CompTIA DA0-001 Based on Real Exam Environment

Explanation

The null hypothesis presumes the status quo. Andy is testing whether or not people who receive an electronic coupon spend more on average, so, the null hypothesis states that people who receive the coupon do spend more on average.

Adding more data reduces statistical errors by improving the reliability and accuracy of statistical measures. A larger sample size helps balance variations and minimizes the impact of outliers​.

Explanation

Duplicate Data.

While invalid, redundant, or missing data are all valid concerns, data about people exists in two of the six systems. As such, Jhon needs to account for duplicate data issues.

Data consistency refers to ensuring that all values in a dataset follow a uniform format and structure. In this dataset:

One age value is recorded as "65F," which includes anextra character (F)that makes it inconsistent with other numeric age values.

The date formats are inconsistent (6/1/22 vs. 6/19/2022), but this is unrelated to the age issue.

Option A (Completeness):Incorrect. There are no missing values in the age column.

Option B (Consistency):Correct.The age data should be consistently formatted asnumeric values only, without extra characters like "F."

Option C (Accuracy):Incorrect. There is no evidence that theactual age valuesare incorrect, only that they are formatted inconsistently.

Option D (Manipulation):Incorrect. There is no indication that the data was intentionally altered for deception.