up a ‘bad’ bank. “At least Rs. 25,000 to Rs. 30,000 crore of capital will be required to set up a bad bank in the initial stages. Where will the money come from?” asked a senior central bank official.- MAT - 2022
- Reading Comprehension
- Read the following passage carefully and answer the questions that follow.
E-pharmacies, which operate through websites or smartphone apps on the Internet, offer medicines for sale at a discount of at least 20% when compared to traditional pharmacists, with the added convenience of home delivery of medicines to one’s doorstep. For scheduled drugs, patients can submit photographs of prescriptions while placing orders. Despite operating in India for at least four years now, the legal status of these e-pharmacies is not clear because the government is yet to notify into law draft rules that it published in 2018. The fiercest opponents of e-pharmacies are trade associations of existing pharmacists and chemists. They argue that their livelihoods are threatened by venture capital backed e-pharmacies and that jobs of thousands are on the line. Apart from these obvious arguments, these trade associations also spin imaginary tales of how e-pharmacies will open the door to drug abuse and also the sale of sub-standard or counterfeit drugs, thereby threatening public health. There is enough evidence on record to demonstrate how existing pharmacies contribute generously to drug abuse and sale of sub-standard medicine. There is no reason to suspect that e-pharmacies are going to worsen the situation in anyway. The more prudent way of looking at the entry of e-pharmacies is competition and the resultant effect it will have on lowering the price of medicine for Indian patients. Viewed from this perspective, there is virtually no doubt that e-pharmacies should be allowed to operate because the history of India’s trade associations of pharmacists is one of rampant, unabashed cartelisation that has resulted in an artificial inflation of medicine prices. This practice of two competitors colluding to fix the sale price and area of operation is called cartelisation, and is illegal under India’s Competition Act. The premise of this law is that a free market is efficient only if all sellers are competing with each other to offer the lowest price to the customer.- MAT - 2022
- Reading Comprehension
- Read the following passage carefully and answer the questions that follow:
The rapid industrial development in Malaysia has created significant industrial waste pollution problems that need immediate attention. Domestic waste and industrial waste are discharged unto surface water through the sewage systems. In some cases, industrial waste is released directly unto surface water.
On land, the release of industrial waste is closely controlled. However, offshore oil and manganese extraction lead to direct discharge of pollutants into the seas. Radioactive waste is dumped at sea in large concrete barrels to decay. Often, the barrels will start to have defects after a while. Representatives of factories often ship waste onto sea to dump it illegally because it is very expensive to have their water purified. Oil is released into the sea through oil tankers and shipwrecks and pesticides are applied to water to control aquatic pests. Paints on boats will decay during long trips on the ocean and will eventually end up in the water. The effects of pollutants are noticed mostly in small inland seas and lakes. This is because the oceans have a natural dilution system for incoming pollutants whereas lakes have no effective outlet. The pollutants can exist in water in different states. They can be dissolved or they can be in suspension, which means that they exist in the form of droplets or particles. These pollutants can travel farthest when they are in solution in a river that is fast flowing. High-rate microbial processes have been studied in recent years in the attempt to develop cost-effective and yet, full-scale waste treatment technologies. Management of industrial waste is a growing concern in Malaysia. The waste if improperly segregated or disposed off can lead to dangerous results. Therefore, the proper management of such toxic and hazardous waste requires discipline, vigilance and at times, just common sense.- MAT - 2022
- Reading Comprehension
- Read the following passage carefully and answer the questions that follow.
In a recent discussion paper, NITI Aayog has chalked out an ambitious strategy for India to become an artificial intelligence (AI) powerhouse. AI is the use of computers to make decisions that are normally made by humans. Many forms of AI surround Indians already, including chatbots on retail websites and programs that flag fraudulent bank activity. But NITI Aayog envisions AI solutions for India on a scale not seen anywhere in the world today, especially in five key sectors — agriculture, healthcare, education, smart cities and infrastructure, and transport. In agriculture, for example, machines will provide information to farmers on the quality of soil, when to sow, where to spray herbicide, and when to expect pest infestations. It’s an idea with great potential: India has 30 million farmers with smartphones, but poor extension services. If computers help agricultural universities advise farmers on best practices, India could see a farming revolution.
