About themathcompany
Company Description
TheMathCompany (also known as MathCo) is a global leader in AI, data analytics, and engineering solutions. Founded in 2016 with headquarters in Chicago, USA, and Bengaluru, India, the company serves clients across North America, Europe, and Asia. MathCo delivers advanced analytics, AI, and machine learning solutions for businesses in industries such as retail, healthcare, finance, manufacturing, and logistics. Its proprietary AI platform, NucliOS®, helps companies automate analytics workflows, optimize decision-making, and gain actionable insights from complex data.
MathCo’s mission is to help organizations transform their operations using data-driven insights, making it a trusted partner for Fortune 500 companies and mid-sized enterprises alike.
Work Culture & Environment
Collaborative & Open: MathCo promotes a transparent, team-oriented culture with flat hierarchies, encouraging employees to voice ideas and contribute across teams.
Continuous Learning: Employees have access to mentorship, training programs, and workshops on AI, ML, Big Data, and analytics to enhance technical skills.
Global Exposure: With offices in multiple countries, employees work with diverse teams and gain international project experience.
Recognition & Growth: High performers are rewarded with promotions, project ownership, and opportunities for leadership roles.
Innovation-Driven: Encourages experimentation with emerging technologies and creative problem-solving.
Work-Life Balance: Flexible work arrangements and wellness initiatives support employee well-being.
Overall, MathCo provides an intellectually stimulating and growth-oriented environment, ideal for professionals passionate about analytics and AI.
Job Roles & Interview Questions
1. Data Scientist
Skills (for reference): Python, R, SQL, Machine Learning, Data Visualization, Statistical Analysis
Previous Roles (for reference): Data Analyst, ML Engineer, Research Scientist
Q1: How do you approach feature selection in a machine learning model?
I analyze feature importance using statistical tests, correlation analysis, and model-based methods. I also consider domain knowledge to ensure relevance.
Q2: Explain the difference between supervised and unsupervised learning.
Supervised learning uses labeled data to predict outcomes; unsupervised learning identifies patterns in unlabeled data, like clustering or dimensionality reduction.
Q3: How do you handle missing or inconsistent data?
I use imputation techniques like mean/mode replacement, regression imputation, or advanced methods like KNN imputation depending on the dataset.
Q4: Describe a challenging data science project you worked on.
Developed a predictive maintenance model for manufacturing machinery using sensor data, reducing downtime by 20%.
Q5: How do you evaluate model performance?
Using metrics like accuracy, precision, recall, F1-score, ROC-AUC for classification, or RMSE and R² for regression tasks.
Q6: What is your experience with deep learning?
Worked with TensorFlow and PyTorch to implement CNNs for image data and RNNs for time-series analysis.
Q7: How do you stay updated with the latest trends in data science?
Through research papers, online courses, webinars, and participation in professional communities.
2. Data Analyst
Skills (for reference): SQL, Excel, Tableau/Power BI, Python, Statistical Analysis
Previous Roles (for reference): Reporting Analyst, Business Analyst, Market Research Analyst
Q1: How do you ensure accuracy in your data analysis?
By validating data against source systems, cleaning datasets, and performing consistency checks.
Q2: Can you provide an example where your analysis influenced a business decision?
Identified low-performing customer segments via cohort analysis, leading to targeted campaigns that increased conversion by 15%.
Q3: How do you handle large datasets?
I use SQL for data extraction, Pandas in Python for processing, and aggregate or sample data as needed for analysis.
Q4: Describe your experience with data visualization tools.
I have created interactive dashboards in Tableau and Power BI to communicate insights to stakeholders effectively.
Q5: How do you prioritize multiple analysis projects?
By assessing deadlines, business impact, and resource availability to ensure timely and accurate delivery.
Q6: How do you communicate insights to non-technical stakeholders?
Through simple visuals, concise explanations, and actionable recommendations.
Q7: How do you handle confidential or sensitive data?
I follow strict data protection protocols, anonymize sensitive information, and ensure secure storage and access control.
3. Machine Learning Engineer
Skills (for reference): Python, TensorFlow, PyTorch, Model Deployment, Cloud Platforms
Previous Roles (for reference): Data Scientist, AI Researcher, Software Engineer
Q1: How do you deploy machine learning models in production?
