About correlation one
Company Description
Correlation One is a leading data science and analytics company that specializes in providing innovative solutions to enhance data literacy and enable organizations to make data-driven decisions. With a strong focus on education and skill development, Correlation One empowers individuals and teams through its proprietary tools and training programs. The company thrives on a culture of collaboration, inclusivity, and continuous learning, fostering an environment where employees are encouraged to share ideas, innovate, and grow. The work environment is dynamic and supportive, with a strong emphasis on professional development and mentorship, ensuring that team members are equipped with the skills necessary to excel in the ever-evolving field of data analytics.
Data Scientist Interview Questions
Q1: What are the key steps you follow in a data science project?
The key steps include defining the problem, data collection, data cleaning and preprocessing, exploratory data analysis, model selection, training the model, evaluating its performance, and finally deploying the model and monitoring its performance in production.
Q2: How do you handle missing data?
I handle missing data through various techniques such as imputation, where I fill in missing values based on the mean, median, or mode of the data, or by using predictive modeling. I also consider removing rows or columns with significant amounts of missing data if appropriate.
Q3: Can you explain the difference between supervised and unsupervised learning?
Supervised learning involves training a model on labeled data, where the outcome variable is known, allowing the model to learn the relationship between input features and the output. Unsupervised learning, on the other hand, deals with unlabeled data, and the model tries to find hidden patterns or groupings within the data without prior knowledge of the outcomes.
Q4: Describe a time when your analysis led to significant business impact.
In a previous role, I identified customer churn patterns using predictive analytics. By implementing targeted retention strategies based on my findings, the company was able to reduce churn by 15%, which significantly improved revenue.
Q5: What programming languages and tools are you proficient in for data analysis?
I am proficient in Python and R for data analysis, and I often use libraries such as Pandas, NumPy, and Scikit-learn. I also have experience with SQL for database management and visualization tools like Tableau and Matplotlib.
Data Analyst Interview Questions
Q1: What is your process for cleaning and preparing data for analysis?
My process involves identifying and handling missing values, removing duplicates, correcting inconsistencies, and transforming data into a suitable format. I also conduct exploratory data analysis to understand the data better before proceeding with the analysis.
Q2: Can you explain a project where you used data visualization to tell a story?
In a project analyzing sales trends, I created a series of visualizations, including bar charts and line graphs, to illustrate sales performance over time. This helped stakeholders quickly grasp the trends and make informed decisions about inventory management.
Q3: How do you prioritize tasks when working on multiple projects?
I prioritize tasks by assessing the deadlines, the impact of each project, and the resource availability. I use project management tools to keep track of progress and ensure that I meet all deadlines efficiently.
Q4: What tools do you use for data visualization, and why?
I primarily use Tableau for its user-friendly interface and ability to create interactive dashboards. I also use Matplotlib and Seaborn in Python for custom visualizations when needed, as they offer more flexibility in design.
Q5: How do you ensure data accuracy in your reports?
I ensure data accuracy by implementing a thorough review process, where I cross-check data sources, validate calculations, and perform consistency checks. I also seek feedback from colleagues to identify any potential errors.
Machine Learning Engineer Interview Questions
Q1: What machine learning frameworks are you familiar with, and which do you prefer?
I am familiar with TensorFlow, PyTorch, and Scikit-learn. I prefer TensorFlow for deep learning projects due to its scalability and community support, while I find Scikit-learn very convenient for traditional machine learning tasks.
Q2: Explain the concept of overfitting and how to prevent it.
Overfitting occurs when a model learns the noise in the training data rather than the underlying pattern, leading to poor generalization on new data. To prevent it, I use techniques like cross-validation, regularization (e.g., L1 and L2), and pruning for decision trees.
Q3: Describe a machine learning project you have worked on and the outcome.
I developed a recommendation system for an e-commerce platform that used collaborative filtering. The system increased user engagement by 25% within a few months as users received more personalized product recommendations.
Q4: How do you evaluate the performance of a machine learning model?
I evaluate model performance using metrics appropriate for the task, such as accuracy, precision, recall, F1 score for classification tasks, and RMSE or MAE for regression tasks. I also use confusion matrices to gain insights into model predictions.
