DS Foundations Part 1

Question 1

What is the difference between structured and unstructured data?

Answer 1

Structured data fits into tables with rows and columns; unstructured data includes text, images, audio, etc.

Question 2

What are examples of categorical data?

Answer 2

Gender, product category, ZIP code.

Question 3

What is ordinal data?

Answer 3

Categorical data with a meaningful order, but no fixed spacing (e.g., rankings, Likert scales).

Question 4

What is nominal data?

Answer 4

Categorical data without an inherent order (e.g., colors, names).

Question 5

What is the difference between discrete and continuous data?

Answer 5

Discrete data has countable values; continuous data can take any value in a range.

Question 6

What is Exploratory Data Analysis (EDA)?

Answer 6

A process to summarize data characteristics using visualization and statistics.

Question 7

What is the purpose of EDA?

Answer 7

To understand data distributions, spot anomalies, and form hypotheses.

Question 8

What plot is best for showing distribution of a numerical variable?

Answer 8

Histogram or boxplot.

Question 9

What plot is best for identifying relationships between two numerical variables?

Answer 9

Scatter plot.

Question 10

What does a boxplot show?

Answer 10

Median, quartiles, and potential outliers of a dataset.

Question 11

What is the mean?

Answer 11

The average of all data values.

Question 12

What is the median?

Answer 12

The middle value when data is sorted.

Question 13

When is the median better than the mean?

Answer 13

When the data is skewed or contains outliers.

Question 14

What is standard deviation?

Answer 14

A measure of how much values vary around the mean.

Question 15

What is IQR?

Answer 15

The interquartile range: Q3 − Q1, shows middle 50% spread.

Question 16

What is skewness?

Answer 16

A measure of the asymmetry of a distribution.

Question 17

What is kurtosis?

Answer 17

A measure of the ‘tailedness’ of a distribution.

Question 18

What does a right-skewed distribution look like?

Answer 18

It has a long tail on the right; mean > median.

Question 19

What is a uniform distribution?

Answer 19

A distribution where all outcomes have equal probability.

Question 20

What does a bimodal distribution suggest?

Answer 20

There may be two subgroups or populations in the data.

Question 21

What are common data quality issues?

Answer 21

Missing values, duplicates, outliers, inconsistent formats.

Question 22

What is a missing value?

Answer 22

An entry in a dataset that has no recorded value.

Question 23

How can you handle missing data?

Answer 23

Methods include deletion, mean/median imputation, or predictive models.

Question 24

What is data duplication?

Answer 24

When the same observation appears more than once unnecessarily.

Question 25

What is outlier detection?

Answer 25

The process of identifying data points that are significantly different from others.

Question 26

Why is data ethics important?

Answer 26

To protect individual rights, ensure fairness, and prevent misuse of data.

Question 27

What is informed consent in data collection?

Answer 27

When individuals agree to data use with full knowledge of risks and purpose.

Question 28

What is algorithmic bias?

Answer 28

When data or models systematically favor certain groups over others.

Question 29

What is the difference between correlation and causation?

Answer 29

Correlation shows association; causation implies one variable influences another.

Question 30

Why is context important in data interpretation?

Answer 30

Because the same metric can mean different things in different domains.