Stats Final
When does sampling error occur? A. When a sample statistic is not equal to the population parameter as a result of nonchance factors. B. When a sample statistic is not equal to the population parameter as a result of chance factors. C. When there has been an error in calculating the standard error of the mean. D. When there has been an error in selecting participants for a sample.
B
What are the degrees of freedom for an independent samples t-test that uses two samples with n = 12 in each sample? A. 23 B. 22 C. 21 D. 20
B
What are we stating if we reject the null hypothesis? A. The sample mean difference represents no difference between two population µs. B. The sample mean difference represents a difference between two population µs that is not zero. C. The sample mean difference is zero. D. The difference between the population means is zero.
B
What does 𝛼 always represent in statistical hypothesis testing? A. The probability of making a correct decision about H0 B. The relative size of the region of rejection C. The critical value D. 0.05
B
What happens to the probability of committing a Type I error if the level of significance is changed from 𝛼 = 0.01 to 𝛼 = 0.05? A. The probability of committing a Type I error will decrease B. The probability of committing a Type I error will increase C. The probability of committing a Type I error will remain the same D. The change in probability will depend on your sample size
B
What should you conclude if two randomly selected sample means produce a confidence interval that is -1.51 ≤ µ1 -µ2 ≤ 2.62? A. A math error was made in the computation of the interval. B. You are 95% confident that the interval between -1.51 and 2.62 contains the difference between the µs for the two conditions. C. The sample means probably came from populations with µ1 - µ2 = 2.0. D. You are 95% confident that the difference between the conditions is 2.0.
B
When are two samples considered to be related? A. When we randomly select and assign participants to samples without regard to other participants selected for either sample. B. When we randomly select and assign participants to samples, making sure to pair each person in one sample with a particular person in the other sample. C. When we randomly select and assign participants t o samples, making sure that each participant serves in only one condition of our experiment. D. When the null hypothesis of the two-sample t-test is retained.
B
10 volunteers recorded their blood pressure in a room with an aquarium and then in a room without one. The appropriate design for testing the significance of the difference between the means is A. related samples t-test. B. independent samples t-test. C. one-sample t-test. D. z-test.
A
18 obese volunteers weighed themselves before and after a 2 day fast. The appropriate design for testing the significance of the difference between the means is A. related samples t-test. B. independent samples t-test. C. one-sample t-test. D. z-test.
A
How is the t-test for related samples performed? A. By conducting a one-sample t-test on the sample of difference scores B. By conducting an independent samples t-test on the sample of difference scores C. By converting the scores to standard scores and then performing a related samples t-test D. By measuring the population variance and testing it using an independent samples t-test
A
How many subjects participated in an independent samples t-test if a researcher reports t(20) = 3.68? A. 22 B. 21 C. 20 D. 18
A
If all other factors are held constant, increasing the level of confidence will have what kind of effect on the width of a confidence interval? A. Increase it B. Decrease it C. Increase it or decrease it D. Have no effect on it
A
In an experiment, the "proportion of variance accounted for" goes by another name. It is called the A. effect size. B. error reduction coefficient. C. confidence interval. D. standard error of the difference between means.
A
In using a sampling distribution of means for statistical hypothesis testing, the mean of the sampling distribution will always equal A. the µ described by H0 B. the µ described by Ha C. the sample mean D. 0.0
A
N represents ______________, whereas n represents ______________. A. the total number of scores in the study; the number of scores in each sample B. the number of scores in each sample; the total number of scores in the study C. the number of pairs in the study; the number of difference scores in the study D. the number of difference scores in the study; the number of pairs in the study
A
Some people claim that psychology is common sense. A. 54.22 ≤ µ ≤ 65.78 B. 54.26 ≤ µ ≤ 65.75 C. 55.25 ≤ µ ≤ 64.75 D. 69.22 ≤ µ ≤ 80.78
A
To determine the extent to which the conditions of the independent variable determine dependent scores, we should compute A. the effect size. B. an independent samples t-test. C. a related samples t-test. D. the standard error of the difference between means.