Q5: What is your approach to feature selection?
My approach to feature selection involves using techniques like correlation analysis, recursive feature elimination, and model-based feature importance to identify the most relevant features that contribute to the model's predictive power while reducing complexity.
Business Analyst Interview Questions
Q1: What methodologies do you use for gathering requirements from stakeholders?
I use techniques such as interviews, surveys, workshops, and document analysis to gather requirements. I also encourage feedback through iterative processes to ensure all stakeholders’ needs are addressed.
Q2: How do you handle conflicting stakeholder opinions on project requirements?
I facilitate discussions to understand the underlying concerns and motivations of each stakeholder. By focusing on the project's goals and using data to support decisions, I work towards a consensus that aligns with overall business objectives.
Q3: Can you give an example of how your analysis influenced a business decision?
In a previous role, my analysis of operational efficiencies revealed areas for cost reduction. By presenting these findings, management decided to streamline processes, which resulted in a 20% reduction in operational costs.
Q4: What tools do you use for data analysis and reporting?
I primarily use Microsoft Excel for data analysis and visualization, along with SQL for database querying. For reporting, I leverage tools like Power BI and Tableau to create interactive dashboards.
Q5: How do you ensure that your findings are communicated effectively to non-technical stakeholders?
I focus on simplifying complex information, using visuals and analogies to make the data relatable. I also tailor my presentations to the audience's knowledge level and encourage questions to foster understanding.
Company Background and Industry Position
Correlation One occupies a unique niche at the intersection of data science education, talent recruitment, and workforce development. Established with a mission to democratize access to data-driven careers, the company has rapidly grown into a leading platform where businesses connect with elite data talent. Its flagship product revolves around coding competitions, data challenges, and training modules designed to identify and nurture high-potential candidates in data analytics, machine learning, and quantitative research.
Unlike traditional recruiting agencies or job boards, Correlation One emphasizes skill-based assessments to ensure candidates possess not just credentials but demonstrable abilities. This approach has positioned it as a trusted partner for firms seeking rigorous, data-savvy professionals without relying exclusively on pedigree or prior experience alone. In the competitive landscape of data-driven hiring, Correlation One’s model stands out by fostering objective, meritocratic talent pipelines.
How the Hiring Process Works
- Application & Eligibility Screening Candidates typically begin by submitting their profiles through Correlation One’s platform or event-specific portals. The initial eligibility check often involves verifying educational background, relevant technical skills, and sometimes prior competition results.
- Online Assessment A core component here is the timed data challenges or coding tests. These aren’t your run-of-the-mill quizzes but are designed to simulate real-world problems, testing candidates’ analytical thinking, programming, and domain knowledge under pressure.
- Recruiter Outreach Top scorers from assessments are contacted by recruitment specialists who explain the next steps, clarify job roles, and sometimes negotiate expectations. This early interaction sets the tone, focusing heavily on candidate experience and transparency.
- Technical Interviews These rounds are often conducted virtually and delve deeper into problem-solving approaches, practical data skills, and sometimes theoretical knowledge. Hiring managers or data scientists lead these sessions and appreciate candidates who articulate their reasoning clearly rather than rattling off memorized answers.
- HR Interview Beyond skills, the HR round explores cultural fit, motivation, and communication style. It’s less about trick questions and more about ensuring alignment with company values and team dynamics.
- Offer & Negotiation Successful candidates receive offers that reflect market standards with room for negotiation based on experience and role complexity.
This layered process ensures a holistic evaluation, balancing raw technical ability with interpersonal and organizational compatibility.
Interview Stages Explained
Initial Online Challenge: Why It Matters
The preliminary assessment is where many stumble, but it serves a crucial purpose: to filter for candidates who can think critically and apply data concepts in practical settings. Unlike a traditional resume filter, these exercises reveal real skills and potential. It’s common for candidates to underestimate the challenge’s difficulty; pacing and problem selection become key strategies.
