Deck 10: The Hypothesis of Difference
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Deck 10: The Hypothesis of Difference
1
In order to calculate the estimated standard error of difference, all that need be known is (are)
A) the means of the two samples
B) the sizes of the two samples
C) the standard deviation of the two samples
D) the standard errors of the mean for each of the two samples
A) the means of the two samples
B) the sizes of the two samples
C) the standard deviation of the two samples
D) the standard errors of the mean for each of the two samples
the standard errors of the mean for each of the two samples
2
10-16. When pairs of samples are selected from two separate populations, the mean of the distribution of differences is assumed to be
A) some value other than zero
B) zero
C) a constant
D) equal to the mean of the distribution of means
A) some value other than zero
B) zero
C) a constant
D) equal to the mean of the distribution of means
A
3
When the difference between pairs of randomly selected means are obtained, the resulting distribution is called
A) the distribution of means
B) the distribution of differences
C) the distribution of individual sample scores
D) the ogive distribution
A) the distribution of means
B) the distribution of differences
C) the distribution of individual sample scores
D) the ogive distribution
B
4
10-15. Regarding the distribution of differences, the assumption of normality is based on
A) Pascal's triangle
B) Gossett's law
C) the Central Limit theorem
D) the Gaussian law
A) Pascal's triangle
B) Gossett's law
C) the Central Limit theorem
D) the Gaussian law
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5
The distribution of differences is composed of the differences between
A) raw scores and the mean
B) the highest and lowest scores in a distribution
C) the standard deviation and the standard error of the mean
D) pairs of randomly selected sample means
A) raw scores and the mean
B) the highest and lowest scores in a distribution
C) the standard deviation and the standard error of the mean
D) pairs of randomly selected sample means
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6
10-11. The estimated standard error of difference is an estimate of
A) centrality
B) variability
C) normality
D) none of these, since the estimated standard error of difference is not a
A) centrality
B) variability
C) normality
D) none of these, since the estimated standard error of difference is not a
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7
10-14. The distribution of differences is
A) a sampling distribution
B) a distribution of parameters
C) always leptokurtic in shape
D) always platykurtic in shape
A) a sampling distribution
B) a distribution of parameters
C) always leptokurtic in shape
D) always platykurtic in shape
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8
10-18. In order to ensure a sampling error of zero, each sample must
A) be randomly selected
B) be equal in size
C) be selected from the same population
D) none of these, since one can never assume a sampling error of zero
A) be randomly selected
B) be equal in size
C) be selected from the same population
D) none of these, since one can never assume a sampling error of zero
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9
When graphing the distribution of differences, the ordinate is used to represent
A) a sample mean
B) the difference between the mean of the individual raw scores and the sample mean
C) the difference between two sample means
D) frequency of occurrence
A) a sample mean
B) the difference between the mean of the individual raw scores and the sample mean
C) the difference between two sample means
D) frequency of occurrence
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10
Whenever the distribution of differences is normally shaped, and all its assumptions are met, then
A) the samples must represent different populations
B) the samples must represent a single population
C) more than two populations must be involved
D) none of these, since when its assumptions are met, the distribution of
A) the samples must represent different populations
B) the samples must represent a single population
C) more than two populations must be involved
D) none of these, since when its assumptions are met, the distribution of
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11
10-13. When selecting a pair of random-sample means from a single population, the probability of the first mean being higher than the second mean is
A) 1.00
B) 0
C) .50
D) either a or b, but never c
A) 1.00
B) 0
C) .50
D) either a or b, but never c
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12
10-10. The estimated standard error of difference may be obtained on the basis of the information contained in
A) a single sample
B) a pair of random samples
C) the sampling error
D) a single z score
A) a single sample
B) a pair of random samples
C) the sampling error
D) a single z score
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13
The estimated standard deviation of the distribution of differences is used to predict the
A) standard error of the mean
B) standard error of difference
C) standard error of the estimate
D) actual standard score
A) standard error of the mean
B) standard error of difference
C) standard error of the estimate
D) actual standard score
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14
10-17. In order to use the estimated standard error of difference for making probability estimates, both samples must
A) have equal means
B) have unequal means
C) be free of sampling error
D) have similar amounts of variability
A) have equal means
B) have unequal means
C) be free of sampling error
D) have similar amounts of variability
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15