A
Using a line graph when interpreting the results of a two-sample experiment allows us to A. envision the scatterplot that the data would form. B. determine the strength of the relationship. C. see whether there are significant differences between the samples. D. apply correlational statistics.
A
What does the standard error of the difference tell us? A. How spread out the values of (X̄1 - X̄2) are when the sampling distribution is created based on samples of the size we selected and our pooled variance. B. How spread out the values of (µ1 - µ2) are when the sampling distribution is created based on samples of the size we selected and our pooled variance. C. How spread out the values of (X̄1 - X̄2) are in our sample distribution. D. How spread out the values of (µ1 - µ2) are in the distribution of the two populations from which we drew our samples.
A
What is pooled variance? A. The weighted average of the sample variances. B. The variance of the difference between the sample means. C. The sum of the two sample variances. D. The variance of the populations from which the samples were drawn.
A
Which of the following is correct regarding the probability of making a Type I error? A. p = 𝛼 B. p = (1-𝛼) C. p < 𝛼 D. p > 𝛼
A
A researcher asked 26 extroverts and 36 introverts how happy they were. The results are shown in the graph below (wtf no they're not). The t(obt) = 2.96. Calculate the strength of the relationship using the squared point-biserial correlation coefficient. A. -0.13 B. +0.13 C. -0.36 D. +0.36
B
Cultural Diversity Task Force A. 0.886 B. 0.829 C. 0.645 D. 0.643
B
For a one-tailed test where the predicted value of the sample mean is larger than the population mean and 𝛼 = 0.05, the critical value of z is always equal to A. ±1.645 B. +1.645 C. -1.645 D. ±1.96
B
How is the null hypothesis of the independent samples t-test verbalized? A. There is a relationship between the independent variable and the dependent variable. B. There is no relationship between the independent variable and the dependent variable. C. The difference between the sample means is equal to µ. D. The independent variable has an effect on the dependent variable.
B
If a sample mean has a value equal to µ, the corresponding value of t will be equal to A. +1.0 B. 0.0 C. -1.0 D. +2.0
B
Suppose the average reading speed of 15 randomly selected elementary school students. A. Increases in age cause increases in reading speed. B. We have evidence that older students tend to read faster. C. There is a proven relationship between age and reading speed. D. The difference between the older and younger students is due to sampling error.
B
Suppose you perform a two-tailed independent samples t-test, using 𝛼 = 0.05, with 15 participants in one group and 16 participants in the other group. Your t(obt) is 4.56, which is significant. Which of the following is the correct way to report this finding? A. t(31) = 4.56; p < 0.05 B. t(29) = 4.56; p < 0.05 C. t(29) = 4.56; p > 0.05 D. t(29) = 4.56; p = 0.05
B
The logic behind computing a confidence interval is to compute the highest and lowest values of a ________ mean that are not significantly different from those of _______. A. sample; the current sample mean B. population; the current sample mean C. population; the population mean specified in the null hypothesis D. sample; the population mean specified in the null hypothesis
B
There are two ways in which samples can be related. In a _______ design, each participant in one condition is paired with a participant in the other condition. In a _______ design, each participant is tested under both conditions of the independent variable. A. repeated measures; matched samples B. matched samples; repeated measures C. dependent samples; related samples D. related samples; dependent samples
B
There's a problem with Cohen's d value and I have no idea what that means and the girl's name is Clarinda so just know those things. A. d = 4.00 B. d = 0.707 C. d = 0.25 D. d = 0.50
B
When is a one-tailed test used? A. When no relationship is predicted B. When a relationship is predicted and the direction in which the scores will change is predicted C. When the demonstrated relationship is predicted D. When a relationship is predicted without stating the direction in which the scores will change
B
When one has the option, a related samples design should be chosen over an independent samples design because A. related samples result in *more* variability, and therefore the design is *more* powerful. B. related samples result in *less* variability, and therefore the design is *more* powerful. C. related samples designs are simpler to use. D. related samples designs are intrinsically better than independent samples designs.
