Question 5Data analysts focus on sample size to make sure they have enough data so that a few unusual responses don’t skew the results.1 pointTrueFalse

The statement regarding data analysts focusing on sample size to ensure that a few unusual responses don’t skew the results is True.

Explanation

Data analysts are keenly aware of the importance of sample size in statistical analysis. A properly determined sample size helps to ensure that the findings derived from the data are reliable and valid. When analysts collect data, they must consider the possibility of outliers or unusual responses that could misrepresent the overall trends or patterns.

1. Influence of Sample Size: A small sample size may be more susceptible to the influence of outliers. In contrast, a larger sample size tends to mitigate the effect of these anomalies, yielding more accurate results.

2. Statistical Power: A larger sample size enhances statistical power, meaning the likelihood of detecting a true effect increases, and the results are more resilient against skewing from unusual responses.

3. Representativeness: Ensuring the sample is representative of the population is also essential. A larger sample size can help capture the diversity and variation present in the population, thereby providing a more comprehensive insight into the overall trends.

Thus, focusing on sample size is a fundamental practice in data analysis to ensure the integrity and reliability of results.