Whenever the mean of the distribution of differences equals zero, then one can be fairly safe in concluding that
A) the samples probably represent a single population
B) the samples probably represent different populations
C) there was absolutely no sampling error
D) none of these, since the mean can never equal zero
A) the samples probably represent a single population
B) the samples probably represent different populations
C) there was absolutely no sampling error
D) none of these, since the mean can never equal zero
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16
10-12. The Central Limit theorem states that the distribution of differences is
A) always based on a pair of samples
B) always based on a single sample
C) a parameter
D) approximately normal in shape
A) always based on a pair of samples
B) always based on a single sample
C) a parameter
D) approximately normal in shape
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17
When graphing the distribution of differences, the abscissa is used to represent
A) a sample mean
B) the difference between the mean of the individual raw scores and the sample mean
C) the difference between two sample means
D) the frequency of occurrence
A) a sample mean
B) the difference between the mean of the individual raw scores and the sample mean
C) the difference between two sample means
D) the frequency of occurrence
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18
When all samples are drawn from a single population, the mean of the distribution of differences should approximate
A) zero
B) +1.0
C) -1.0
D) the mean of the distribution of means
A) zero
B) +1.0
C) -1.0
D) the mean of the distribution of means
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19
If the mean of the distribution of differences were to equal -6.00, this would indicate that
A) the standard deviation of the distribution is a function of the range
B) the samples probably represent different populations
C) the samples were probably selected from a single population
D) none of these, since the mean can never be negative
A) the standard deviation of the distribution is a function of the range
B) the samples probably represent different populations
C) the samples were probably selected from a single population
D) none of these, since the mean can never be negative
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20
If all the possible pairs of sample means were obtained from a single population, the mean of the distribution of differences would be
A) a statistic
B) a parameter
C) identical with the mean of the distribution of means
D) equal to one-sixth of the range
A) a statistic
B) a parameter
C) identical with the mean of the distribution of means
D) equal to one-sixth of the range
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21
Whenever the null hypothesis is rejected, then
A) the alternative hypothesis must also be rejected
B) the alternative hypothesis must be accepted
C) the alternative hypothesis must be tested separately
D) none of these, since the null hypothesis and the alternative hypothesis are
A) the alternative hypothesis must also be rejected
B) the alternative hypothesis must be accepted
C) the alternative hypothesis must be tested separately
D) none of these, since the null hypothesis and the alternative hypothesis are
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22
The difference between the T score and the t ratio is that
A) the T score always results in a higher value than does the t ratio
B) the T score refers to several sample means, whereas the t ratio only refers to two sample means
C) the T score is used as a measure of individual performance, whereas the t ratio evaluates the possibility of a performance difference between two
Independent groups
D) none of these, since T and t are the same
A) the T score always results in a higher value than does the t ratio
B) the T score refers to several sample means, whereas the t ratio only refers to two sample means
C) the T score is used as a measure of individual performance, whereas the t ratio evaluates the possibility of a performance difference between two
Independent groups
D) none of these, since T and t are the same
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23
The alternative hypothesis for the independent t test is also called
A) the hypothesis of association
B) the hypothesis of difference
C) the null hypothesis
D) none of these
A) the hypothesis of association
B) the hypothesis of difference
C) the null hypothesis
D) none of these
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24
The t test for two independent samples may only be used when
A) the selection of subjects for the first group does not depend in any way on the selection of subjects for the second group
B) the subjects used in the two samples are matched on some relevant variable
C) the same subjects are used twice
D) the degrees of freedom are independent of the sample sizes
A) the selection of subjects for the first group does not depend in any way on the selection of subjects for the second group
B) the subjects used in the two samples are matched on some relevant variable
C) the same subjects are used twice
D) the degrees of freedom are independent of the sample sizes
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25
For the independent t test, the null hypothesis is always stated in terms of
A) the sample means
B) the population means
C) both of these
D) neither of these
A) the sample means
B) the population means
C) both of these
D) neither of these
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26
The independent t ratio may be used to evaluate whether
A) two samples represent a single population
B) two samples represent different populations
C) both of these
