Quiz 1 Review

Question 1

What are the main differences between structured, semi-structured, and unstructured data?

Answer 1

Structured data is organized with a clear format (e.g., tables), semi-structured has some structure (e.g., JSON), and unstructured lacks a defined format (e.g., text, images)

Question 2

List common types of data in programming and data analysis

Answer 2

Common data types include string (text), integer (whole numbers), float (decimal numbers), boolean (true/false), and character

Question 3

Outline the steps in the CRISP-DM process and their purpose in data mining and analysis

Answer 3

Stands for Cross-Industry Standard Process for Data Mining. CRISP-DM involves Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment; used for structured approaches in data analysis and mining

Question 4

Define API and describe its primary purpose in software development and data integration

Answer 4

: API (Application Programming Interface) is a set of rules for software to interact with other software; used to access web services and retrieve data.

Question 5

What is a black box model and how is it utilized in machine learning?

Answer 5

A black box model conceals its internal workings; used when the focus is on the model’s output rather than its process or logic.

Question 6

Explain what it means to have imbalanced classes in a dataset

Answer 6

Imbalanced classes occur when one class has significantly fewer instances than others in a dataset.

Question 7

Provide key actions to take and avoid when dealing with missing data, imbalanced classes, and outliers in a dataset

Answer 7

Impute or remove missing data; address imbalanced classes with techniques like oversampling or under sampling; handle outliers by identifying and potentially removing them.

Question 8

Define ETL and describe its significance in data processing and analysis

Answer 8

ETL (Extract, Transform, Load) is a process for data integration: extracting data from sources, transforming it into a usable format, and loading it into a target database.

Question 9

Why do we conduct exploratory data analysis(EDA) in the field of data science?

Answer 9

EDA is used to understand data’s main characteristics, patterns, and relationships; aids in making informed decisions for subsequent analysis.

Question 10

Define metadata and explain its relevance to understanding and managing data

Answer 10

Metadata is data about data, providing information about data attributes, structure, and context; aids in understanding and managing data effectively.

Question 11

Fishbone Diagram

Answer 11

This is a handy diagram to help us think
through the factors that could be inputs to
the business question/problem.

Question 12

Classification

Answer 12

We use this to put new data points in
categories.

Question 13

Type of learning we use to find patterns in
unlabeled data

Answer 13

Unsupervised

Question 14

We implement an ______________ to study
what is in our data.

Answer 14

Algorithm

Question 15

Type of learning we use to predict or
classify using labeled training data

Answer 15

Supervised

Question 16

. The data mining process we’e following is
____

Answer 16

CRISP - DM

Question 17

Type of learning we use to teach robots how
to vacuum floors.

Answer 17

Reinforcement

Question 18

We perform ________ analysis to find
subgroups in the data.

Answer 18

Clustering

Question 19

To figure out what type of products people
buy together, we perform _____ ______
mining.

Answer 19

Association Rule

Question 20

A ______ _______ diagram helps us
formulate the analytic problem.

Answer 20

Black-Box

Question 21

To predict the value of y based on the value
of x, we use __________ analysis.

Answer 21

Regression

Question 22

. It all starts with a _____________.

Answer 22

Question

Question 23

PCA is a type of ________ _________.

Answer 23

Dimension Reduction

Question 24

Data mining involves deriving ___________ from raw data using algorithms.

Answer 24

Insights

Question 25

Clustering ___________ the difference between points within the same cluster.

Answer 25

minimizes

Question 26

Clustering ____________ the distance between points that are in different clusters

Answer 26

maximizes

Question 27

Another term for association rule mining, which describes what it is often used for is _______ ________ analysis

Answer 27

market basket

Question 28

Geospatial data can be raster or ______________.

Answer 28

Vector

Question 29

Examining data for missing values, errors, formatting, statistical distributions etc. is (2 words) ____ _____ analysis.

Answer 29

Exploratory Data

Question 30

Central tendency, dispersion, shape, frequency and percentiles are all examples of (1 word) _____ statistics.

Answer 30

Descriptive

Question 31

What does Stratified k fold do?

Answer 31

ensures that all samples taken for testing have the same class imbalance as the whole dataset.

Question 32

How can your time series model training and testing be ruined if you don’t use forward chaining?

Answer 32

Using backward or reverse chaining in time series model training and testing can ruin the process because it introduces information leakage, results in unrealistic evaluation, violates causality, and provides invalid performance estimates.