Technical Rounds: Beyond the Correct Answer
Hiring teams use this stage to evaluate not just correctness but problem-solving process, clarity of communication, and adaptability. Interviewers often throw curveballs intentionally to see how candidates handle ambiguity. This is where storytelling about past projects can shine—walking through how one approached data issues provides context beyond static answers.
The HR Conversation: Culture and Motivation
Many candidates dread HR interviews, fearing generic questions or trickery. With Correlation One, however, it’s more candid. Recruiters genuinely want to understand aspirations, work styles, and whether candidates can thrive in a fast-paced, innovation-driven setting. Expect questions like: “What excites you about data science?” or “Tell me about a time you navigated a team challenge.” They’re looking for authenticity and resilience.
Examples of Questions Candidates Report
- “Given a dataset with missing values, how would you handle them before model training?”
- “Write a function to calculate the moving average of a time series.”
- “Explain the difference between supervised and unsupervised learning with examples.”
- “Describe a project where you improved a process using data analytics.”
- “How do you prioritize competing deadlines when collaborating on multiple projects?”
Eligibility Expectations
Correlation One tends to attract candidates with strong quantitative backgrounds—statistics, computer science, engineering, or economics. Yet, they value demonstrated skills over just formal degrees. Their eligibility criteria usually include a grasp of programming languages like Python or R, familiarity with machine learning concepts, and a problem-solving mindset. Interestingly, the company encourages participation from non-traditional candidates who can prove competence through challenges or prior contributions.
So while a top-tier university degree might help, it isn’t a strict gatekeeper. This opens doors for self-taught professionals or bootcamp graduates who have polished their skills via hands-on projects or competitions.
Common Job Roles and Departments
Correlation One doesn’t just serve as a hiring platform but also directly employs talent, especially in roles related to product development and client engagement. Typical job categories linked to their recruitment include:
- Data Scientist – Developing and validating models, optimizing data pipelines.
- Machine Learning Engineer – Implementing scalable algorithms for real-time applications.
- Data Engineer – Building and maintaining infrastructure to support large-scale data processing.
- Product Manager (Data-focused) – Bridging technical teams and business goals to deliver data products.
- Recruitment Analyst – Using data insights to refine talent sourcing strategies.
In addition, many companies leveraging Correlation One’s platform recruit for analyst and quantitative research roles, reflecting the platform’s emphasis on high-impact analytical skill sets.
Compensation and Salary Perspective
| Role | Estimated Salary (USD) |
|---|---|
| Data Scientist (Entry-Level) | $85,000 – $110,000 |
| Machine Learning Engineer (Mid-Level) | $120,000 – $150,000 |
| Data Engineer | $110,000 – $140,000 |
| Product Manager (Data) | $100,000 – $130,000 |
| Recruitment Analyst (Data Talent) | $70,000 – $90,000 |
These ranges reflect industry averages for tech hubs in the US, though Correlation One’s partnerships can sometimes yield premium compensation, especially for candidates who ace their rigorous assessments.
Interview Difficulty Analysis
Correlation One’s interview rounds stand out for their combination of technical rigor and real-world applicability. Candidates often remark that while the challenges are tough, they’re fair—testing practical problem-solving rather than obscure trivia. The progressive format also allows candidates to acclimate before facing the more intense technical and HR rounds.
Compared to typical data science interviews at FAANG or top fintech firms, Correlation One’s process may feel more skills-focused and less dependent on whiteboard algorithms. But the time constraints and multifaceted problem sets introduce pressure that weeds out those unprepared in simulated conditions. This creates a recruiting funnel that balances accessibility with elite standards.
Preparation Strategy That Works
- Master Core Data Skills – Brush up on Python, SQL, statistics, and basics of machine learning. Don’t just memorize; focus on understanding concepts deeply.
- Practice Realistic Data Challenges – Use platforms like Kaggle or Correlation One’s own practice modules to get comfortable with timed, applied problems.
- Simulate Interview Scenarios – Record yourself explaining solutions out loud to build clarity and confidence. This helps especially for technical interviews where communication is key.
- Review Past Projects Thoroughly – Be ready to narrate your role, challenges faced, and outcomes. Storytelling sells your hands-on experience better than generic statements.
