Question 3

Missing data tend to skew the results of the analysis.

Starting an analysis with flawed data, particularly when data is missing, can lead to skewed results. This compromises the integrity of the analysis, as conclusions drawn may not accurately reflect reality.

A) More time is spent managing data than analyzing data.

While it is true that flawed data can increase the amount of time spent on data management, this option does not directly address the consequences of analysis with flawed data. The core issue is the impact on the results, not the time allocation for data management.

B) Data must be put in a table or a chart so that errors can be more easily detected.

This statement focuses on a method for organizing data rather than the direct consequences of starting with flawed data. While organizing data can help identify errors, it does not capture the inherent problems that arise from the flawed data itself.

C) Missing data tend to skew the results of the analysis.

This option accurately identifies the primary issue with starting an analysis with flawed data. Missing data can lead to biased results, as the analysis may not fully represent the population or phenomenon being studied, ultimately misleading conclusions.

D) Spreadsheets must be used to increase the likelihood of analyzing the flawed data.

This statement implies that using spreadsheets would somehow improve the analysis of flawed data, which is misleading. The use of spreadsheets does not rectify the underlying problem of flawed data; it merely provides a platform for analysis.

Conclusion

Option C is definitively correct as it directly addresses the detrimental effects of flawed data on analysis outcomes. The other options either misinterpret the implications of flawed data or focus on unrelated aspects, failing to capture the critical point that missing data skews results and undermines the validity of any analysis conducted.