Using Docker for containerization, CI/CD pipelines for automation, and monitoring models to maintain performance.
Q2: Explain overfitting and how to prevent it.
Overfitting occurs when the model learns noise from training data. Prevent with regularization, cross-validation, and dropout techniques.
Q3: Describe a machine learning project you implemented.
Built a recommendation engine for an e-commerce platform, increasing user engagement by 25%.
Q4: How do you handle imbalanced datasets?
Techniques include oversampling minority classes, undersampling majority classes, or using class-weighted algorithms.
Q5: Experience with cloud ML platforms?
Worked with AWS SageMaker and Azure ML Studio for training, hyperparameter tuning, and deployment.
Q6: How do you ensure models are scalable?
Optimize algorithms, modularize code, and leverage distributed computing frameworks.
Q7: How do you keep up with ML advancements?
Regularly read research papers, attend conferences, and participate in online AI communities.
4. Business Analyst
Skills (for reference): Requirements Gathering, Process Mapping, Agile, Stakeholder Management
Previous Roles (for reference): Systems Analyst, Product Manager, Project Coordinator
Q1: How do you gather requirements?
Through interviews, workshops, surveys, and reviewing existing process documentation.
Q2: Describe a process improvement initiative you led.
Optimized order fulfillment workflows, reducing delivery time by 20%.
Q3: How do you handle conflicting stakeholder requests?
Facilitate discussions, prioritize based on business impact, and document agreed-upon requirements.
Q4: Experience with Agile methodologies?
Participated in Scrum teams, sprint planning, stand-ups, and retrospectives to ensure iterative delivery.
Q5: How do you ensure project timelines are met?
Track progress using project management tools and proactively mitigate risks or delays.
Q6: How do you manage scope changes?
Assess impact, communicate with stakeholders, and adjust plans accordingly.
Q7: How do you measure project success?
Using KPIs, stakeholder satisfaction, and achieving defined business objectives.
5. Big Data Engineer
Skills (for reference): Hadoop, Spark, SQL/NoSQL, Data Warehousing, ETL
Previous Roles (for reference): Data Engineer, ETL Developer, Database Administrator
Q1: How do you design scalable data pipelines?
Use distributed frameworks like Spark, partition data efficiently, and ensure fault tolerance.
Q2: Difference between SQL and NoSQL?
SQL databases are relational; NoSQL databases are non-relational and handle unstructured data.
Q3: How do you optimize queries for large datasets?
Using indexing, caching, partitioning, and query optimization techniques.
Q4: Example of a big data project?
Built a real-time social media analytics platform processing millions of daily records.
Q5: Ensuring data quality?
Data validation, cleansing routines, and continuous monitoring.
Q6: Experience with cloud-based big data services?
AWS EMR, Google BigQuery, and Azure Data Lake for processing and storage.
Q7: How do you ensure data security?
Encryption, access controls, and adherence to compliance standards.
6. AI Specialist
Skills (for reference): Deep Learning, NLP, Computer Vision, TensorFlow, PyTorch
Previous Roles (for reference): ML Engineer, AI Researcher, Data Scientist
Q1: How do you approach building an AI model?
Define the problem, preprocess data, select algorithms, train, validate, and deploy models.
Q2: Experience with NLP or Computer Vision projects?
Developed sentiment analysis models using NLP and object detection models using CNNs.
Q3: How do you handle overfitting in deep learning?
Use dropout, regularization, and cross-validation techniques.
Q4: How do you evaluate AI model performance?
Use metrics such as accuracy, precision, recall, F1-score, and domain-specific KPIs.
Q5: How do you deploy AI models to production?
Through containerization, REST APIs, and integration with existing systems.
Q6: How do you ensure ethical AI practices?
Avoid bias in data, maintain transparency, and ensure fairness in decision-making.
Q7: How do you stay updated on AI advancements?
Reading research papers, attending conferences, and participating in online AI communities.
