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Share some Data Scientist E20-007 exam questions and answers below.
You have plotted the distribution of savings account sizes for a bank.
Based on the distribution shown in the exhibit, how would you proceed?
A.Data is extremely skewed. Replot the data on a logarithmic scale to get a better understanding of it.
B.Data is extremely skewed but looks bimodal. Replot the data in the range 2,500 – 10,000 to be certain.
C.Accounts of sizes greater than 2,500 are rare and are most likely outliers. Eliminate them from future analysis.
D.Data is extremely skewed. Split the analysis into two cohorts; accounts less than 2,500 and accounts greater than 2,500.
Refer to the exhibit.
Click on the calculator icon in the upper left corner. An analyst is searching a corpus of documents for the topic "solid state disk". In the Exhibit, Table A provides the inverse document frequency for each term across the corpus. Table B provides each term’s frequency in four documents selected from corpus. Which of the four documents is most relevant to the analyst’s search?
A. Document B
B. Document A
C. Document C
D. Document D
A business colleague who is new to Hadoop approaches you with a question. The
colleague wants to know the best approach to access their data. The colleague has previously worked extensively with SQL and databases.
Which query interface should be recommended?
You have been assigned to do a study of the daily revenue effect of a pricing model of online transactions. All the data currently available to you has been loaded into your analytics database; revenue data, pricing data, and online transaction data. You find that all the data comes in different levels of granularity. The transaction data has timestamps (day, hour, minutes, seconds), pricing is stored at the daily level, and revenue data is only reported monthly. What is your next step?
A. Report back to the business owner that the current data model does not support the business question.
B. Interpolate a daily model for revenue from the monthly revenue data.
C. Aggregate all data to the monthly level in order to create a monthly revenue model.
D. Disregard revenue as a driver in the pricing model, and create a daily model based on pricing and transactions only.
You are using MADlib for Linear Regression analysis. Which value does the statement return?
SELECT (linregr(depvar, indepvar)).r2 FROM zeta1;
A. Goodness of fit
C. Standard error
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