FREE MS-DS Master of Data science Statistical Methods for Data Science Questions and Answers

Question 1

Which of the following statistical methods is most appropriate for analyzing the relationship between a categorical independent variable (e.g., treatment group) and a continuous dependent variable (e.g., blood pressure reduction) when there are three or more independent groups?

Accepted Answer

ANOVA (Analysis of Variance)

Answer

Chi-squared test

Answer

Linear Regression

Answer

Logistic Regression

Question 2

A data scientist is working with a dataset of customer purchases and wants to predict whether a customer will churn (yes/no) based on their browsing history and demographic information. Which statistical modeling technique would be most suitable for this binary classification problem?

Accepted Answer

Logistic Regression

Answer

K-Means Clustering

Answer

Principal Component Analysis (PCA)

Answer

Support Vector Regression (SVR)

Question 3

When performing hypothesis testing, what does a p-value of 0.01 imply if the significance level (alpha) is set to 0.05?

Accepted Answer

We reject the null hypothesis, indicating statistically significant evidence against it.

Answer

There is a 1% chance the null hypothesis is true.

Answer

We fail to reject the null hypothesis.

Answer

The observed effect is practically insignificant.

Question 4

Which of the following scenarios would most appropriately utilize a time series analysis?

Accepted Answer

Forecasting monthly sales for the next year based on past sales data.

Answer

Predicting customer churn based on historical transaction data.

Answer

Clustering customers into segments based on demographic features.

Answer

Determining the relationship between advertising spend and product sales in a single month.

Question 5

In the context of linear regression, what does the R-squared value represent?

Accepted Answer

The proportion of the variance in the dependent variable that is predictable from the independent variable(s).

Answer

The p-value of the model's coefficients.

Answer

The average absolute error of the predictions.

Answer

The strength and direction of the linear relationship between variables.

Question 6

A data scientist wants to reduce the dimensionality of a high-dimensional dataset while retaining as much variance as possible. Which unsupervised learning technique is best suited for this task?

Accepted Answer

Principal Component Analysis (PCA)

Answer

K-Nearest Neighbors (KNN)

Answer

Support Vector Machines (SVM)

Answer

Gradient Boosting