FA4 + M4 - Sheet1

Question 1

Which of the following activities are associated with Data Exploration?

Data cleaning
Data augmentation and transformation
Exploratory data analysis
Feature selection
Identify data dependencies and correlations
Identify trends or anomalies in the data

Answer 1

Exploratory data analysis
Identify data dependencies and correlations
Identify trends or anomalies in the data

Question 2

Which of the following activities are associated with Data Exploration?

Group of answer choices

Identify data dependencies and correlations

Identify trends or anomalies in the data

Exploratory data analysis

Data cleaning

Feature selection

Data augmentation and transformation

Answer 2

Identify data dependencies and correlations

Identify trends or anomalies in the data

Exploratory data analysis

Question 3

Which of the following activities are associated with Data Modification?

Group of answer choices

Data cleaning

Data augmentation and transformation

Exploratory data analysis

Feature selection

Identify data dependencies and correlations

Identify trends or anomalies in the data

Answer 3

Data cleaning

Data augmentation and transformation

Identify trends or anomalies in the data

hindi dapat identify, feature selection dapat :/

Question 4

Which activity involves adding new data points or modifying existing ones to improve the dataset?

Group of answer choices

Data augmentation

Data cleaning

Exploratory data analysis

Feature selection

Answer 4

Data augmentation

Question 5

Which of the following is NOT typically a part of Data Exploration?

Group of answer choices

Cleaning the data

Identifying data dependencies

Identifying trends in the data

Exploratory data analysis

Answer 5

Cleaning the data

Question 6

Which activity is crucial for understanding the relationships between different variables in a dataset?

Group of answer choices

Identifying data dependencies and correlations

Data cleaning

Data augmentatio

Feature selection

Answer 6

Identifying data dependencies and correlations

Question 7

What does the data say will happen?

Answer 7

Predictive Analytics

Question 8

What has happened or what is happening now?

Answer 8

Descriptive Analytics

Question 9

Why it happened?

Answer 9

Diagnostic Analytics

Question 10

What will likely happen?

Answer 10

Predictive Analytics

Question 11

Predictive Analytics Process:

Answer 11

Project Design
Data Sampling
Data Exploration
Data Modification
Model Validation
Model Development
Project Design

Question 12

Project Design:

Answer 12

Kickoff meeting
Understand modeling objective
Define acceptance criteria
Document data and deployment requirement

Question 13

Data Sampling

Answer 13

Data extraction
Apply filters and exclusions
Identify external data sources

Question 14

Data Exploration

Answer 14

Exploratory data analysis
Identify data dependencies and correlations
Identify trends or anomalies in the data

Question 15

Data Modification

Answer 15

Data Cleaning
Data augmentation and transformation
Feature selection

Question 16

Model Validation

Answer 16

Model performance review
Feedback based on business knowledge and inputs from subject matter experts (SME’s)

Question 17

Model Development

Answer 17

Apply different modeling techniques and select final methodology

Question 18

Dependent Variable (Value to be predicted)

Answer 18

y

Question 19

Beta coefficient (Rate multiplied to X)

Answer 19

6

Question 20

Independent variable (Value driving prediction)

Answer 20

x

Question 21

Alpha intercept (Baseline figure for y)

Answer 21

α

Question 22

Error term (Balancing figure)

Answer 22

ε

Question 23

To account for unexplained variability in the dependent variable for other relevant independent variables, which may not have been included in the model

Answer 23

Inclusion for the Error Term

Question 24

To capture measurement error in both the dependent and independent variables

Answer 24

Inclusion for the Error Term

Question 25

You can have more than one predictor variable (x1 - xn)

Answer 25

Multiple Linear Regression

Question 26

Training vs. Validation vs. Test Data

Answer 26

Splitting the Dataset

Question 27

Can I use the model already for prediction purposes? You still need to investigate the model’s ______ You need to prove if your predictors are ____

Answer 27

goodness-of-fit. significant

Question 28

The ________ , is a goodness-of-fit measure

Answer 28

coefficient of multiple determination, R^2

Question 29

___ is a figure of merit

Answer 29

R^2

Question 30

the ____ the R^2, the better is the success of the model in explaining the variation in the response using the set of predictors

Answer 30

higher

Question 31

___ is normally expressed as a percentage and is interpreted as the amount of variability in the response explained by the independent variables

Answer 31

R^2

Question 32

The _____ is a decomposition of the total variation in the response into explained (pattern) and unexplained (error) parts

Answer 32

ANOVA

Question 33

ANOVA meaning:

Answer 33

Analysis of Variance

Question 34

The ____ variability is the amount of variation in the response variable that may be attributed to the predictors explicitly state in the model

Answer 34

explained

Question 35

The _____ variability is the amount of variation attribute to random error

Answer 35

unexplained

Question 36

SS refers to

Answer 36

Sum of Squares

Question 37

There is good fit if the Regression Sum of Squares is ____ than the Residual Sum of Squares

Answer 37

much larger

Question 38

The df column refers to the ____

Answer 38

degrees of freedom

Question 39

The df for Regression is always the ________

Answer 39

number of regression parameters minus one

Question 40

The df for Residual, it is the sample size minus the _____

Answer 40

number of regression parameter

Question 41

The total df is the _____

Answer 41

sum of those two degrees of freedom

Question 42

MS refers to _____.

Answer 42

Mean Squares

Question 43

The values in this column are the ratio of each sum of square to their respective degrees of freedom.

Answer 43

Mean Squares

Question 44

have no physical meaning but are instrumental in computing the F-statistic

Answer 44

Mean Squares

Question 45

Mean squares have no physical meaning but are instrumental in computing the _____

Answer 45

F-statistic

Question 46

The ____ determines if regression is meaningful for the data at hand

Answer 46

F-test

Question 47

When the ____ is small. it means that there is at least one significant predictor in the analysis

Answer 47

p-value

Question 48

When the p-value is _____. it means that there is at least one significant predictor in the analysis

Answer 48

small

Question 49

When p is ___, Ho must

Answer 49

low, go

Question 50

The p-value is _____ than the a significance level

Answer 50

low if it is less

Question 51

The ___ helps in assessing if an individual predictor is significant

Answer 51

t-test

Question 52

If p <0.05:

Answer 52

significant predictor

Question 53

if p >0.05:

Answer 53

insignificant predictor