- Prepare for Behavioral Questions – Think through examples demonstrating teamwork, conflict resolution, and learning from failures. Authenticity beats rehearsed answers.
- Understand Correlation One’s Mission – Align your motivation with their emphasis on democratizing data science. Recruiters appreciate candidates who resonate with the company’s values.
Work Environment and Culture Insights
From conversations with former candidates and employees, Correlation One fosters a culture of continuous learning and inclusivity. The company thrives on intellectual curiosity, encouraging experimentation and hackathon-style innovation sessions. It’s not unusual for teams to collaborate across functions—product, engineering, and analytics—blurring traditional silos.
On the flip side, the pace can be brisk, and expectations high, which suits professionals passionate about data but who can also comfortably navigate ambiguity and iterative feedback. The overall vibe is young, mission-driven, and tech-savvy, appealing strongly to those eager to make an impact in the data ecosystem.
Career Growth and Learning Opportunities
One of Correlation One’s selling points is the professional development it offers. Beyond standard roles, candidates can engage in community challenges, mentorship programs, and workshops that sharpen and expand their data skills. The company also promotes internal mobility, allowing employees to explore various facets of data science, product management, or even client-facing roles.
This emphasis on growth is a direct extension of their recruitment philosophy—spotting potential and nurturing it rather than hiring for static competencies. Candidates who join often remark on how their learning curve steepens noticeably within months, thanks to exposure to complex problems and collaborative teams.
Real Candidate Experience Patterns
Many applicants mention an initial nervousness about the online challenges, given their unfamiliarity and time constraints. However, those who persist find the process rewarding because it tests applied skills rather than rote knowledge. A recurring observation is the responsiveness and clarity of communication from Correlation One recruiters, who tend to provide timely feedback and set clear expectations.
During technical interviews, candidates report a conversational atmosphere rather than a grilling session. Interviewers are described as genuinely interested in problem-solving approaches, often providing hints or nudges rather than outright corrections. The HR discussions are usually relaxed, focusing on cultural fit and future aspirations rather than stress-inducing pressure.
That said, some candidates do find the layered rounds taxing, especially those balancing multiple job applications. The key takeaway is that preparation tailored to the company’s challenge-based approach pays off significantly, and resilience through the process is essential.
Comparison With Other Employers
When stacked against giants like Google or IBM, Correlation One’s recruitment process distinguishes itself by focusing less on theoretical computer science and more on applied data science and analytics skills. It’s not about memorizing algorithms but demonstrating an ability to handle messy data and derive insights under constraints.
Compared to boutique recruiting firms or coding bootcamps, Correlation One offers a more structured and transparent process with clear feedback loops. Its platform’s competitive environment also provides candidates with ongoing opportunities to polish skills, which many larger employers lack.
In short, it sits somewhere between elite tech firms and training academies, offering a meritocratic, skills-first pathway that values diversity of background while maintaining high standards.
Expert Advice for Applicants
Don’t just prepare for the questions—prepare for the mindset. Correlation One looks for curiosity, resilience, and clear communication as much as raw technical ability. Spend time working through real datasets and explaining your thought process out loud.
Another tip: treat the online challenges as both a filter and a learning opportunity. Even if you don’t succeed the first time, the feedback and experience can accelerate your growth for future attempts.
Lastly, be authentic during HR rounds. The culture fit isn’t about ticking boxes but about genuine alignment with the company’s mission to widen access to data careers. Show your passion and your willingness to grow.
Frequently Asked Questions
What kinds of interview questions should I expect at Correlation One?
Expect questions centered on practical data problems—handling missing data, writing functions in Python or R, explaining machine learning models, and solving analytical puzzles under timed conditions. Behavioral questions will focus on teamwork, problem-solving approaches, and motivation for working in data science.
How competitive is the Correlation One hiring process?
The process is moderately competitive, with multiple selection rounds designed to filter for true skill and cultural fit. The online challenges particularly narrow the field since they require applied knowledge and quick thinking.
Can I apply if I don’t have a formal degree in a quantitative field?
Yes. While strong foundational knowledge is essential, Correlation One values demonstrated skills and problem-solving ability. Self-taught candidates and those with non-traditional backgrounds have successfully navigated the recruitment rounds by proving their competence in challenges and interviews.
