Some analysts suggest that the average credit card debt for college students is $5,000, but university officials do not think that is true (i.e. the alternative hypothesis is H1: µ ≠ $5,000). If the 95% confidence interval estimating average credit debt among students is [$4,095, $5,025], what conclusion can be drawn? a. $5,000 is in the interval, so we fail to reject the null. b. $5,000 is not in the interval, so another sample is needed. c. $5,000 is not in the interval, so we reject the null. d. Since this was not based on a population, we cannot make a conclusion.

Some analysts suggest that the average credit card debt for college students is $5,000, but university officials do not think that is true (i.e. the alternative hypothesis is H1: µ ≠ $5,000). If the 95% confidence interval estimating average credit debt among students is [$4,095, $5,025], what conclusion can be drawn? a. $5,000 is in the interval, so we fail to reject the null. b. $5,000 is not in the interval, so another sample is needed. c. $5,000 is not in the interval, so we reject the null. d. Since this was not based on a population, we cannot make a conclusion.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section: Chapter Questions

Problem 8SGR

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Question

Some analysts suggest that the average credit card debt for college students is $5,000, but university officials do not think that is true (i.e. the alternative hypothesis is H₁: µ ≠ $5,000). If the 95% confidence interval estimating average credit debt among students is [$4,095, $5,025], what conclusion can be drawn?

a. $5,000 is in the interval, so we fail to reject the null.

b. $5,000 is not in the interval, so another sample is needed.

c. $5,000 is not in the interval, so we reject the null.

d. Since this was not based on a population, we cannot make a conclusion.

Definition Definition Method in statistics by which an observation’s uncertainty can be quantified. The main use of interval estimating is for describing a range that is made by transforming a point estimate by determining the range of values, or interval within which the population parameter is likely to fall. This range helps in measuring its precision.

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