B
When statisticians report that the results from an experiment are significant, this means the results A. are scientifically important B. are too unlikely to accept as sampling error C. differ from what was predicted by the experimental hypothesis D. do not differ from what was predicted by the null hypothesis
B
When we construct a 95% confidence interval, we are 95% sure that the A. sample mean difference falls within the interval. B. population mean difference falls within the interval. C. population mean difference is at the center of the interval. D. sample mean difference is at the center of the interval.
B
When we construct a 95% confidence interval, we are 95% sure that the A. sample mean falls within the interval B. population mean falls within the interval C. sample mean is at the center of the interval D. population mean is at the center of the interval
B
Which of the following is correct regarding the probability of avoiding a Type I error? A. p = 𝛼 B. p = (1-𝛼) C. p < 𝛼 D. p > 𝛼
B
Which of the following is one of the assumptions of a one-sample t-test? A. The obtained scores are on an ordinal or interval scale. B. The population standard deviation is estimated by computing sx. C. The population standard deviation is known. D. The population distribution is skewed.
B
Which of the following represents a Type I error? We say that something A. works when it really does B. works when it really doesn't C. doesn't work when it really does D. doesn't work when it really doesn't
B
Daniel conducted an independent samples t-test and found t(20) = 0.57; p > .05. He then calculated his effect size and obtained a value of d = 0.02. What should Daniel say in the report on his results? A. He should indicate he has obtained a significant test result with a small effect size. B. He should indicate his t-test is *not* significant and that his effect size is a *small* one. C. He should indicate his t-test is *not* significant. He should, therefore, *not* report his effect size. D. He should recheck his calculations because a t-value of 0.57 is not possible.
C
Developmental psychologist A. 0.83 B. 0.98 C. 3.72 D. 4.39
C
For a study with a related samples design and 30 participants in which each participant is measured twice (repeated measures), what is the critical value? Assume a two-tailed test with 𝛼 = 0.05. A. 1.699 B. 2.042 C. 2.045 D. 2.048
C
For a two-tailed test where 𝛼 = 0.05, the critical value of z is always equal to A. -1.96 B. +1.96 C. ±1.96 D. ±1.645
C
How does increasing the size of the samples increase the power of an experiment? A. *Larger* number of subjects result in *smaller* degrees of freedom, which results in a *smaller* value of t(crit). B. *Larger* number of subjects result in *larger* degrees of freedom, which results in a *larger* value of t(crit). C. *Larger* number of subjects result in *larger* degrees of freedom, which results in a *smaller* value of t(crit). D. *Larger* number of subjects result in *smaller* degrees of freedom, which results in a *larger* value of t(crit).
C
How is the t-distribution defined? A. The distribution of all possible values of t B. How far the sample mean is from the µ of the sampling distribution in estimated standard error units. C. The distribution of al possible values of t for random samples having the same N from the population described by H0 D. The distribution of all possible values of t for random samples having the same N from the population described by Ha.
C
If a researcher predicts that the experimental treatment will produce a decrease in an independent samples t-test (X̄1 - X̄2 > 0), how will the null hypothesis be stated? A. H0: µ1 - µ2 = 0 B. H0: µ1 - µ2 ≠ 0 C. H0: µ1 - µ2 ≤ 0 D. H0: µ1 - µ2 ≥ 0
C
In the independent samples t-test, we always test whether the difference between X̄1 and X̄2 is significantly different from the A. population variance B. sampling distribution mean described by Ha C. difference between µ1 and µ2 described by H0 D. difference between µ1 and µ2 described by Ha
C
One way to increase power is to minimize the variability of the raw scores. How is this accomplished? A. Change 𝛼 from 0.05 to 0.01. B. Change the size of N from 100 to 25. C. Design and conduct the experiment so that all the subjects in a sample are treated in a consistent manner. D. Select two very different levels of the independent variable that are likely to produce a relatively large difference between the means.