Company Background and Industry Position
themathcompany stands at the intersection of data science and business transformation, recognized primarily for its prowess in leveraging analytics and AI to solve complex business problems. Founded in the early 2010s, the company quickly carved a niche in the competitive data science consulting market, serving Fortune 500 clients across industries like retail, telecom, and financial services. Unlike many tech firms that focus solely on product development, themathcompany blends deep domain expertise with technical finesse, positioning itself as an end-to-end analytics partner.
In an industry flooded with startups and traditional consultancies, themathcompany’s hybrid model—combining hands-on analytics implementation with strategic advisory—makes it a sought-after employer for data scientists and engineers who want their work to directly impact business outcomes. This dual focus also shapes their recruitment approach, aiming to attract candidates who are not just technically brilliant but can also engage meaningfully with clients.
How the Hiring Process Works
- Application and Resume Screening: The journey begins with an online application where resumes are meticulously screened for relevant experience, educational background, and skill alignment. Recruiters pay attention to proven project work, especially in machine learning, big data frameworks, and analytics tools.
- Initial HR Discussion: This stage serves multiple purposes: verifying eligibility criteria, understanding candidate motivation, and assessing cultural fit. It’s less about technical chops here and more about communication skills and clarity of career goals.
- Technical Assessment: Candidates often face a mix of coding challenges and domain-specific problems. This might be a remote test or a take-home assignment, designed to assess both analytical reasoning and programming skills.
- Technical Interview Rounds: Typically comprising two or more rounds, these sessions dive deeper into data structures, algorithms, machine learning concepts, and sometimes business case discussions. Interaction with potential team members or project leads is common to gauge collaboration style.
- Final HR Round and Offer Discussion: The concluding conversation often revolves around salary expectations, role clarity, and organizational values. Transparency is valued here to set the right candidate expectations.
Understanding why themathcompany structures their hiring like this is crucial. Each step filters not just technical capability but also adaptability and cultural alignment, reflecting the company’s consultative client engagements.
Interview Stages Explained
Resume Shortlisting
This isn’t just about ticking boxes. Recruiters look for candidates who showcase hands-on experience with languages like Python, R, and frameworks such as Spark or TensorFlow. Real-world project examples where analytics drove measurable outcomes stand out. If your resume reads like a laundry list of buzzwords, expect it to be discarded quickly.
HR Screening Call
Usually a 20-30 minute chat, this round is an opportunity to tell your story naturally. Candidates often report being asked about their motivation to join themathcompany, understanding of the company’s offerings, and alignment with team culture traits like curiosity and client orientation. This step is less stressful than it sounds—think of it as rapport building.
Technical Assessment
Depending on the role, this can vary. Data scientists might be tested on statistics, ML algorithms, and coding skills via platforms like HackerRank. Data engineers could face questions around system design and database optimizations. The idea is to simulate real challenges faced on the job, not just theoretical puzzles.
Technical Interviews
These rounds are often conversational but intense. Interviewers dig into problem-solving approaches, ask candidates to explain their reasoning, and sometimes challenge them with live coding or whiteboard exercises. Business acumen comes into play here; understanding client problems and applying analytics thoughtfully is a must.
Final HR Interview
The last conversation often clarifies role expectations, growth paths, and compensation packages. Candidates appreciate when recruiters are transparent about the salary range and company benefits—helping them make informed decisions.
Examples of Questions Candidates Report
- Explain how you would handle imbalanced datasets in a classification problem.
- Walk me through a machine learning project you led end-to-end.
- Write a SQL query to find the second highest salary from an employee table.
- How do you optimize Spark jobs for large datasets?
- Describe a time you had to communicate complex data insights to non-technical stakeholders.
- Implement a function in Python to detect duplicates in a list without using extra space.
- What factors would you consider when designing a recommendation engine?
Notice how the questions blend technical expertise with real-world application and communication skills. themathcompany’s interviewers want to see that candidates can think both like data scientists and consultants.
Eligibility Expectations
At themathcompany, the baseline eligibility varies by role but generally includes a degree in Computer Science, Statistics, Mathematics, or related fields. For data science roles, experience with at least one programming language (Python or R) is almost mandatory. Candidates with exposure to cloud platforms like AWS or Azure have an edge, given the company’s push towards scalable solutions.