How should I prepare for the technical interviews?
Focus on honing your coding ability, statistical understanding, and familiarity with data science tools. Practice explaining your reasoning clearly and work through timed datasets on platforms like Kaggle or Correlation One’s own practice challenges.
What is the typical timeline from application to offer?
The entire process can span anywhere from two to six weeks, depending on the role and volume of applicants. Candidates often receive prompt updates after each stage, but some patience is required as technical and HR interviews are scheduled.
Final Perspective
Correlation One’s hiring experience offers a meaningful alternative to conventional tech recruitment by centering on meritocratic, skill-based evaluation. For candidates, that means preparation is less about guessing obscure questions and more about genuine capability and communication. The process is challenging but fair, transparent, and designed to identify those who don’t just know data science but can apply it under pressure.
For anyone passionate about data, willing to invest time mastering practical skills and articulating their journey, Correlation One represents an opportunity to break into an innovative ecosystem with strong career prospects. It’s not just a job gatekeeper but a platform for continuous learning, growth, and community engagement. If you prepare thoughtfully and embrace the process’s nuances, you stand a very good chance of turning your data passion into a rewarding career.
correlation one Interview Questions and Answers
Updated 21 Feb 2026Data Analyst Interview Experience
Candidate: Emma T.
Experience Level: Mid-level
Applied Via: Indeed
Difficulty:
Final Result: Rejected
Interview Process
3
Questions Asked
- Write SQL queries to extract and aggregate data.
- Explain how you would clean a messy dataset.
- Describe a dashboard you created and its impact.
- How do you communicate data insights to non-technical stakeholders?
- What tools do you use for data visualization?
Advice
Practice SQL and storytelling with data, and prepare examples of your analysis work.
Full Experience
The initial phone screen was about my background and motivation. The second round was a technical test with SQL and data cleaning tasks. The final round was a behavioral interview. Although I wasn't selected, the interviewers provided helpful feedback.
Software Engineer Interview Experience
Candidate: David S.
Experience Level: Entry-level
Applied Via: Job Fair
Difficulty: Easy
Final Result:
Interview Process
2
Questions Asked
- Implement a function to reverse a linked list.
- Explain object-oriented programming concepts.
- Describe your experience with Python or Java.
- What is your approach to debugging code?
- Have you worked with APIs before?
Advice
Focus on coding fundamentals and be ready to explain your projects.
Full Experience
I met a recruiter at a job fair and submitted my resume. The first round was a phone interview with coding questions. The second was a video interview with some behavioral questions. The process was straightforward and supportive.
Product Manager Interview Experience
Candidate: Cynthia L.
Experience Level: Mid-level
Applied Via: Referral
Difficulty:
Final Result:
Interview Process
3
Questions Asked
- How do you prioritize features in a data product?
- Describe a time you managed cross-functional teams.
- Explain a data-driven decision you made.
- How do you handle conflicting stakeholder requirements?
- What metrics would you track for a data analytics platform?
Advice
Demonstrate strong communication skills and understanding of data products.
Full Experience
I was referred by a current employee and had a recruiter phone screen first. Then I had two rounds of interviews focusing on product sense and behavioral questions. The interviewers valued clear communication and data-driven thinking.
Machine Learning Engineer Interview Experience
Candidate: Brian K.
Experience Level: Senior
Applied Via: Company Website
Difficulty: Hard
Final Result: Rejected
Interview Process
4
Questions Asked
- Design a recommendation system for an e-commerce platform.
- Explain gradient descent and its variants.
- Implement a neural network from scratch.
- Discuss challenges in deploying ML models to production.
- How do you monitor model performance over time?
Advice
Prepare for system design and coding challenges, and be ready to discuss production ML pipelines.
Full Experience
The process started with an online coding test, followed by a technical phone interview. Then there was an onsite with multiple rounds including system design and behavioral interviews. The questions were challenging and very focused on practical ML engineering experience.
Data Scientist Interview Experience
Candidate: Alice M.
