Data Analysis

Question 1

What is descriptive statistical analysis?

Answer 1

It uses numbers to describe the qualities of a data set.

Question 2

What is inferential statistical analysis?

Answer 2

It draws conclusions about a larger population based on a sample group.

Question 3

What is associational statistical analysis?

Answer 3

It is used to make predictions and find causation.

Question 4

What is predictive analysis?

Answer 4

It uses statistical algorithms and machine learning to predict future events and behavior.

Question 5

What is prescriptive analysis?

Answer 5

It helps organizations use data to guide decision-making.

Question 6

What is exploratory data analysis?

Answer 6

It identifies patterns and trends in a data set.

Question 7

What is causal analysis?

Answer 7

It determines causation or why things happen, used in quality assurance and investigations.

Question 8

What role does metadata play in unstructured data analysis?

Answer 8

It provides information about data for management, storage, and analysis.

Question 9

What is Natural Language Processing (NLP)?

Answer 9

A machine learning method to analyze the meaning of unstructured text data.

Question 10

How are images analyzed in unstructured data?

Answer 10

By understanding unstructured information, e.g., diagnosing medical conditions from x-rays.

Question 11

What is supervised machine learning?

Answer 11

It requires labeled input and output data for training and is used for classification and prediction.

Question 12

What is unsupervised machine learning?

Answer 12

It uses raw, unlabeled data to identify patterns and cluster similar data.

Question 13

What are the main uses of unsupervised machine learning?

Answer 13

Clustering datasets, understanding relationships, and initial data analysis.

Question 14

What are key differences between supervised and unsupervised learning?

Answer 14

Supervised needs labeled data and is used for classification/prediction; unsupervised finds relationships and is less explainable.

Question 15

How is data dredging different from data mining?

Answer 15

Data dredging lacks a hypothesis and produces patterns by chance.

Question 16

Quantitative data, name 4 features

Answer 16

Expressed as a numerical value
Analysed using computational techniques and algorithms
Measured objectively
Answers questions like ‘how much’ and ‘how often’

Question 17

Qualitative data, name 4 features

Answer 17

Represented as a name or symbol
Organised into themes
Measured subjectively
Answers questions such as ‘why or ‘how’

Question 18

Mean

Answer 18

Mathematical average of a range of numbers.

Question 19

Median

Answer 19

The midpoint in a range of numbers when in numerical order

Question 20

Mode

Answer 20

The most commonly occurring number in the data set.

Question 21

Skewness

Answer 21

Skewness indicates how symmetrical a range of numbers is