Entry-level roles might require internships or academic projects demonstrating analytical skills, while senior roles demand several years of hands-on experience and ownership of analytics pipelines. The company also values certifications in machine learning and data engineering but prioritizes demonstrated competence over paper qualifications.
Common Job Roles and Departments
themathcompany’s organizational structure revolves around several key domains:
- Data Science and Analytics: Roles include Data Scientist, Machine Learning Engineer, and Analytics Consultant. These teams drive model development, data exploration, and client problem-solving.
- Data Engineering: Positions like Big Data Engineer and Cloud Engineer focus on building and maintaining data infrastructure that supports analytics workloads.
- Business Intelligence: BI Analysts who translate data into dashboards and reports, enabling client decision-making.
- Product and Technology: Software Developers and DevOps Engineers develop internally used tools and platforms that support client projects.
- Consulting and Client Services: Specialists who bridge technical solutions with business strategy, ensuring implementations drive real impact.
Understanding these roles helps candidates tailor their preparation and expectations according to the department-specific competencies required.
Compensation and Salary Perspective
| Role | Estimated Salary |
|---|---|
| Data Scientist (Entry-level) | $70,000 - $90,000 per annum |
| Machine Learning Engineer (Mid-level) | $100,000 - $130,000 per annum |
| Senior Data Engineer | $120,000 - $150,000 per annum |
| Business Intelligence Analyst | $60,000 - $85,000 per annum |
| Analytics Consultant | $90,000 - $120,000 per annum |
These figures vary depending on location, experience, and negotiation skills. Compared to industry averages, themathcompany’s salary bands are competitive but not extravagant—they compensate with a robust learning environment and client exposure.
Interview Difficulty Analysis
From what candidates share, the interview journey at themathcompany is challenging but fair. The technical rounds test both depth and breadth—expect to be grilled on fundamentals and practical applications. Unlike pure product tech firms that prioritize coding speed, themathcompany leans towards problem-solving clarity and thought process.
Some candidates mention the unpredictability of case-based questions, which is understandable given the consulting-style engagement model. It can throw off applicants used to straightforward technical interviews. However, the company doesn’t expect perfection; they value adaptability and logical reasoning under pressure.
Preparation Strategy That Works
- Master Core Concepts: Strengthen your understanding of algorithms, data structures, probability, and statistics. Don’t just memorize; internalize.
- Practice Coding Regularly: Use platforms like LeetCode and HackerRank focusing on problems related to arrays, strings, and trees—commonly tested areas.
- Hands-On ML Projects: Build projects that showcase end-to-end machine learning pipelines. Prepare to discuss trade-offs and decisions made during development.
- Brush Up on SQL and Big Data: Since data querying is frequent, be comfortable writing efficient SQL queries and understanding distributed data systems.
- Develop Communication Skills: Practice explaining technical concepts to a non-technical audience; storytelling matters hugely during interviews.
- Simulate Case Studies: Engage with mock consulting problems to get used to business-driven questions and frame your answers accordingly.
Work Environment and Culture Insights
themathcompany fosters a culture steeped in continuous learning and collaboration. The work environment reflects a startup vibe with the stability of an established firm. Candidates often describe the culture as intellectually stimulating but also demanding, where deadlines and client expectations keep the pace brisk.
Employees appreciate the transparent feedback loops and the emphasis placed on peer learning. Diversity and inclusion aren't just buzzwords here—the company actively encourages cross-cultural teams and flexible work models.
Career Growth and Learning Opportunities
Growth at themathcompany is meritocratic and driven by demonstrated impact. Employees regularly take on projects that push them out of comfort zones, gaining exposure to new industries and tools. The company invests in training programs, certifications, and knowledge-sharing sessions to keep skill levels sharp.
For data scientists, there’s a clear path from analyst roles to consulting and leadership tracks. Similarly, engineers can evolve towards architecture and strategic product roles. The opportunity to work alongside domain experts accelerates learning, making the company a great place for career development.
Real Candidate Experience Patterns
Listening to candidates talk about their themathcompany interview journeys reveals some consistent themes. Many emphasize the respectful and conversational tone of interviewers, which helps ease nerves. On the flip side, some mention the challenge of balancing technical questions with case discussions, which can feel like switching hats mid-interview.