D) neither of these
A) two samples represent a single population
B) two samples represent different populations
C) both of these
D) neither of these
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27
The independent t ratio specifies how far the difference between the sample means deviated from
A) an assumed mean of 50, in units of standard deviations
B) an assumed mean of 100, in units of estimated standard errors of difference
C) an assumed mean of zero, in units of estimated standard errors of difference
D) the standard deviation of the population
A) an assumed mean of 50, in units of standard deviations
B) an assumed mean of 100, in units of estimated standard errors of difference
C) an assumed mean of zero, in units of estimated standard errors of difference
D) the standard deviation of the population
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28
When the alternative hypothesis is accepted, then
A) the sample means are assumed to be equal
B) the population means are assumed to be equal
C) chance is rejected
D) a significant difference has been established
A) the sample means are assumed to be equal
B) the population means are assumed to be equal
C) chance is rejected
D) a significant difference has been established
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29
For the t ratio, when the null hypothesis is rejected, then
A) the difference is assumed to be significant
B) the difference is assumed to equal zero
C) the difference is assumed to be positive
D) none of these
A) the difference is assumed to be significant
B) the difference is assumed to equal zero
C) the difference is assumed to be positive
D) none of these
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30
When the degrees of freedom reach infinity, the t distribution
A) becomes identical with the distribution of raw scores
B) gets larger
C) approximates normality
D) cannot be obtained
A) becomes identical with the distribution of raw scores
B) gets larger
C) approximates normality
D) cannot be obtained
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31
For the independent t test, degrees of freedom are based on
A) the population sizes
B) the sample sizes
C) the number of samples being compared
D) none of these
A) the population sizes
B) the sample sizes
C) the number of samples being compared
D) none of these
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32
Like the T score, the t ratio is a measure of
A) individual performance
B) how a single sample performed
C) central tendency
D) none of these, since the T score involves a measure of individual
A) individual performance
B) how a single sample performed
C) central tendency
D) none of these, since the T score involves a measure of individual
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33
The independent t test may be used to evaluate the difference between
A) two sample means
B) two or more sample means
C) the mean and the standard deviation
D) the mean and the variance
A) two sample means
B) two or more sample means
C) the mean and the standard deviation
D) the mean and the variance
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34
The statement that the difference between the two population means is zero, represents
A) the Type 1 error
B) the sampling error
C) the alternative hypothesis
D) the null hypothesis
A) the Type 1 error
B) the sampling error
C) the alternative hypothesis
D) the null hypothesis
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35
For the independent t test, the null hypothesis states that the samples
A) represent a single population
B) represent different populations
C) are of infinite size
D) each have mean scores of zero
A) represent a single population
B) represent different populations
C) are of infinite size
D) each have mean scores of zero
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36
For the independent t test, the null hypothesis is always
A) a function of sample size
B) a function of variability
C) a function of centrality
D) the same as the "chance" hypothesis
A) a function of sample size
B) a function of variability
C) a function of centrality
D) the same as the "chance" hypothesis
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37
When a difference is considered "significant", it indicates that the difference is probably
A) meaningful and profound
B) due to chance and chance alone
C) not due to chance alone
D) none of these
A) meaningful and profound
B) due to chance and chance alone
C) not due to chance alone
D) none of these
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38
For the independent t test, the hypothesis of "no difference" is called the
A) alternative hypothesis
B) null hypothesis
C) central limit hypothesis
D) hypothesis of association
A) alternative hypothesis
B) null hypothesis
C) central limit hypothesis
D) hypothesis of association
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39
When the null hypothesis is rejected, then
A) the "chance" explanation is completely ruled out
B) the "chance" explanation, though not ruled out, becomes improbable
C) the "chance" explanation is fully accepted
D) the "chance" explanation becomes irrelevant
A) the "chance" explanation is completely ruled out
B) the "chance" explanation, though not ruled out, becomes improbable
C) the "chance" explanation is fully accepted
D) the "chance" explanation becomes irrelevant
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40
When a difference is said to be "significant", it means that the difference probably
A) does not exist in the population
B) does exist in the population
C) is no longer related to the population
D) none of these
A) does not exist in the population
B) does exist in the population
C) is no longer related to the population
D) none of these