C
The confidence interval for a single µ is A. a point interval estimation of the population mean. B. an interval containing values of µ that our sample mean is *not* likely to represent. C. an interval containing values of µ that our sample mean is likely to represent. D. a point on the variable at which the population µ is expected to fall.
C
The major problem with point estimation is that it A. cannot be utilized to estimate population parameters B. cannot be utilized with sample data C. is extremely vulnerable to sampling error D. provides only a single point in its estimate
C
The power of a statistical test is the probability of A. failing to reject a false null B. failing to reject a true null C. rejecting a false null D. rejecting a true null
C
The sampling distribution of differences between means is the distribution of all possible A. sample means B. differences between two means with specified sample sizes C. differences between two means with specified sample sizes, drawn from the raw score populations described by H0 D. differences between two means with specified sample sizes, drawn from the raw score populations described by Ha
C
What are the degrees of freedom for an independent samples t-test that uses one sample with n = 13 and one sample with n = 15? A. 28 B. 27 C. 26 D. 24
C
What can we conclude if we reject the null hypothesis in an independent samples t-test? A. It is likely that sampling error accounted for the differences between the sample means. B. It is likely that the sample means came from the same population. C. The difference between our sample means is unlikely to be representing zero difference in the population means. D. The difference between our sample means is merely a poor representation of zero difference in the population means.
C
What is sX̄? A. The estimated population standard deviation B. The population standard deviation C. The estimated standard error of the mean D. The standard error of the mean
C
What is the purpose of using a confidence interval? A. To estimate the value of a sample mean B. To use a level of confidence to estimate a sample mean C. To use a sample mean to estimate the value of a population mean D. To use the sample mean to determine the population level of confidence
C
What is the standard error of the difference? A. The standard deviation of the sample means. B. The standard deviation of the sampling distribution of the mean. C. The standard deviation of the sampling distribution of the mean differences. D. The pooled standard deviation from the populations from which the samples are drawn.
C
When can the z-test be used in statistical hypothesis testing? A. When the measure of central tendency used for the raw scores is the median B. When the raw scores are transformed from a nominal scale to a ratio scale C. When the raw score population's standard deviation is known D. When the z-test standard deviation is known
C
Which kind of estimation is performed when we claim that a population mean is equal to the sample mean? A. Interval estimation B. Mean estimation C. Point estimation D. Population estimation
C
Which of the following is NOT one of the assumptions of the t-test for independent samples? A. The population mean is unknown B. There are two random samples of interval/ratio scores C. There is homogeneity of variance D. The standard deviation of at least one of the populations is known
D
If a researcher predicts that the experimental treatment will produce an increase in an independent samples t-test (X̄1 - X̄2 < 0), how will the null hypothesis be stated? A. H0: µ1 - µ2 = 0 B. H0: µ1 - µ2 ≠ 0 C. H0: µ1 - µ2 ≤ 0 D. H0: µ1 - µ2 ≥ 0
D
If a sample mean is different from a particular population µ, we can conclude that the sample mean probably represents some other population or that A. the sample mean does not represent the sample statistic B. an error was made in calculating the sample mean C. an error was made in calculating standard error D. the sample mean occurred as a result of sampling error
D
In a related samples design, H0 states that A. our population mean represents the distribution of difference scores wherein µD ≠ 0. B. our population mean represents a sample of difference scores where µD ≠ 0. C. our sample mean represents a population of difference scores for which µD ≠ 0. D. our sample mean represents a population of difference scores for which µD = 0.
D
On the basis of a pretest on knowledge of foreign languages, each subject in the 9:00 class was matched with a subject in the 10:30 class. The 9:00 class used a participant approach to the study of Latin, and the 10:30 class used the Hiffendorf method. At the end of the term, the same Latin test was given to both classes. The appropriate design for testing the significance of the difference between the means is A. related samples t-test. B. independent samples t-test. C. one-sample t-test. D. z-test.