Preparation gaps often emerge around business case understanding; candidates with purely technical backgrounds sometimes find this jarring. Another common observation is the thoroughness of feedback—whether in rejection or offer scenarios, candidates frequently note timely responses and detailed explanations.
Comparison With Other Employers
When stacked against other major analytics consulting firms or tech giants, themathcompany strikes a unique balance. Unlike pure product companies where the focus is on software engineering, themathcompany demands a blend of consulting aptitude and technical depth. This makes the interview process broader but also richer.
Compared to firms like Mu Sigma or Fractal Analytics, themathcompany’s recruitment rounds are slightly more technical but less sales-driven. The emphasis on collaborative problem-solving and culture fit also tends to be stronger than at large consulting firms.
| Company | Interview Focus | Candidate Experience |
|---|---|---|
| themathcompany | Technical + Business Case | Balanced, engaging, somewhat challenging |
| Mu Sigma | Business Problem + Analytical Skills | Consulting heavy, less coding |
| Algorithmic Coding + System Design | Highly technical, intense competition | |
| Fractal Analytics | Analytics + Domain Knowledge | Moderate difficulty, domain focused |
Expert Advice for Applicants
If you’re aiming for a job at themathcompany, remember this: they want thinkers, doers, and communicators all rolled into one. Don’t just cram formulas or code snippets. Understand why an approach works, and be ready to articulate your reasoning clearly.
Also, dive into real-world datasets and try explaining your insights as if you were presenting to a client. It might sound obvious, but many candidates overlook this aspect and find themselves floundering during the business case discussions.
Finally, stay calm during interviews. The process isn’t designed to trip you up but to find a good match. If you feel stuck, it’s often better to explain your thought process out loud than to stay silent.
Frequently Asked Questions
What is the typical duration of the themathcompany interview process?
Usually, the entire selection process spans 3 to 5 weeks, including time for assessments and scheduling multiple rounds. However, it can be shorter or longer depending on the role and candidate availability.
Do I need prior consulting experience to get hired?
No, not strictly. While consulting experience helps with case discussions, themathcompany hires many candidates from purely technical backgrounds, provided they demonstrate strong problem-solving and communication skills.
Are there opportunities for remote work?
Yes, themathcompany has embraced hybrid and remote work models, especially post-pandemic. However, some client-facing roles may require occasional travel or on-site presence.
How should I prepare for the business case interview?
Practice framing problems logically, focus on structuring your thoughts, and relate solutions to business impact. Resources like case study books or mock consulting sessions can be very useful.
What technical skills are most valued for data scientist roles?
Strong programming skills in Python or R, statistical knowledge, familiarity with machine learning frameworks, and experience working with large datasets and cloud platforms are key.
Final Perspective
Joining themathcompany is more than just landing a data science job; it’s about stepping into a dynamic environment where analytics meets business strategy. The interview process reflects this multifaceted reality—demanding both analytical rigor and interpersonal finesse.
Candidates who prepare thoughtfully, embracing both the technical and consultative dimensions, tend to navigate the process successfully. If you’re someone who thrives on solving real-world problems with data and enjoys engaging with clients, themathcompany could be an excellent career home.
Remember, preparation is more than practice—it’s about understanding the company’s DNA and proving you can add value beyond algorithms. With this mindset, your themathcompany interview journey will be a meaningful stepping stone in your career.
themathcompany Interview Questions and Answers
Updated 21 Feb 2026Software Engineer Interview Experience
Candidate: Meera Joshi
Experience Level: Mid-level
Applied Via: Campus recruitment
Difficulty: Hard
Final Result: Rejected
Interview Process
4
Questions Asked
- Implement a function to detect cycles in a graph.
- Explain object-oriented programming concepts.
- Describe your experience with cloud platforms.
- Solve a coding problem on arrays.
Advice
Practice coding problems extensively and review system design basics.
Full Experience
Through campus recruitment, I went through a written test, two technical interviews, and an HR round. The technical interviews were tough, focusing on algorithms and system design. Though I didn't get selected, the experience helped me identify areas to improve.
