A financial analyst wants to predict the exact closing price of a stock tomorrow. They have historical daily prices, trading volumes, and news sentiment scores. They are considering both regression and forecasting approaches. What is the most important consideration when choosing between these two?

The choice does not matter because both will produce identical results

Forecasting is always better for stock prices because they are time-series data

Regression is always better because it can handle any type of data

Regression is appropriate if the goal is to predict a continuous value from features, while forecasting is appropriate if the goal is to predict a future value in a time series

A retail chain wants to anticipate next month's total sales revenue for each of its 200 stores to plan inventory purchasing. They have five years of daily sales figures, promotional calendars, and local economic indicators. Which modeling approach is most appropriate?

Clustering to group stores by sales patterns

Optimization to maximize store revenue

Classification to label stores as high or low revenue

Forecasting using time-series models on historical sales data

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Domain 1Objective 3

Objective 1.3 Classify a Question into a Known Data Science Problem CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 3)

Part of the 1.0 Defining the need to be addressed through the application of data science domain, which accounts for 7-9% of the CERTIFIED-DATA-SCIENCE-PRACTITIONER exam.

45questions here

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Questions 11–15

11foundation · easy
A real estate company wants to predict the selling price of a house based on its size, location, and number of bedrooms. This is an example of which type of data science problem?
Select an answer first
12foundation · easy
A company wants to recommend products to users based on their past purchases and browsing history. Which modeling type is most appropriate?
Select an answer first
13foundation · easy
Which of the following is an example of text data?
Select an answer first
14expert · hard
A financial analyst wants to predict the exact closing price of a stock tomorrow. They have historical daily prices, trading volumes, and news sentiment scores. They are considering both regression and forecasting approaches. What is the most important consideration when choosing between these two?
Select an answer first
15application · medium
A retail chain wants to anticipate next month's total sales revenue for each of its 200 stores to plan inventory purchasing. They have five years of daily sales figures, promotional calendars, and local economic indicators. Which modeling approach is most appropriate?
Select an answer first

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Objective 1.3 Classify a Question into a Known Data Science Problem CERTIFIED-DATA-SCIENCE-PRACTITIONER Practice Questions (Page 3)

Questions 11–15

A real estate company wants to predict the selling price of a house based on its size, location, and number of bedrooms. This is an example of which type of data science problem?

A company wants to recommend products to users based on their past purchases and browsing history. Which modeling type is most appropriate?

Which of the following is an example of text data?

A financial analyst wants to predict the exact closing price of a stock tomorrow. They have historical daily prices, trading volumes, and news sentiment scores. They are considering both regression and forecasting approaches. What is the most important consideration when choosing between these two?

A retail chain wants to anticipate next month's total sales revenue for each of its 200 stores to plan inventory purchasing. They have five years of daily sales figures, promotional calendars, and local economic indicators. Which modeling approach is most appropriate?

Keep studying — 1.0 Defining the need to be addressed through the application of data science