Question

1-4): True or False?

1) The sample statistic is at the center of a confidence interval for that statistic.

2) In a hypothesis test, increasing the significance level increases the chance of making a type 1 error.

3) Failure to reject the null hypothesis test in a hypothesis test implies strong support for the null hypothesis.

4) When no prior belief about a population characteristic is held, construction of a confidence interval, rather than the use of hypothesis testing, is used to estimate the population characteristic.

Answer 1

1) True

( Confidence interval is a range computed using sample statistic to estimate an unknown population parameter with a stated level of confidence. At the center of a confidence interval lies the sample statistic. General form of confidence interval is given as: sample statistic margin of error.)

2) True

( Since, P(type 1 error) = where,   is the level of significance set for a hypothesis test. It is the probability of rejecting a null hypothesis given that it is true.Therefore, when increases the chance of making a type 1 error also increases.)

3) True

( Failing to reject the null hypothesis doesnot mean that the null hypothesis is true, only that the test did not prove it to be false i.e, the test implies strong support for the null hypothesis.)

4) True

( If no prior information is given about the populaton, then we can construct a confidence interval based on sample statistics. Then from the confidence interval we will get a range of the population characteristics.)