D
One way to increase power is to maximize the difference produced by the two conditions in the experiment. How is this accomplished? A. Change 𝛼 from 0.05 to 0.01. B. Change the size of N from 100 to 25. C. Design and conduct the experiment so that all the subjects in a sample are treated in a consistent manner. D. Select two very different levels of the independent variable that are likely to produce a relatively large difference between the means.
D
Suppose that you measure the IQ of 14 students with short index fingers. A. There is no relationship between length of index finger and IQ. B. There is a relationship between length of index finger and IQ. C. The relationship between length of index finger and IQ does not exist. D. We do not have convincing evidence that our measured relationship between length of index finger and IQ is due to anything other than sampling error.
D
The assumptions of the t-test for related samples are the same as those for the t-test for independent samples except for requiring A. that the dependent variable be measured on an interval or ratio scale. B. that the population represented by either sample form a normal distribution. C. homogeneity of variance. D. that each score in one sample be paired with a particular score in the other sample.
D
Unless we use the correct t(crit) from the t-distribution for the appropriate N, A. we will fail to reject H0. B. we will always reject H0. C. the probability of making a Type I error will increase. D. the probability of making a Type I error will not equal 𝛼.
D
What does t(obt) indicate in an independent samples t-test? A. The probability of rejecting the null hypothesis B. The probability of retaining the null hypothesis C. The location of the population mean difference, (µ1 - µ2), relative to the mean of the sampling distribution of mean differences D. The location of the sample mean difference relative to the mean of the sampling distribution of mean differences in standard error of the difference units
D
What does the homogeneity of variance assumption state? A. The two sample variances are equal B. The population variance is equal to the variance of the sample selected from it C. The variance must stay constant for each subject in the experiment D. The variance in one population is equal to the variance in another population
D
What does the t(obt) value indicate? A. The probability of rejecting the null hypothesis. B. The probability of retaining the null hypothesis. C. How far the population mean, µ, is from the mean of the sampling distribution of means. D. How far the sample mean is from the µ of the sampling distribution in estimated standard error units.
D
What is the next step in an experiment if the results of an independent samples t-test are statistically significant? A. Correlate the scores on the dependent variable with the conditions of the independent variable. B. Compute a predicted score for each true score on the dependent variable. C. Make a prediction about the strength of the relationship based on the scatterplot. D. Compute a confidence interval for the difference between the µs.
D
When H0 is true, the mean of the sampling distribution of differences between means is equal to A. the population mean µ. B. 1.0. C. the mean of the two sample means. D. zero.
D
When experimental results are significant, this means that the _____ hypothesis has been _____. A. experimental; rejected B. alternative; rejected C. null; accepted D. null; rejected
D
When is a t-test used instead of a z-test? A. When the population µ is known B. When the population deals with two samples C. When the population standard deviation is known D. When the population standard deviation is unknown
D
When is a two-tailed test used? A. When no relationship is predicted B. When a relationship is predicted and the direction in which the scores will change is predicted C. When the demonstrated relationship is predicted D. When a relationship is predicted without stating the direction in which the scores will change
D
Which hypothesis is actually being tested in statistical hypothesis testing? A. The error hypothesis B. The experimental hypothesis C. The alternative hypothesis D. The null hypothesis
D
Which of the following accurately defines a Type II error? A. Rejecting the null when it is true B. Rejecting the null when it is false C. Failing to reject the null when it is true D. Failing to reject the null when it is false
D
Which of the following describes the situation if the relationship you are testing in your experiment really exists? A. The null hypothesis B. The statistical hypotheses C. The real-world hypothesis D. The alternative hypothesis
D
T/F: The null hypothesis specifies the value of the sample statistic.
True
T/F: There is evidence in the Bible of God creating something instantly.
True
T/F: When we reject the null, we reject chance.
True
