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In statistics, there are two types of errors for hypothesis tests: Type 1 error and Type 2 error. Type 1 error is when the null hypothesis is rejected, but actually true. It is often called alpha. An example of Type 1 error would be a "false positive" for a disease. Type 2 error is when the null hypothesis is not rejected, but actually false. It is often called beta. An example of Type 2 error would be a "false negative" for a disease. Type 1 error and Type 2 error have an inverse relationship. The larger the Type 1 error is, the smaller the Type 2 error is. The smaller the Type 2 error is, the larger the Type 2 error is. Type 1 error and Type 2 error both can be reduced if the sample size is increased.
Define market research, describe its purpose, and give at least one example of a type of market research that producers conduct
descriptive
An example scenario?æof a type II error is a woman's pregnancy?ætest showed negative even if the woman is?æindeed?æpregnant. If the purpose of the test is to prove the probability that a right decision can be made even if the null is incorrect, meaning to correctly reject it, then the research can be published.
An example of informal research could be conducting surveys or interviews with friends, family, or colleagues to gather opinions or perspectives on a particular topic. This type of research is typically done without strict guidelines or structured methodologies.
An experimental error is is
Historical research is the examination of a past event and providing details concerning it. One example is how slavery impacted the Civil War. This is an informative type of research.
If error was avoidable, then there's nothing left for future research improvement.
type1 error is more dangerous
It depends on whether it is the Type I Error or the Type II Error that is increased.
Type your answer here omission error commission error principles error compensatory error
It depends on whether it is the Type I Error or the Type II Error that is increased.