Business Analyst Interview Experience
Candidate: Vikram Singh
Experience Level: Mid-level
Applied Via: LinkedIn
Difficulty:
Final Result:
Interview Process
3
Questions Asked
- How do you gather requirements from stakeholders?
- Explain a situation where you had to manage conflicting priorities.
- What tools do you use for data visualization?
Advice
Be clear about your communication skills and experience with stakeholder management.
Full Experience
I applied through LinkedIn and was invited for a phone interview, a case study presentation, and a final HR round. The case study required me to analyze a business problem and present solutions. The process was professional and well-structured.
Data Analyst Interview Experience
Candidate: Sneha Patel
Experience Level: Entry-level
Applied Via: Company website
Difficulty: Easy
Final Result:
Interview Process
2
Questions Asked
- What are the different types of joins in SQL?
- How do you handle outliers in data?
- Describe a time you worked with large datasets.
Advice
Focus on SQL and basic statistics, and be ready to talk about any internships or projects.
Full Experience
Applied via the company website and had a quick HR screening followed by a technical interview. The technical interview was straightforward, mostly about SQL and data handling. The interviewers were supportive and gave me a chance to explain my internship experience.
Machine Learning Engineer Interview Experience
Candidate: Rohit Kumar
Experience Level: Senior
Applied Via: Referral
Difficulty: Hard
Final Result: Rejected
Interview Process
4
Questions Asked
- Design a recommendation system for an e-commerce platform.
- Explain the bias-variance tradeoff.
- How do you optimize hyperparameters in a deep learning model?
- Write code to implement gradient descent.
Advice
Prepare for coding challenges and system design questions related to machine learning pipelines.
Full Experience
Referred by a current employee, I went through a phone screen, a coding test, a technical deep dive, and a final managerial round. The coding test was challenging, and the technical round required detailed explanations of ML concepts. Despite good feedback, I was not selected.
Data Scientist Interview Experience
Candidate: Anita Sharma
Experience Level: Mid-level
Applied Via: Online job portal
Difficulty:
Final Result:
Interview Process
3
Questions Asked
- Explain the difference between supervised and unsupervised learning.
- How do you handle missing data in a dataset?
- Describe a project where you used machine learning to solve a business problem.
Advice
Brush up on your machine learning fundamentals and be ready to discuss your past projects in detail.
Full Experience
I applied through an online portal and was shortlisted for a phone screening, followed by a technical round and a final HR interview. The technical round focused on practical machine learning questions and problem-solving. The interviewers were friendly and encouraged me to explain my thought process. I received an offer within a week.
Frequently Asked Questions in themathcompany
Have a question about the hiring process, company policies, or work environment? Ask the community or browse existing questions here.
Common Interview Questions in themathcompany
Q: In a sports contest there were m medals awarded on n successive days (n > 1). 1. On the first day 1 medal and 1/7 of the remaining m - 1 medals were awarded. 2. On the second day 2 medals and 1/7 of the now remaining medals was awarded; and so on.On the nth and last day, the remaining n medals were awarded.How many days did the contest last, and how many medals were awarded altogether?
Q: A man has a wolf, a goat, and a cabbage. He must cross a river with the two animals and the cabbage. There is a small rowing-boat, in which he can take only one thing with him at a time. If, however, the wolf and the goat are left alone, the wolf will eat the goat. If the goat and the cabbage are left alone, the goat will eat the cabbage. How can the man get across the river with the two animals and the cabbage?
Q: A rich merchant had collected many gold coins. He did not want anybody to know about them. One day his wife asked, "How many gold coins do we have?" After pausing a moment, he replied, "Well! If I divide the coins into two unequal numbers, then 32 times the difference between the two numbers equals the difference between the squares of the two numbers."The wife looked puzzled. Can you help the merchant's wife by finding out how many gold coins they have?
Q: Suppose a newly-born pair of rabbits, one male, one female, are put in a field. Rabbits are able to mate at the age of one month so that at the end of its second month a female can produce another pair of rabbits. Suppose that our rabbits never die and that the female always produces one new pair (one male, one female) every month from the second month on.