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41
A powerful test is one that is
A) less likely to commit the Type 2 error
B) more likely to commit the Type 2 error
C) more likely to accept the null hypothesis
D) less likely to detect a population difference
A) less likely to commit the Type 2 error
B) more likely to commit the Type 2 error
C) more likely to accept the null hypothesis
D) less likely to detect a population difference
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42
If the tabled value for t, for a certain number of degrees of freedom, were 3.17, and the calculated value of t were 3.17, then
A) There is a failure to reject Ho
B) Ho is rejected
C) alpha becomes equal to zero
D) the t distribution must be normal
A) There is a failure to reject Ho
B) Ho is rejected
C) alpha becomes equal to zero
D) the t distribution must be normal
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43
The only time a difference between two sample means may be called "significant" is when
A) they are at least 10 points apart
B) they differ by at least .05 points
C) the first mean is larger than the second mean
D) the null hypothesis has been rejected
A) they are at least 10 points apart
B) they differ by at least .05 points
C) the first mean is larger than the second mean
D) the null hypothesis has been rejected
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44
The larger the effect size, the greater the likelihood
A) of ignoring the null hypothesis
B) of rejecting the null hypothesis
C) of committing the Type 2 error
D) that the population means are not significantly different
A) of ignoring the null hypothesis
B) of rejecting the null hypothesis
C) of committing the Type 2 error
D) that the population means are not significantly different
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45
Power can be defined as
A) One plus beta
B) Two plus beta
C) One minus beta
D) One minus alpha
A) One plus beta
B) Two plus beta
C) One minus beta
D) One minus alpha
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46
The alpha level sets the probability for the
A) Type 1 error
B) Type 2 error
C) Type 3 error
D) none of these
A) Type 1 error
B) Type 2 error
C) Type 3 error
D) none of these
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47
The power of a statistical test, such as the independent t test, can be increased by
A) increasing the sample size
B) increasing the alpha error
C) using a one-tail test
D) all of these
A) increasing the sample size
B) increasing the alpha error
C) using a one-tail test
D) all of these
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48
Every degree of freedom value specifies
A) a different t distribution
B) the same t distribution
C) that the t distribution must be assumed to be normal
D) the number of sample groups being compared
A) a different t distribution
B) the same t distribution
C) that the t distribution must be assumed to be normal
D) the number of sample groups being compared
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49
The higher the likelihood of rejecting null when null really should be rejected, then
A) the higher becomes the value of beta
B) the less powerful the statistical test
C) the more powerful the statistical test
D) none of these, since rejecting the null hypothesis is not related to either
A) the higher becomes the value of beta
B) the less powerful the statistical test
C) the more powerful the statistical test
D) none of these, since rejecting the null hypothesis is not related to either
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50
The t distribution assumes normality only when
A) there are infinite degrees of freedom
B) there is a large degree of bias
C) the null hypothesis has been rejected
D) none of these, since the t distribution can never be normal
A) there are infinite degrees of freedom
B) there is a large degree of bias
C) the null hypothesis has been rejected
D) none of these, since the t distribution can never be normal
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51
The sign of the t ratio only becomes important to the statistical decision when
A) null is accepted
B) the degrees of freedom are infinite
C) alpha is set at .05 or less
D) calculating a one-tail t test
A) null is accepted
B) the degrees of freedom are infinite
C) alpha is set at .05 or less
D) calculating a one-tail t test
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52
According to the text, the value beyond which alpha should not be set, is
A) .01
B) .05
C) .50
D) 1.00
A) .01
B) .05
C) .50
D) 1.00
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53
To do a one-tail t test, as opposed to a two-tail,
A) the direction of the difference must always be specified beforehand
B) the direction of the difference need only be specified after null has been rejected
C) the direction of the difference must only be specified when null is accepted
D) the direction of the difference becomes irrelevant
A) the direction of the difference must always be specified beforehand
B) the direction of the difference need only be specified after null has been rejected
C) the direction of the difference must only be specified when null is accepted
D) the direction of the difference becomes irrelevant
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54
The effect size is determined by how much difference there is between the
A) two types of error, Type 1 and Type 2
B) population means in units of population standard deviations
C) population mean and the sample variance
D) sample mean and the population variance
A) two types of error, Type 1 and Type 2
B) population means in units of population standard deviations
C) population mean and the sample variance
D) sample mean and the population variance
