ExamGecko
Search Search Login
Home Home / Snowflake / DSA-C02
Question list
Search
Search
Open VPLUS File
Convert VPLUS to PDF

Related questions

Consider a data frame df with 10 rows and index [ 'r1', 'r2', 'r3', 'row4', 'row5', 'row6', 'r7', 'r8', 'r9', 'row10']. What does the aggregate method shown in below code do? g = df.groupby(df.index.str.len()) g.aggregate({'A':len, 'B':np.sum})
Which one is not the feature engineering techniques used in ML data science world?
You are training a binary classification model to support admission approval decisions for a college degree program. How can you evaluate if the model is fair, and doesn't discriminate based on ethnicity?
Which metric is not used for evaluating classification models?
Which type of Python UDFs let you define Python functions that receive batches of input rows as Pandas DataFrames and return batches of results as Pandas arrays or Series?
Which of the following is a Python-based web application framework for visualizing data and analyzing results in a more efficient and flexible way?
To return the contents of a DataFrame as a Pandas DataFrame, Which of the following method can be used in SnowPark API?
Which Python method can be used to Remove duplicates by Data scientist?
Which of the learning methodology applies conditional probability of all the variables with respec-tive the dependent variable?
Mark the incorrect statement regarding usage of Snowflake Stream & Tasks?

Question 3 - DSA-C02 discussion

Report
Export

In a simple linear regression model (One independent variable), If we change the input variable by 1 unit. How much output variable will change?

A.
by 1
Answers
A.
by 1
B.
no change
Answers
B.
no change
C.
by intercept
Answers
C.
by intercept
D.
by its slope
Answers
D.
by its slope
Suggested answer: D

Explanation:

What is linear regression?

Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable's value is called the independent variable.

Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed data. One variable is considered to be an explanatory variable, and the other is considered to be a dependent variable. For example, a modeler might want to relate the weights of individuals to their heights using a linear regression model.

A linear regression line has an equation of the form Y = a + bX, where X is the explanatory variable and Y is the dependent variable. The slope of the line is b, and a is the intercept (the value of y when x = 0).

For linear regression Y=a+bx+error.

If neglect error then Y=a+bx. If x increases by 1, then Y = a+b(x+1) which implies Y=a+bx+b. So Y increases by its slope.

For linear regression Y=a+bx+error. If neglect error then Y=a+bx. If x increases by 1, then Y = a+b(x+1) which implies Y=a+bx+b. So Y increases by its slope.

Show Answer
asked 23/09/2024
Trevor O'Brien
37 questions
PreviousPreviousNextNext
User
Your answer:
0 comments
Sorted by

Leave a comment first

ExamGecko

Copyright @2023 ExamGecko | All right reserved

Mail us: [email protected]
About us
Contact us
Twitter X
Facebook
Medium
Convert VPLUS to PDF
Open VPLUS files Easily and Quickly
Privacy Policy
Disclaimer
Terms