# Hypothesis-Testing Procedure for Separate Groups

The __________ is a hypothesis-testing procedure in which there are two separate groups of people tested and the population variance is not known.

A.t test for dependent means

B.t test for a single sample

C.t test for independent means

D.t test for repeated measures

Question 2 of 25 1.0 Points

Which of the following is an example of a situation in which you could conduct a t test for independent means?

A.A comparison of the SAT scores of a group of 10 students who completed a special SAT preparation course compared to how people do on the SAT in general.

B.A comparison of scores of participants in a memory study in which one group learns the words in alphabetical order and another group learns the words in order of word length.

C.A comparison of participants' scores on a skills test before and after attending a training session for improving the skill.

D.None of the above would be suitable for a t test for independent means.

Question 3 of 25

The comparison distribution for a t test for independent means is a:

A.distribution of differences between means

B.Z distribution (i.e., a normal curve)

C.distribution of difference scores

D.distribution of proportional variance scores

Question 4 of 25

A "distribution of differences between means" can be thought of as a distribution of as:

A.difference scores, in which the difference scores are found by subtracting a series of sample means from the population mean

B.the differences you find when you use several methods, in sequence, of estimating the population mean

C.the differences you get when you repeatedly draw a sample mean from one population and a sample mean from another population and subtract one mean from the other

D.the differences between a single sample from Population 1 and all possible samples from Population 2

Question 5 of 25

You conduct a t test for independent means and reject the null hypothesis. This means that:

A.the samples were from populations that were actually dependent rather than independent

B.the variance of one sample is so much larger than the variance of the other sample that you decide that the variances of the parent populations must not have been the same

C.the mean of one sample is so far from the mean of the other sample that you decide the samples must come from populations with different means

D.the mean of one sample is statistically the same as the mean of the other sample, so they probably come from populations with equal means

Question 6 of 25

When conducting a t test for independent means, a typical research hypothesis might be:

A.the mean of Population 1 is greater than the mean of Population 2

B.the mean of Sample 1 is greater than the mean of Sample 2

C.the mean of Sample 1 is the same as the mean of Sample 2

D.the mean of Population 1 is the same as the mean of Population 2

Question 7 of 25

All of the following are true for both the t test for independent means AND the t test for dependent means, EXCEPT:

A.population variances are estimated from the information in the sample of scores actually studied

B.pretest-posttest experimental designs are common

C.the population means are unknown

D.the sample scores (in some form) are eventually compared to a t distribution

Question 8 of 25

When determining the pooled population variance estimate in a t test for independent means:

A.the variance of at least one of the original populations must be known (as opposed to estimated), but the other can be estimated from sample scores

B.the variance of BOTH of the original populations must be known, as opposed to estimated

C.the estimates based on each of the samples are averaged in such a way as to give more influence to the estimate based on more participants

D.the scores from both samples are combined to form a single sample, and the estimated variance is figured in the usual way, but using this combined sample

Question 9 of 25

In a t test for independent means, the weighted average of the estimates of the population variance from two samples is known as the:

A.estimate of sample standard deviation

B.primed estimate of population standard deviation

C.pooled estimate of population variance

D.pooled estimate of degrees of freedom

Question 10 of 25

In a t test for independent means, the square root of the variance of distribution of differences between means is known as the:

A.overestimate of population variance

B.pooled estimate of population standard deviation

C.variance of the distribution of differences between means

D.standard deviation of the distribution of differences between means

Question 11 of 25

Which of the following is the best way to reduce the variances in the distributions of means when conducting a t test for independent means?

