Biassing is a term that is often used in the fields of statistics and electronics. It refers to the process of intentionally or unintentionally influencing the outcome of a measurement or experiment. Biassing can have a significant impact on the accuracy and validity of results, and it is important to understand the concept in order to avoid potential errors.
Definitions
Biassing can be defined as the act of introducing a systematic error or distortion into a measurement or experiment. This can occur through a variety of means, such as selecting a biased sample, using biased measurement tools, or intentionally manipulating data. Biassing can also refer to the process of adjusting the settings of an electronic device to achieve a desired outcome.
Origin
The term “bias” has its roots in the Latin word “biase,” which means “oblique.” The term was first used in the context of statistics in the early 20th century, and has since become a common term in the field of research and experimentation.
Meaning in different dictionaries
According to the Oxford English Dictionary, biassing is defined as “the introduction of a bias or prejudice into a measurement or experiment.” Merriam-Webster defines it as “the act of causing something to have a particular bias or tendency.” The Cambridge Dictionary defines it as “the act of influencing something in a particular way, often unfairly.”
Associations
Biassing is often associated with the potential for error and distortion in research and experimentation. It is important to be aware of potential biases and take steps to minimize their impact in order to ensure the accuracy and validity of results.
Synonyms
Some synonyms for biassing include influencing, distorting, prejudicing, and skewing.
Antonyms
Antonyms for biassing include objectivity, fairness, impartiality, and neutrality.
The same root words
Words with the same root as biassing include biased, biasness, and bias.
Example Sentences
- The researcher was accused of biassing the study by selecting only participants who were likely to support their hypothesis.
- The technician adjusted the settings on the machine to biass the results in favor of the desired outcome.
- The journalist was criticized for biassing their reporting by presenting only one side of the story.
- The judge emphasized the importance of avoiding biassing the jury in their decision-making process.
- The scientist took steps to minimize the potential for biassing in their experimental design, including using a randomized sample and double-blind procedures.