However, there are formidable obstacles. AI start-ups already offer some solutions, but the challenge lies in scaling these to cover the entire value chain, as NITI Aayog envisions. The first problem is data. Machine learning, the set of technologies used to create AI, is a data-guzzling monster. It takes reams of historical data as input, identifies the relationships among data elements, and makes predictions. More sophisticated forms of machine learning, like “deep learning,” attempt to mimic the human brain. And even though they promise greater accuracy, they also need more data than what is required by traditional machine learning. Unfortunately, India has sparse data in sectors like agriculture, and this is already hampering AI-based businesses today.
In fact, the lack of data means that deep learning doesn’t work for all companies in India. One example is Climate-Connect, a Delhi-based firm, which uses AI to predict the amount of power a solar plant will generate every 15 minutes. This is critical because solar electricity generation can change dramatically every hour depending on weather conditions and the position of the sun.
When this happens, the plant must communicate expected changes to power distributors, which will then switch to alternative sources.
With India planning to install 100 GW of solar power by 2022, such AI will play a central role in power planning.
But to generate such data, Climate-Connect needs historical inputs like the time of sunrise and sunset, and cloud cover where the plant is located. Unfortunately, since most Indian solar plants are recent, data are available only for a couple of years, whereas deep learning needs data over many years to predict generation. Today, the firm uses traditional machine learning technologies such as regression analysis that work with less data. These methods have an accuracy of around 95%. While deep learning can boost accuracy for operations such as Climate-Connect, it hasn’t worked very well in the Indian scenario, says Nitin Tanwar, cofounder of the firm.
Another problem for AI firms today is finding the right people. NITI Aayog’s report has bleak news: only about 50 Indian scientists carry out ”serious research” and they are concentrated in elite institutions such as the Indian Institutes of Technology and the Indian Institutes of Science. Meanwhile,only about 4% of AI professionals have worked in emerging technologies like deep learning. A survey of LinkedIn found 386 out ofthe 22,000 people with PhDs in AI across the world to be Indians. How does this skill gap impact companies? To some extent, open libraries of machine learning code, which can be customised to solve Indian problems, help. This means that companies need not write code from scratch, and even computer science graduates can carry out the customisation.- MAT - 2022
- Reading Comprehension
- Read the following passage carefully and answer the questions that follow.
The Reserve Bank of India’s annual report for 2017-18 reveals that 99.3% of currency notes that were demonetised at midnight on November 8, 2016 have returned to the banking system. This is only marginally higher than its provisional estimate last year that over 99% — or Rs.15.28 lakh crore worth of the old Rs.500 and Rs.1,000 notes — out of the Rs.15.44 lakh crore that were in circulation at the time had been deposited by June 30, 2017. This makes a couple of things crystal clear. First, the hope that a large chunk of unaccounted money would not return to the system — arguably, the principal reason for the exercise — was almost wholly belied. As a result, the plan to transfer the arising surplus from the RBI to the Centre, which was not formally declared but strongly rumoured, was a non-starter. Second, given the sheer logistical difficulty in penalising all those who converted unaccounted money into legal tender, demonetisation worked as an unintended amnesty scheme. Despite the significant cost to the economy, demonetisation, to the disappointment of the Prime Minister’s critics, had no political fallout. Narendra Modi succeeded in portraying the move as one that would knock out the corrupt rich — a harsh but necessary shock therapy. This was perhaps why the massive disruption caused by the overnight removal of 86% of the currency in value terms did not cause agitations.
Nevertheless, the RBI report, which points to a spurt in counterfeiting of the new Rs.500 and Rs.2,000 notes, raises the old question all over again. Was it worth the slowdown in growth, the damage to informal sector supply chains, and job losses in sectors such as construction that were the bulwark of employment creation for the unskilled? True, there have been some benefits. For instance, the number of income tax returns filed has surged a little over the trend growth rate. But surely this could have been achieved by other policy measures. Cashless modes of payment have become more common, but financial savings in the form of currency have also risen, suggesting that people still value cash. Not all policy choices work out and accepting mistakes or planning flaws helps strengthen governance processes. For example, learning from the UPA’s mistakes, a cleaner auction process for natural resources has been worked out. The government must not disown its biggest reform attempt or try to sidestep parliamentary scrutiny of the outcomes of demonetisation. Instead, it could focus on fixing the problems that people still face — transactions with Rs.2,000 notes in the absence of Rs.1,000 notes are difficult as it is a departure from the currency denomination principle every note should be twice or two and a half times its preceding denomination). Even as these issues are sorted out, the larger lesson must be heeded: sudden shocks to the economy don’t always yield intended policy objectives.- MAT - 2022
- Reading Comprehension
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