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Practice Question - 54 (Connected Data Sets) | 100 DILR Questions for CAT Preparation PDF Download

DIRECTIONS for the following four questions:
The Table I shows the comparative costs, in US Dollars, of major surgeries in USA and a select few Asian countries.
Practice Question - 54 (Connected Data Sets) | 100 DILR Questions for CAT PreparationThe equivalent of US Dollar in the local currencies is given in Table II.
Practice Question - 54 (Connected Data Sets) | 100 DILR Questions for CAT PreparationA consulting firm found that the quality of the health services were not the same in all the countries above. A poor quality of a surgery may have significant repercussions in future, resulting in more cost in correcting mistakes. The cost of poor quality of surgery is given in Table III.
Practice Question - 54 (Connected Data Sets) | 100 DILR Questions for CAT Preparation
Q1: A US citizen is hurt in an accident and requires an angioplasty, hip replacement and a knee replacement. Cost of foreign travel and stay is not a consideration since the government will take care of it. Which country will result in the cheapest package, taking cost of poor quality into account?
(a) India
(b) Thailand
(c) Malaysia
(d) Singapore
(e) USA

Practice Question - 54 (Connected Data Sets) | 100 DILR Questions for CAT PreparationView Answer  Practice Question - 54 (Connected Data Sets) | 100 DILR Questions for CAT Preparation

Ans: (c)
Total cost incurred by the american citizen in various countries after taking cost of poor quality into account is ( in '000 USD)
America - 57 + 43 + 40 = 140
India - 11 + 9 + 8.5 + 5 + 7 + 9 = 49.5
Thailand - 13 + 12 + 10 + 5 + 5 + 6 = 51
Singapore - 13 + 12 + 13 + 4 + 5 + 4 = 51
Malaysia - 11 + 10 + 8 + 6 + 8 + 4 = 47
Hence the cheapest country is Malaysia.

Q2: Taking the cost of poor quality into account, which country/countries will be the most expensive for knee replacement?
(a) India
(b) Thailand
(c) Malaysia
(d) Singapore
(e) India and Singapore

Practice Question - 54 (Connected Data Sets) | 100 DILR Questions for CAT PreparationView Answer  Practice Question - 54 (Connected Data Sets) | 100 DILR Questions for CAT Preparation

Ans: (a)
Knee replacement cost in the countries given in the options are :
India - 17.5
Thailand - 16
Malaysia - 17
Singapore - 12.
Hence the costliest treatment is in India.

Q3: Approximately, what difference in amount in Bahts will it make to a Thai citizen if she were to get a hysterectomy done in India instead of in her native country, taking into account the cost of poor quality? It costs 7500 Bahts for oneway travel between Thailand and India.
(a) 23500
(b) 40500
(c) 57500
(d) 67500
(e) 75000

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Ans: (d)
Cost of treatment in India in USD ('000) 8 and in Thailand 10.5.
So she pays 2.5 more in Thailand.
Converting in Bahts we get 82500.
Subtracting the total travelling cost of 15000 Baht from the above.
So difference is 67500 Bahts.

Q4: The rupee value increases to Rs.35 for a US Dollar, and all other things including quality, remain the same. What is the approximate difference in cost, in US Dollars, between Singapore and India for a Spinal Fusion, taking this change into account?
(a) 700
(b) 2500
(c) 4500
(d) 8000
(e) No difference

Practice Question - 54 (Connected Data Sets) | 100 DILR Questions for CAT PreparationView Answer  Practice Question - 54 (Connected Data Sets) | 100 DILR Questions for CAT Preparation

Ans: (b) 
Cost for operation in India is around = 5500 * 41.
After Rupee value increases, increased cost in USD = 5500 * 41 / 35 which is around 6500 USD.
Thus the requires difference in price is 9000(for singapore) - 6500 = 2500 USD.

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FAQs on Practice Question - 54 (Connected Data Sets) - 100 DILR Questions for CAT Preparation

1. What are connected data sets and how are they used in data analysis?
Ans. Connected data sets refer to multiple data collections that are related and can be analyzed together to derive insights. These data sets enable analysts to understand correlations and patterns across different variables, enhancing the depth of analysis. They are often used in fields like finance, healthcare, and marketing to link customer behavior, sales data, and demographic information for comprehensive insights.
2. What are some common challenges faced when working with connected data sets?
Ans. Working with connected data sets can pose several challenges, including data integration issues, data quality concerns, and the complexity of managing large volumes of data. Analysts may encounter difficulties in ensuring that data from different sources is compatible and accurately reflects the same criteria. Additionally, maintaining data security and privacy across connected datasets can also be a significant challenge.
3. How can data visualization aid in interpreting connected data sets?
Ans. Data visualization plays a crucial role in interpreting connected data sets by providing visual representations of complex data relationships. Tools like graphs, charts, and dashboards can help reveal trends, patterns, and correlations that may not be immediately apparent in raw data. Effective visualization allows stakeholders to quickly grasp insights and make data-driven decisions.
4. What methods are commonly used to analyze connected data sets?
Ans. Common methods for analyzing connected data sets include statistical analysis, machine learning algorithms, and data mining techniques. Statistical analysis helps in identifying relationships and testing hypotheses, while machine learning can uncover hidden patterns and predict outcomes based on historical data. Data mining techniques are used to extract useful information from large datasets, enhancing the overall analysis.
5. Why is it important to maintain data integrity in connected data sets?
Ans. Maintaining data integrity in connected data sets is essential because it ensures the accuracy and reliability of the analysis. Inaccurate or inconsistent data can lead to misleading conclusions, which may impact decision-making processes. Ensuring data integrity involves regular validation, cleaning, and updating of data to preserve its quality throughout the analysis lifecycle.
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