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Reliability refers to a statistical method’s reliability, consistency, and stability. You can determine it by testing-retest consistency and internal consistency.
A test’s credibility is determined by the consistency with which it’s carried out under similar circumstances. A thermometer is an example of a reliable measure. It displays the same temperature for the exact conditions, making it useful to detect long-term illnesses. However, the results of different medical professionals may differ. Therefore, it’s crucial to assess the test as well as the reliability of the questionnaire. Here are a few instances:
The reliability of an assessment tool in similar circumstances is known as test-retest. When a teacher is using the same test to measure the same behaviour for two different groups, with both groups receiving the same score, that test is highly reliable. Research of high-quality is reliable when the results match the properties that are present in the real world. If two thermometers give distinct temperatures, they’re not trustworthy. These thermometers are either defective or malfunctioning.
The student can do research to study the influence of income on the voting process in different nations. She must have a hypothesis before gathering data and looking for evidence to support her hypothesis. Or else, she’ll provide data that don’t support the hypothesis. In this scenario, she failed to form a hypothesis based on the information she https://www.planetchika.com/who-else-wants-to-write-my-essays-for-me/ has collected. If she had formed a hypothesis from all of the available information, it would be more specific.
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