Question

would response bias cause type I or type II errors? why? would sloppy measurements create Type I or type II errors? why?

Answer 1

Answer to the question)

Response bias tends to generate values different from the true population characterstics. Generally the difference is expressed by alternate hypothesis

Thus a response bias always supports the alternate hypothesis, hence forcing the researcher to reject the null

The error caused by rejecting the null hypothesis when in fact it is true is called type I error

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Sloppy measurements: are careless methods of measurement that fail to observe and catch minor differences and make a sharp observation about the underlying characterstic of the population. It fails to show a difference in value, which is supported by the alternate hypothesis. Hence a sloppy measurement would force the researcher to consider the alternate hypothesis to be incorrect and thus accepting the null

The error caused by accepting the null hypothesis when in fact it is false is type II error

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Conclusion: Thus we conclude that response bias can cause type I error and sloppy measurements may lead to type II errors.