When we conclude that an experiment does not provide sufficient evidence to reject the null hypothesis when,in fact,an independent variable does produce an effect,the inferential statistics problem is called a

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A Type II error is when we fail to reject the null hypothesis even though it is actually false. This means that we are accepting a false null hypothesis and concluding that there is no significant effect or difference between the groups being compared. This can happen when the sample size is too small or there is too much variability in the data, making it difficult to detect the true effect of the independent variable.

When We Conclude That an Experiment Does Not Provide Sufficient