A data scientist is attempting to identify sentences that are conceptually similar to each other within a set of text files. Which of the following is the best way to prepare the data set to accomplish this task after data ingestion?

• A.Embeddings
• B.Extrapolation
• C.Sampling
• D.One-hot encoding

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Which of the following does k represent in the k-means model?

• A.Number of model tests
• B.Number of data splits
• C.Number of clusters
• D.Distance between features

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A data scientist needs to analyze a company's chemical businesses and is using the master database of the conglomerate company. Nothing in the data differentiates the data observations for the different businesses. Which of the following is the most efficient way to identify the chemical businesses' observations?

• A.Ingest the data from all of the hard drives and perform exploratory data analysis to identify which business is responsible for chemical operations.
• B.Perform analysis on all of the data and create a summary report on the results relevant to chemical operations.
• C.Consult with the business team to identify which sites are responsible for chemical operations and ingest only the relevant data for analysis.
• D.Ingest data from the hard drive containing the most data and present sample results on the chemical operations.

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A data scientist is creating a responsive model that will update a product's daily pricing based on the previous day's sales volume. Which of the following resource constraints is the data scientist's greatest concern?

• A.Deployment time
• B.Training time
• C.Development time
• D.Data collection time

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A data scientist needs to determine whether product sales are impacted by other contributing factors. The client has provided the data scientist with sales and other variables in the data set.
The data scientist decides to test potential models that include other information.
INSTRUCTIONS
Part 1
Use the information provided in the table to select the appropriate regression model.
Part 2
Review the summary output and variable table to determine which variable is statistically significant.
If at any time you would like to bring back the initial state of the simulation, please click the Reset All button.

Correct Answer:

See explanation below.
Explanation:
Part 1
Linear regression.
Of the four models, linear regression has the highest R² (0.8), indicating it explains the greatest proportion of variance in sales.

Part 2
Var 4 - Net operations cost.
Net operations cost has a p-value of essentially 0 (far below 0.05), indicating it is the only additional predictor statistically significant in explaining sales. Neither inventory cost (p#0.90) nor initial investment (p#0.23) reach significance.

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