Data Science Worksheet

Identify the key data science skills among the following.

• Data Visualization

• Machine learning

• Statistics

• All of Above

Give the name of the Python library which is used in data science for data visualization.

• Matplotlib

• NumPy

• Pandas

• scikit-learn

What is the purpose of the term "feature engineering" in machine learning?

• Extracting valuable information from the target variable

• Creating new features or modifying existing ones to improve model performance

• Selecting the most important features for model training

• Normalizing feature values to have zero mean and unit variance

In statistics, what does the term p-value represent in hypothesis testing?

• The probability of making a Type II error

• The probability of observing the data given that the null hypothesis is true

• The significance level for the test

• The probability of rejecting the null hypothesis

Explain the concept of bagging in ensemble learning.

• Combining prediction from multiple models

• Creating diverse models by training each on a different subset of the data

• Reducing model complexity

• Fitting models sequentially to improve accuracy

What is the primary goal of exploratory data analysis (EDA)?

• Making predictions

• Summarizing data characteristics

• Testing hypotheses

• Model deployment

What is the key principle behind the k-nearest neighbors (KNN) algorithm?

• Minimizing the sum of squared errors

• Maximizing the margin between classes

• Assigning a data point the most common label among its k-nearest neighbors

What is the term "cross-validation" in machine learning?

• A technique for evaluating a model by partitioning data into training and validation folds

• A process of scaling features to a common range

• An algorithm used to construct decision trees

• A method for converting categorical variables to numerical codes

How do you calculate the median of a dataset?

• Sorting the data and selecting the middle value

• Finding the average of the smallest and largest values

• Summing all values and dividing by the number of values

• Identifying the most frequently occurring value

What is the purpose of a histogram in data visualization?

• Displaying hierarchical relationships

• Comparing multiple datasets

• Showing the distribution of a single variable

• Representing geographical data