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NEW QUESTION 49
A data architect has determined that a table of the following format is necessary:
Which of the following code blocks uses SQL DDL commands to create an empty Delta table in the above
format regardless of whether a table already exists with this name?
- A. 1. CREATE OR REPLACE TABLE table_name
2. WITH COLUMNS ( id STRING, birthDate DATE, avgRating FLOAT ) USING DELTA
- B. 1. CREATE OR REPLACE TABLE table_name AS
2. SELECT id STRING, birthDate DATE, avgRating FLOAT USING DELTA
- C. 1. CREATE TABLE table_name AS
2. SELECT id STRING, birthDate DATE, avgRating FLOAT
- D. 1. CREATE TABLE IF NOT EXISTS table_name ( id STRING, birthDate DATE, avgRating FLOAT )
- E. 1. CREATE OR REPLACE TABLE table_name ( id STRING, birthDate DATE, avgRating FLOAT )
NEW QUESTION 50
Question-26. There are 5000 different color balls, out of which 1200 are pink color. What is the maximum
likelihood estimate for the proportion of “pink” items in the test set of color balls?
- A. .48
- B. 2.4
- C. .24
- D. 4.8
- E. 24 0
Given no additional information, the MLE for the probability of an item in the test set is exactly its frequency
in the training set. The method of maximum likelihood corresponds to many well-known estimation methods
in statistics. For example, one may be interested in the heights of adult female penguins, but be unable to
measure the height of every single penguin in a population due to cost or time constraints. Assuming that the
heights are normally (Gaussian) distributed with some unknown mean and variance, the mean and variance
can be estimated with MLE while only knowing the heights of some sample of the overall population. MLE
would accomplish this by taking the mean and variance as parameters and finding particular parametric values
that make the observed results the most probable (given the model).
In general, for a fixed set of data and underlying statistical model the method of maximum likelihood selects
the set of values of the model parameters that maximizes the likelihood function. Intuitively, this maximizes
the “agreement” of the selected model with the observed data, and for discrete random variables it indeed
maximizes the probability of the observed data under the resulting distribution. Maximum-likelihood
estimation gives a unified approach to estimation, which is well-defined in the case of the normal distribution
and many other problems. However in some complicated problems, difficulties do occur: in such problems,
maximum-likelihood estimators are unsuitable or do not exist.
NEW QUESTION 51
Which of the following data workloads will utilize a Bronze table as its source?
- A. A job that aggregates cleaned data to create standard summary statistics
- B. A job that queries aggregated data to publish key insights into a dashboard
- C. A job that ingests raw data from a streaming source into the Lakehouse
- D. A job that enriches data by parsing its timestamps into a human-readable format
- E. A job that develops a feature set for a machine learning application
NEW QUESTION 52
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