# Tokopedia Data Science Interview Questions and Answers

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Preparing for a data science interview at Tokopedia? We’ve got you covered! Data science is a dynamic and multi-faceted field, and interviews can range from technical skills to problem-solving abilities. Here’s a comprehensive guide with common questions and insightful answers to help you shine in your interview.

### Statistics Interview Questions

#### Question: What is the difference between Type I and Type II errors?

• Type I Error: This occurs when we reject a true null hypothesis (false positive). The probability of committing a Type I error is denoted by alpha (α), which is the significance level.
• Type II Error: This occurs when we fail to reject a false null hypothesis (false negative). The probability of committing a Type II error is denoted by beta (β).

#### Question: How do you interpret a p-value?

Answer: A p-value measures the strength of the evidence against the null hypothesis. A low p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, suggesting that we reject the null hypothesis. A high p-value (> 0.05) indicates weak evidence against the null hypothesis, so we fail to reject the null hypothesis.

#### Question: What is the difference between correlation and causation?

• Correlation: This measures the strength and direction of a linear relationship between two variables. It does not imply causation.
• Causation: This implies that changes in one variable directly cause changes in another variable. Establishing causation requires more rigorous testing and experimental design.

#### Question: Explain the concept of confidence intervals.

Answer: A confidence interval is a range of values derived from a sample statistic that is likely to contain the population parameter. The interval has an associated confidence level that quantifies the level of confidence that the parameter lies within the interval. For example, a 95% confidence interval means we are 95% confident that the interval contains the true population parameter.

#### Question: What is multicollinearity, and how can it be detected?

Answer: Multicollinearity occurs when independent variables in a regression model are highly correlated. This can lead to unreliable estimates of coefficients and can affect the model’s interpretability. It can be detected using:

• Variance Inflation Factor (VIF): A VIF value greater than 10 indicates high multicollinearity.
• Correlation Matrix: Checking the correlation between independent variables.

#### Question: What is the difference between a t-test and a z-test?

• T-test: Used when the sample size is small (n < 30) and the population variance is unknown. It compares the means of two groups.
• Z-test: Used when the sample size is large (n ≥ 30) and the population variance is known. It also compares the means of the two groups.

### Basic Algebra Interview Questions

#### Question: What is the difference between an expression and an equation?

Answer: An expression is a combination of variables, constants, and operators without an equality sign (e.g., 3x+23x + 23x+2). An equation is a statement that two expressions are equal, connected by an equality sign (e.g., 3x+2=113x + 2 = 113x+2=11).

#### Question: How do you solve a linear equation?

Answer: To solve a linear equation, simplify both sides, move variable terms to one side and constants to the other, and then isolate the variable using inverse operations. For example, for 2x+3=112x + 3 = 112x+3=11, subtract 3 and divide by 2 to get x=4x = 4x=4.

#### Question: What is the quadratic formula, and when is it used?

Answer: The quadratic formula, x=−b±b2−4ac2ax = \frac{-b \pm \sqrt{b^2 – 4ac}}{2a}x=2a−b±b2−4ac​​, is used to solve quadratic equations of the form ax2+bx+c=0ax^2 + bx + c = 0ax2+bx+c=0. It finds the values of xxx that satisfy the equation.

#### Question: How do you factor a quadratic equation?

Answer: To factor a quadratic equation ax2+bx+cax^2 + bx + cax2+bx+c, find two numbers that multiply to acacac and add to bbb. Rewrite the middle term using these numbers, factor by grouping, and simplify.

#### Question: What is a linear function?

Answer: A linear function is a function that creates a straight line when graphed. It has the form f(x)=mx+bf(x) = mx + bf(x)=mx+b, where mmm is the slope and bbb is the y-intercept.

#### Question: How do you find the slope of a line?

Answer: The slope of a line is found using the formula m=y2−y1x2−x1m = \frac{y_2 – y_1}{x_2 – x_1}m=x2​−x1​y2​−y1​​, which calculates the change in yyy over the change in xxx between two points (x1,y1)(x_1, y_1)(x1​,y1​) and (x2,y2)(x_2, y_2)(x2​,y2​).