Experience Level: Mid-level
Applied Via: LinkedIn
Difficulty:
Final Result:
Interview Process
3
Questions Asked
- Explain a time you used machine learning to solve a business problem.
- Describe the difference between supervised and unsupervised learning.
- Write SQL queries to manipulate and extract data from a database.
- How do you handle missing data in a dataset?
- Explain the bias-variance tradeoff.
Advice
Brush up on SQL and machine learning fundamentals, and be ready to discuss past projects in detail.
Full Experience
I applied through LinkedIn and was invited to a phone screen focusing on my background and technical skills. The second round was a technical interview with coding and data science questions. The final round was a case study presentation where I analyzed a dataset and presented insights. The interviewers were friendly and the process was well-structured.
Frequently Asked Questions in correlation one
Have a question about the hiring process, company policies, or work environment? Ask the community or browse existing questions here.
Common Interview Questions in correlation one
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: There are two balls touching each other circumferencically. The radius of the big ball is 4 times the diameter of the small all. The outer small ball rotates in anticlockwise direction circumferencically over the bigger one at the rate of 16 rev/sec. The bigger wheel also rotates anticlockwise at N rev/sec. What is 'N' for the horizontal line from the centre of small wheel always is horizontal.
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: T, U, V are 3 friends digging groups in fields. If T & U can complete i groove in 4 days &, U & V can complete 1 groove in 3 days & V & T can complete in 2 days. Find how many days each takes to complete 1 groove individually.
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: At 6?o a clock ticks 6 times.The time between first and last ticks is 30 seconds.How long does it tick at 12?o clock?2.A hotel has 10 storey. Which floor is above the floor below the floor, below the floor above the floor, below the floor above the fifth.
Q: The egg vendor calls on his first customer and sells half his eggs and half an egg. To the second customer, he sells half of what he had left and half an egg and to the third customer he sells half of what he had then left and half an egg. By the way he did not break any eggs. In the end three eggs were remaining . How many total eggs he was having ?
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: Jarius and Kylar are playing the game. If Jarius wins, then he wins twice as many games as Kylar. If Jarius loses, then Kylar wins as the same number of games that Jarius wins. How many do Jarius and Kylar play before this match?
Q: There are four dogs/ants/people at four corners of a square of unit distance. At the same instant all of them start running with unit speed towards the person on their clockwise direction and will always run towards that target. How long does it take for them to meet and where?
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: An escalator is descending at constant speed. A walks down and takes 50 steps to reach the bottom. B runs down and takes 90 steps in the same time as A takes 10 steps. How many steps are visible when the escalator is not operating.Â
Q: A Man is sitting in the last coach of train could not find a seat, so he starts walking to the front coach ,he walks for 5 min and reaches front coach. Not finding a seat he walks back to last coach and when he reaches there,train had completed 5 miles. what is the speed of the train ?
Q: A person meets a train at a railway station coming daily at a particular time. One day he is late by 25 minutes, and he meets the train 5 k.m. before the station. If his speed is 12 kmph, what is the speed of the train.
Q: Joe started from Bombay towards Pune and her friend julie in opposite direction. they met at a point . distance traveled by joe was 1.8 miles more than that of julie.after spending some both started there way. joe reaches in 2 hours while julie in 3.5 hours.Assuming both were traveling with constant speed. What is the distance between the two cities.
Q: In mathematics country 1,2,3,4....,8,9 are nine cities. Cities which form a no. that is divisible by 3 are connected by air planes. (e.g. cities 1 & 2 form no. 12 which divisible by 3 then 1 is connected to city 2). Find the total no. of ways you can go to 8 if you are allowed to break the journeys.
Q: Six persons A,B,C,D,E & F went to solider cinema. There are six consecutive seats. A sits in one of the seats followed by B, followed by C and soon. If a taken one of the six seats , then B should sit adjacent to A. C should sit adjacent A or B. D should sit adjacent to A, B,or C and soon. How many possibilities are there?
Q: A is driving on a highway when the police fines him for over speeding and exceeding the limit by 10 km/hr. At the same time B is fined for over speeding by twice the amount by which A exceeded the limit. If he was driving at 35 km/hr what is the speed limit for the road?
