CompTIA DA0-001 Exam With Confidence Using Practice Dumps

Explanation

Alfonso had the highest score. A left skewed distribution is a distribution where the tail is longer on the left side than on the right side, meaning that most of the values are clustered on the right side and there are some outliers on the left side. In a left skewed distribution, the mean is less than the median, which is less than the mode. Therefore, Joseph, who scored at the mean, had the lowest score, Gaby, who scored at the end of the tail, had the second lowest score, and Alfonso, who scored at the median, had the highest score. Reference: Skewness - Statistics How To

The SQL query provided is selecting all records from the Cust_table where the age column has values greater than 60 and the City column matches “New York”. The > operator selects values that are strictly greater than the comparison value, so it does not include customers aged exactly 60. The term “New York” in the context of a city database typically refers to New York City, not the state of New York. Therefore, the correct answer is that the analyst is retrieving data for all customers older than age 60 in New York City.

References:

The use of the > operator in SQL is to select values greater than the specified value1.

Understanding the WHERE clause in SQL and its use in filtering records based on specified conditions2.

Clarification on the distinction between city and state names in database records3.

The correct join the analyst should complete is B. LEFT JOIN, four rows.

A LEFT JOIN is a type of SQL join that returns all the rows from the left table, and the matched rows from the right table. If there is no match, the right table will have null values. A LEFT JOIN is useful when we want to preserve the data from the left table, even if there is no corresponding data in the right table1

Using the example tables, a LEFT JOIN query would look like this:

SELECT t1.Name, t1.City, t2.Age FROM Table1 t1 LEFT JOIN Table2 t2 ON t1.Name = t2.Name;

The result of this query would be:

Name City Age Jane Smith Detroit NULL John Smith Dallas 34 Candace Johnson Atlanta 45 Kyle Jacobs Chicago 39

As you can see, the query returns four rows, one for each name in Table1. The name John Smith appears twice in Table2, but only one of them is matched with the name in Table1. The name Jane Smith does not appear in Table2, so the age column has a null value for that row.