Data Science Exam Questions with Correct Answers Latest Update 2025/2026
1 - Answers 1
2 - Answers 1
Missing Data - Answers Observations where one or more values are not recorded.
Imputation - Answers Replacing missing values with estimated values such as the mean or
median.
Outliers - Answers Data points that significantly differ from the rest of the dataset.
Normalization - Answers Scaling data to a fixed range, usually [0,1] [0,1].
Standardization - Answers Scaling data to have a mean of 0 and standard deviation of 1.
Categorical Encoding - Answers Converting non-numeric variables into numeric form.
One-Hot Encoding - Answers Representing categories as binary indicator variables.
Feature Engineering - Answers Creating new input variables from existing data.
Data Transformation - Answers Applying mathematical operations to change data distribution.
Train-Test Split - Answers Dividing data into training and testing sets.
Descriptive Statistics - Answers Numerical summaries describing a dataset.
Mean - Answers The arithmetic average of values.
Median - Answers The middle value in an ordered dataset.
Variance - Answers A measure of data spread around the mean.
Standard Deviation - Answers The square root of variance.
Distribution - Answers The overall shape and spread of data values.
Skewness - Answers The degree of asymmetry in a distribution.
Correlation - Answers A measure of the strength and direction of a relationship between
variables.
Visualization - Answers Graphical representation of data.
Multicollinearity - Answers High correlation among independent variables.
Linear Regression - Answers A model that fits a linear relationship between variables.
1 - Answers 1
2 - Answers 1
Missing Data - Answers Observations where one or more values are not recorded.
Imputation - Answers Replacing missing values with estimated values such as the mean or
median.
Outliers - Answers Data points that significantly differ from the rest of the dataset.
Normalization - Answers Scaling data to a fixed range, usually [0,1] [0,1].
Standardization - Answers Scaling data to have a mean of 0 and standard deviation of 1.
Categorical Encoding - Answers Converting non-numeric variables into numeric form.
One-Hot Encoding - Answers Representing categories as binary indicator variables.
Feature Engineering - Answers Creating new input variables from existing data.
Data Transformation - Answers Applying mathematical operations to change data distribution.
Train-Test Split - Answers Dividing data into training and testing sets.
Descriptive Statistics - Answers Numerical summaries describing a dataset.
Mean - Answers The arithmetic average of values.
Median - Answers The middle value in an ordered dataset.
Variance - Answers A measure of data spread around the mean.
Standard Deviation - Answers The square root of variance.
Distribution - Answers The overall shape and spread of data values.
Skewness - Answers The degree of asymmetry in a distribution.
Correlation - Answers A measure of the strength and direction of a relationship between
variables.
Visualization - Answers Graphical representation of data.
Multicollinearity - Answers High correlation among independent variables.
Linear Regression - Answers A model that fits a linear relationship between variables.