A.Increase the size of the samples

B.Raise the study's level of significance

C.Use the true population variance

D.Treat the two samples as one sample

Question 12 of 25

When conducting a t test for independent means, once the variances are known for each of the distributions of means, the variances can be added together to give the:

A.pooled estimate of the population variance

B.variance of the distribution of differences between means

C.t score

D.power of the study

Question 13 of 25

The variance of a distribution of differences between means equals:

A.the difference between the variances of the two distributions of means

B.the sum of the variances of the two distributions of means

C.the difference between the two estimated population variances

D.the sum of the two estimated population standard deviations

Question 14 of 25

The comparison distribution for a t test for independent means is a t distribution (as opposed to a normal curve) because:

A.tables are not available for the normal curve

B.the population variance is estimated

C.Z distributions were not used at the time the t test for independent means was invented

D.there are more degrees of freedom for a single sample than for when you use two samples

Question 15 of 25

When using a t table, the degrees of freedom you should use for a t test for independent means is the:

A.degrees of freedom for Sample 1 divided by the total degrees of freedom for both samples

B.average of the degrees of freedom for the two samples

C.sum of the two sample sizes, minus one

D.sum of the two samples' degrees of freedom

Reset Selection

Question 16 of 25

Each of the following is part of conducting a t test for independent means, EXCEPT:

A.difference scores are found for each participant

B.the population variances are estimated

C.a comparison is made against a t distribution

D.the variance of the distribution of differences between means is figured

Question 17 of 25

When conducting a t test for independent means:

A.you assume the medians of the two populations are equal

B.you reject the null hypothesis if the t score is more extreme than the cutoff t score

C.you should use only the .01 significance level because of the greater power compared to a t test for dependent means

D.all of the above

Question 18 of 25

Many computer programs provide two sets of results for the t test for independent means. The standard method assumes that the population variances are __________ ; an alternative procedure takes into account that the population variances may be __________.

A.negatively skewed; positively skewed

B.skewed; normally distributed

C.equal; unequal

D.divisible by one another; highly skewed

Question 19 of 25

The effect size for the t test for independent means is the difference between the sample means divided by the:

A.pooled estimate of the population SD

B.SD of the distribution of differences between means

C.SD of difference scores

D.variance of difference scores for the population

Question 20 of 25

For a study using a t test for independent means, with any given total number of participants, power is greatest when the participants are divided into __________ groups.

A.2 equal

B.3 equal

C.2 unequal

D.3 unequal

Question 21 of 25

For a study using a t test for independent means, the approximate number of participants needed for 80% power for an estimated small effect size and using a one-tailed test is:

A.50

B.64

C.310

D.393

Question 22 of 25

Suppose you carry out a study using a t test for independent means. The number of participants in each group is 40 and you conduct a one-tailed test. What would be the approximate level of power if you anticipated a medium effect size? (Consult the power table 9-4).

A..07

B..72

C..97

D..29

Question 23 of 25

Suppose you carry out a study using a t test for independent means. The number of participants in each group is 50 and you conduct a two-tailed test. What would be the approximate level of power if you anticipated a small effect size? (Consult the power table 9-4).

A..53

B..80

C..60

D..17

Question 24 of 25

In an experiment involving 50 participants, which study would have the most power?

A.A study with 5 in the experimental group and 40 in the control group

B.A study with 40 in the experimental group and 10 in the control group

C.A study with 25 in the experimental group and 25 in the control group

D.All would have the same power because power depends on the total number of participants; how they are divided between groups makes no difference.

Question 25 of 25

In a t test for independent means, when the number of scores in the two groups differs, the __________ is used as the equivalent of each group's sample size when determining power.

A.power coefficient

B.pooled estimate

C.harmonic mean

D.independent t scores

© BrainMass Inc. brainmass.com October 25, 2018, 9:45 am ad1c9bdddfhttps://brainmass.com/statistics/type-i-and-type-ii-errors/hypothesis-testing-procedure-separate-groups-585665

#### Solution Summary

The solution gives detailed answers on 25 statistical multiple choice questions including the topics of effect size, sample size, power, t test for independent means and so on.

Hypothesis Testing: Two sample Z test for proportion

1.To compare the effectiveness of two treatments 1 and 2 for a particular disease. Patients were separated in 2 treatment groups. A patient in group 1 received treatment 1 and patients in group 2 received treatment 2. The results are given in the table below:

Treatment 1 Treatment 2

Success 170 180

Failure 30 10

(a) To answer the following question "Do treatments 1 and 2 have different effectiveness?", which test statistic should we use?

(b) A student, to whom the problem had been submitted, replied affirmatively to the question asked. Is the answer correct?