Q: 9 cards are there. You have to arrange them in a 3*3 matrix. Cards are of 4 colors. They are red, yellow, blue and green. Conditions for arrangement: one red card must be in first row or second row. 2 green cards should be in 3rd column. Yellow cards must be in the 3 corners only. Two blue cards must be in the 2nd row. At least one green card in each row.
Q: Consider a pile of Diamonds on a table. A thief enters and steals 1/2 of the total quantity and then again 2 extra from the remaining. After some time a second thief enters and steals 1/2 of the remaining+2. Then 3rd thief enters and steals 1/2 of the remaining+2. Then 4th thief enters and steals 1/2 of the remaining+2. When the 5th one enters he finds 1 diamond on the table. Find out the total no. of diamonds originally on the table before the 1st thief entered.
Q: There are 3 clans in an island - The Arcs who never lie, the Dons who always lie and the Slons who lie alternately with the truth. Once a tourist meets 2 guides who stress that the other is a Slon. They proceed on a tour and see a sports meet. The first guide says that the prizes have been won in the order Don, Arc, Slon. The other says that, the order is Slon, Don, Arc. (the order need not be exact). To which clan did each of the guides and the players belong? ...
Q: 36 people {a1, a2, ..., a36} meet and shake hands in a circular fashion. In other words, there are totally 36 handshakes involving the pairs, {a1, a2}, {a2, a3}, ..., {a35, a36}, {a36, a1}. Then size of the smallest set of people such that the res...
Q: The citizens of planet nigiet are 8 fingered and have thus developed their decimal system in base 8. A certain street in nigiet contains 1000 (in base 8) buildings numbered 1 to 1000. How many 3s are used in numbering these buildings?
Q: A light bulb is hanging in a room. Outside of the room there are three switches, of which only one is connected to the lamp. In the starting situation, all switches are 'off' and the bulb is not lit. If it is allowed to check in the room only once.How would you know which is the switch?
Q: There are 3 sticks placed at right angles to each other and a sphere is placed between the sticks . Now another sphere is placed in the gap between the sticks and Larger sphere . Find the radius of smaller sphere in terms of radius of larger sphere.
Q: ABCDE are sisters. Each of them gives 4 gifts and each receives 4 gifts No two sisters give the same combination ( e.g. if A gives 4 gifts to B then no other sisters can give four to other one.)Â (i) B gives four to A.(ii) C gives 3 to E. How much did A,B,C,E give to D?
Q: Tom has three boxes with fruits in his barn: one box with apples, one box with pears, and one box with both apples and pears. The boxes have labels that describe the contents, but none of these labels is on the right box. How can Tom, by taking only one p
Q: A vessel is full of liquid. From the vessel, 1/3rd of the liquid evaporates on the first day. On the second day 3/4th of the remaining liquid evaporates. What fraction of the volume is present at the end of the second day
Q: There are 7 letters A,B,C,D,E,F,GAll are assigned some numbers from 1,2 to 7.B is in the middle if arranged as per the numbers.A is greater than G same as F is less than C.G comes earlier than E.Which is the fourth letter
Q: In a Park, N persons stand on the circumference of a circle at distinct points. Each possible pair of persons, not standing next to each other, sings a two-minute song ? one pair immediately after the other. If the total time taken for singing is 28 minutes, what is N?
Q: Raj has a jewel chest containing Rings, Pins and Ear-rings. The chest contains 26 pieces. Raj has 2 and 1/2 times as many rings as pins, and the number of pairs of earrings is 4 less than the number of rings. How many earrings does Raj have?...
Q: Given a collection of points P in the plane , a 1-set is a point in P that can be separated from the rest by a line, .i.e the point lies on one side of the line while the others lie on the other side. The number of 1-sets of P is denoted by n1(P)....
Q: Jack and his wife went to a party where four other married couples were present. Every person shook hands with everyone he or she was not acquainted with. When the handshaking was over, Jack asked everyone, including his own wife, how many hands they shook?
Q: There are some chickens in a poultry. They are fed with corn. One sack of corn will come for 9 days. The farmer decides to sell some chickens and wanted to hold 12 chicken with him. He cuts the feed by 10% and sack of corn comes for 30...