A repeated-measures test usually is more likely to detect a real treatment effect than an independent-measures test because the repeated-measures design typically has a smaller variance and a smaller estimated standard error. A. TrueB. False

A. True

Explanation:

The repeated-measures test is a technique used in research to measure a variable's accuracy & precision. It involves measuring a certain variable multiple times; this measurement can be carried out under the same conditions or different conditions over a period of time.

Independent-measures test(also called the two sample t-test) is a technique employed in inferential statistics to ascertain if there is a significant difference between 2 samples taken separately & independent of each other

Because the repeated-measures test by design is carried out repetitively to verify the accuracy of a variable rather than 'incidentally or accidentally'(as in the case of Independent-measures test), it typically has a smaller variance and a smaller estimated standard error as compared to the Independent-measures test. Hence, it is True (option A)

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explanation: