Types of Misleading Data - Essay Sample

Introduction

Statistics are used widely in the organization, studies, politics, and media. Frequently, it is tabled without the background information necessary for its accurate interpretation. Sometimes misleading statics is tabled with a cautious intention to influence individuals and too hasty an agenda. Similarly, it is often due to inattentiveness or just the issue of not comprehending the data correctly. There are different types of ways, which statistics can be misleading. Below is a discussion of five-way statistic can be misleading.

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Bad Sampling

The data can be misguiding by using incorrect sampling techniques to collect data. For example, the type of sample and the size utilized in any statistics serve a substantial role. The majority of questionnaires and polls target specific audiences, which give specific answers, leading to a small and biased sample size. An example of statistics from a wrong sampling is misleading graphs from the new paper.

Details

Misleading data is created by using a purposeful bias to influence data findings without even shamming professional accountability. The bias is generated from the elimination of some data or adjusting data.
This can be corrected by ensuring that data from the two variables are corrected, and none of the variables’ data has been manipulated to favor the other variable. To verify that data has not to be manipulated, it will require scrutiny.

Conclusion

Always think critically about data, especially data from retrospective or observational studies.Discuss with the client what potential baffling variables are in this specific study. Emphasize a statistician being engaged in the design, data gathering, and analysis plan before the study begins. Think rationally about the data, particularly data from observational and retrospective. If the variable is on the causal pathway, it is not a baffling variable one should not change it.