Introduction: When preparing for a data science interview, brushing up on your coding and statistical knowledge is crucial—but math puzzles also play a significant role. Many interviewers use puzzles to assess how candidates approach complex problems, test their logical reasoning, and gauge their problem-solving efficiency. These puzzles are often designed to test not only your knowledge of math but also your ability to think critically and creatively. Here, we've compiled 20 challenging yet exciting math puzzles to help you prepare for data science interviews. We’ll walk you through each puzzle, followed by an explanation of the solution. 1. The Missing Dollar Puzzle Puzzle: Three friends check into a hotel room that costs $30. They each contribute $10. Later, the hotel realizes there was an error and the room actually costs $25. The hotel gives $5 back to the bellboy to return to the friends, but the bellboy, being dishonest, pockets $2 and gives $1 back to each friend. No
To have a solid foundation in probability theory for data science, let's explore key concepts in a structured manner. We’ll start from the basics and gradually move to more advanced ideas. This overview will give you the necessary theoretical background to understand how probability is applied in data science, particularly in machine learning, statistical modeling, and predictive analytics. 1. Random Variables A random variable is a variable that takes on different values based on the outcomes of a random phenomenon. Random variables are of two main types: Discrete Random Variables : These take on a countable number of values. For example, the outcome of a die roll (1 through 6) is a discrete random variable. Continuous Random Variables : These take on an uncountable number of values, typically within some interval. For example, the time it takes for a customer to make a purchase in an online store can be modeled as a continuous random variable. 2. Probability Distribution T