According to a report, the standard deviation of monthly cell phone bills was $$ 4.85$ in 2017 . A researcher suspects that the standard deviation of monthly cell phone bills is different today.

What would it mean to make a Type I error?
A. The sample evidence did not lead the researcher to believe the standard deviation of monthly cell phone bills is different from $$ 4.85$ when, in fact, the standard deviation of bills is different from $$ 4.85$ .

B. The sample evidence did not lead the researcher to believe the standard deviation of monthly cell phone bills is higher than $$ 4.85$ when, in fact, the standard deviation of bills is higher than $$ 4.85$ .

C. The sample evidence led the researcher to believe the standard deviation of monthly cell phone bills is higher than $$ 4.85$ when, in fact, the standard deviation of bills is $$ 4.85$ .
D. The sample evidence led the researcher to believe the standard deviation of monthly cell phone bills is different from $$ 4.85$ when, in fact, the standard deviation of bills is $$ 4.85$ .

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$D. The sample evidence led the researcher to believe the standard deviation of monthly cell phone bills is different from $4.85 when, in fact, the standard deviation of bills is $4.85.$

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Step 1 ：A Type I error, also known as a false positive, occurs when we reject a true null hypothesis. In this context, the null hypothesis is that the standard deviation of monthly cell phone bills is still $4.85.

Step 2 ：Therefore, a Type I error would occur if the researcher concludes that the standard deviation is different from $4.85 w h e n i t i s a c t u a l l y s t i l l$ 4.85.

Step 3 ： $D. The sample evidence led the researcher to believe the standard deviation of monthly cell phone bills is different from $4.85 when, in fact, the standard deviation of bills is $4.85.$

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