Chapter 9

If other factors are held constant,as the sample variance increases, the estimated standard error also increases. T or F?

True

When the population variance or standard deviation is not known, you must use a t statistic instead of a z-score for a hypothesis test. T or F?

True

A researcher conducts a hypothesis test using a sample of n = 20 from an unknown population. What is the df value for the t statistic?

a) 19* b) 20 c) 21 d) cannot be determined from the information given

Which of the following describes what a confidence interval does?

a) it uses a sample mean to estimate the corresponding population mean* b) it uses a population mean to predict a sample mean c) it uses a level of confidence to estimate a sample mean d) it uses the sample mean to determine a level of confidence

Two samples from the same population both have n = 10 scores with M = 45. If the t statistic is computed for each sample, then what is the relationship between the two t values?

a) the two t statistics will be identical b) the sample with the larger variance will produce the larger t statistic c) the sample with the smaller variance produce the larger t statistic* d) there is no way to predict the relationship between the two t statistics

On average, what value is expected for the t statistic when the null hypothesis is true?

a) 0* b) 1 c) 1.96 d) t > 1.96

A researcher conducts a hypothesis test using a sample from an unknown population. If the t statistic has df = 30, how many individuals were in the sample?

a) n =29 b) n = 30 c) n = 31* d) cannot be determined from the information given

If two samples from the same population are the same size and have the same mean, then they will have the same t statistic. T or F?

False

In general, the larger the value of the sample variance, the greater the likelihood of rejecting the null hypothesis. T or F?

False

Compared to a z-score, a hypothesis test with a t statistic requires less information from the population. T or F?

True

Compared to a z-score, a hypothesis test with a t statistic requires more information from the sample. T or F?

True

If other factors are held constant, as the sample size increases, the estimated standard error decreases. T or F?

True

If other factors are held constant, the bigger the sample is, the greater the likelihood of rejecting the null hypothesis. T or F?

True

Which of the following is not needed to compute a t statistic?

a) a hypothesized value for the population mean b) the value of the population variance or standard deviation* c) the value of the sample mean d) the value of the sample variance or standard deviation

Which set of characteristics will produce the smallest value for the estimated standard error?

a) a large sample size and a small sample variance* b) a large sample size and a large sample variance c) a small sample size and a small sample variance d) a small sample size and a large sample variance

If other factors are held constant, how does sample size influence the likelihood of rejecting the null hypothesis and measures of effect size such as r2 and Cohen's d?

a) a larger sample increases both the likelihood and measures of effect size b) a larger sample increases the likelihood but has little influence on measures of effect size* c) a larger sample decreases the likelihood but has little influence on measures of effect size d) a larger sample decreases both the likelihood and measures of effect size

Under what circumstances can a very small treatment effect be statistically significant?

a) if the sample size big and the sample variance is small* b) if the sample size and the sample variance are both big c) if the sample size is small and the sample variance is big d) if the sample size and the sample variance are both small

If two samples are selected from the same population, under what circumstances will the two samples have exactly the same t statistic?

a) if the samples are the same size and have the same variance b) if the samples are the same size and have the same mean c) if the samples have the same mean and the same variance d) if the samples are the same size and have the same mean and the same variance*

When n is small (less than 30), how does the shape of the t distribution compare to the normal distribution?

a) it is almost perfectly normal b) it is flatter and more spread out than the normal distribution* c) it is taller and narrower than the normal distribution d) there is no consistent relationship between the t distribution and the normal distribtuion

If other factors are held constant, what is the effect of increasing the sample size?

a) it will increase the estimated standard error and increase the likelihood of rejecting Ho b) it will increase the estimated standard error and decrease the likelihood of rejecting Ho c) it will decrease the estimated standard error and increase the likelihood of rejecting* d) it will decrease the estimated standard error and decrease the likelihood of rejecting Ho

If other factors are held constant, what is the effect of increasing the sample variance?

a) it will increase the estimated standard error and increase the likelihood of rejecting Ho b) it will increase the estimated standard error and decrease the likelihood of rejecting Ho* c) it will decrease the estimated standard error and increase the likelihood of rejecting Ho d) it will decrease the estimated standard error and decrease the likelihood of rejecting Ho

If other factors are held constant, how does sample variance influence the likelihood of rejecting the null hypothesis and measures of effect size such as r2 and Cohen's d?

a) larger sample variance increases both the likelihood and measures of effect size* b) larger sample variance increases the likelihood but has little influence on measures of effect size c) larger sample variance decreases the likelihood but has little influence on measures of effect size d) larger sample variance decreases both the likelihood and measures of effect size

How does sample variance influence the estimated standard error and measures of effect size such as r2 and Cohen's d?

a) larger variance increases both the standard error and measures of effect size b) larger variance increases the standard error but decreases measures of effect size* c) larger variance decreases the standard error but increases measures of effect size d) larger variance decreases both the standard error and measures of effect size

Why are t statistics more variable than z-scores?

a) the extra variability is caused by variations in the sample mean b) the extra variability is caused by variations in the sample variance* c) the extra variability is caused by variations in the df value d) none of the other options explains the extra variability for t statistics

Which of the following is a fundamental difference between the t statistic and a z -score?

a) the t statistic uses the sample mean in place of the population mean b) the t statistic uses the sample variance in place of the population variance* c) the t statistic computes the standard error by dividing the standard deviation by n - 1 instead of dividing by n d) all of these are differences between t and z

What value is estimated with a confidence interval using the t statistic?

a) the value for an known sample mean b) the value for an unknown population mean* c) the difference between two populations means d) the difference between two sample means

If a researcher is using a t statistic to test a null hypothesis about a population, what information is needed from the population to calculate the t statistic?

a) you must know the population mean b) you must know the population variance or standard deviation c) you must know the population mean and the variance or standard deviation d) the t statistic does not require any information about the population*