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55
With infinite sample sizes, t ratios of +1.96
A) include only the middle-most 68% of all t values
B) include only the middle-most 50% of all t values
C) include only the middle-most 5% of all t values
D) exclude only the most extreme 5% of all t values
A) include only the middle-most 68% of all t values
B) include only the middle-most 50% of all t values
C) include only the middle-most 5% of all t values
D) exclude only the most extreme 5% of all t values
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56
Whenever the alternative hypothesis is written as "mean 1 is greater than mean 2", then
A) a one-tail t test is allowed
B) only a two-tail t test is allowed
C) an independent t test is not allowed
D) sample sizes must be greater than 30
A) a one-tail t test is allowed
B) only a two-tail t test is allowed
C) an independent t test is not allowed
D) sample sizes must be greater than 30
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57
If an independent t ratio is to be calculated for a two-group design, 20 subjects in each group, then the degrees of freedom equal
A) 1
B) .05
C) 40
D) 38
A) 1
B) .05
C) 40
D) 38
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58
The t distributions deviate from normality when
A) the null hypothesis is being tested
B) the alpha is less than .05
C) sample sizes become smaller
D) none of these, since the t distribution never deviates from normality
A) the null hypothesis is being tested
B) the alpha is less than .05
C) sample sizes become smaller
D) none of these, since the t distribution never deviates from normality
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59
Anytime the probability of beta is reduced, then
A) power increases
B) power decreases
C) the likelihood of rejecting null is minimized
D) the likelihood of obtaining a significant difference is minimized
A) power increases
B) power decreases
C) the likelihood of rejecting null is minimized
D) the likelihood of obtaining a significant difference is minimized
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60
With one degree of freedom, a significant t ratio will occur
A) 1% of the time
B) 99% of the time
C) 68% of the time
D) none of these, since degrees of freedom reflect sample sizes not frequency
A) 1% of the time
B) 99% of the time
C) 68% of the time
D) none of these, since degrees of freedom reflect sample sizes not frequency
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61
The distribution of differences is a distribution of sample measures.
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62
When the Levene test results in a significant value, .05 or less, then the variances can be assumed to be equal.
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63
If the Levene test resulted in a significance level greater than .05, then homogeneity of variance can be assumed.
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64
The estimated standard error of difference may never assume a negative value.
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65
The larger the sample sizes, the greater the degrees of freedom.
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66
When all the possible sample pairs have been selected from a single population, the mean of the distribution of differences is expected to approximate zero.
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67
The greater the number of degrees of freedom for the t ratio, the less the likelihood of rejecting the null hypothesis.
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68
With an infinite number of degrees of freedom the t distribution assumes normality.
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69
The mean of the distribution of differences becomes zero only when all sample pairs represent different populations.
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70
The true standard error of difference is equal to the standard deviation of the entire sampling distribution of differences when all the sample pairs in the population have been measured.
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71
The estimated standard error of difference estimates the value of the population mean.
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72
When the direction of the difference between two sample means is not specified, we must use the two-tail t.
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73
When the null hypothesis is rejected, then the alternative hypothesis must be accepted.
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74
When the two sample means are equal, the t ratio will always lead to an accept of the null hypothesis.
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75
The central limit theorem suggests that the entire distribution of differences between pairs of successively drawn sample means will approximate normality.
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76
The t ratio may only be calculated when the data are in ordinal form.
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77
When there is a failure to reject Ho then one may assume that the two sample groups represent a common population.
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78
The assumption of homogeneity of variance can be tested using the Levine Test.
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79
The estimated standard error of difference is an estimate of the variability occurring within the entire distribution of differences.
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80
Student's t test for two independent samples assumes that the variances within each of the two groups are NOT significantly different from each other.
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