#### Question: What is the difference between a function and a relation?

Answer: A relation is a set of ordered pairs, while a function is a specific type of relation where each input (x-value) is paired with exactly one output (y-value).

### SQL Interview Questions

#### Question: What is the difference between INNER JOIN and LEFT JOIN?

Answer: INNER JOIN returns only the rows that have matching values in both tables. LEFT JOIN returns all the rows from the left table and the matched rows from the right table, and if no match is found, NULLs are returned for columns from the right table.

#### Question: What is the purpose of the GROUP BY clause?

Answer: The GROUP BY clause groups rows that have the same values in specified columns into aggregate data. It is often used with aggregate functions like COUNT, SUM, AVG, MAX, and MIN.

#### Question: What is a foreign key?

Answer: A foreign key is a column or a set of columns in one table that refers to the primary key in another table. It establishes a relationship between the two tables and enforces referential integrity.

#### Question: Explain the difference between UNION and UNION ALL.

Answer: UNION combines the result sets of two queries and removes duplicate rows. UNION ALL combines the result sets of two queries and includes all duplicates.

#### Question: What is indexing in SQL, and why is it used?

Answer: Indexing is a database optimization technique that improves the speed of data retrieval operations on a table at the cost of additional storage and maintenance overhead. Indexes are created on columns to allow faster searches, queries, and access patterns.

### Python Interview Questions

#### Question: Explain the difference between lists and tuples in Python.

Answer: Lists are mutable, meaning their elements can be changed after creation, and are defined using square brackets []. Tuples are immutable, meaning their elements cannot be changed, and are defined using parentheses ().

#### Question: What are Python decorators, and how are they used?

Answer: Decorators are a way to modify or extend the behavior of functions or methods. They are defined using the @decorator_name syntax above the function to be decorated. They allow for reusable code and can add functionality before or after the function call.

#### Question: How does Python handle memory management?

Answer: Python uses automatic memory management, primarily through reference counting and garbage collection. Objects are deallocated when their reference count drops to zero, and cyclic references are cleaned up by the garbage collector.

#### Question: What is the difference between __init__ and __new__ in Python?

Answer: __new__ is a static method that creates a new instance of a class, while __init__ initializes the newly created instance. __new__ is called before __init__ and is used for immutable objects or custom object creation.

#### Question: Explain the concept of list comprehensions and provide an example.

Answer: List comprehensions provide a concise way to create lists. The syntax includes an expression followed by a for clause and can have additional for or if clauses. Example: [x**2 for x in range(10) if x % 2 == 0] generates a list of squares of even numbers from 0 to 9.

### ML Algorithm Interview Questions

#### Question: What is the difference between a decision tree and a random forest?

Answer: A decision tree is a single tree structure used for classification or regression. A random forest is an ensemble method that builds multiple decision trees and merges them to improve accuracy and prevent overfitting. It uses techniques like bagging and feature randomness.

#### Question: How does gradient descent work?

Answer: Gradient descent is an optimization algorithm used to minimize the cost function. It iteratively adjusts model parameters in the opposite direction of the gradient of the cost function concerning the parameters, with the step size determined by the learning rate.

#### Question: What is cross-validation, and why is it used?

Answer: Cross-validation is a technique used to evaluate a model’s performance and ensure it generalizes well to new data. It involves splitting the dataset into multiple folds, training the model on some folds, and testing it on the remaining fold, then averaging the results to reduce bias and variance.

#### Question: Explain the concept of overfitting and how to prevent it.

Answer: Overfitting occurs when a model learns noise and details in the training data to the extent that it performs poorly on new data. It can be prevented by using techniques like cross-validation, pruning, regularization (L1 and L2), and using simpler models or more data.

#### Question: What is the difference between logistic regression and linear regression?

Answer: Linear regression predicts continuous values using a linear relationship between input features and the target variable. Logistic regression predicts binary outcomes (0 or 1) using a logistic function to model the probability of the target variable.

### Conclusion

Preparing for a data science interview at Tokopedia involves understanding fundamental concepts, methodologies, and algorithms in data science. Review these common questions and answers, and you’ll be better equipped to demonstrate your knowledge and skills during your interview. Good luck!