1. The two independent samples t statistic, according to Norman and Streiner (2009) can be interpreted as:
a. (Observed difference in means)/(pooled standard deviation) = signal/noise
b. (Observed difference in means)/(expected variability in means due to random sampling) = noise/signal
c. (Observed difference in means)/(expected variability in means due to random sampling) = signal/noise
d. (Observed treatment mean)/(expected variability in means due to random sampling) = noise/signal
e. (Observed difference in medians)/(expected variability in medians due to random sampling) = signal/noise
2. The two independent samples t statistic, makes an additional assumption, compared to that of the one sample/paired t statistic, that is assessed by Levenes statistic what is this:
a. Variances of both samples is due to random sampling
b. Variances of both samples is due to sampling bias
c. Variances of both samples is due to sample size
d. Variances of both samples is significantly different
e. Means of both samples is due to random sampling
3. The sampling distribution of Levenes statistic follows a particular theoretical distribution which of the following is it?
a. Standard normal
b. t
c. F
d. Chi square
e. Exponential
4. Traditionally, when evaluating a null hypothesis one makes use of a critical value. A critical value . is. .?
a. a value set by the computer to create a decision rule regarding acceptance/rejection of the null hypothesis
b. a value you set to create a decision rule regarding effect size
c. a value set by the computer to create a decision rule regarding acceptance/rejection of the null hypothesis
d. a value you set to create a confidence interval regarding acceptance/rejection of the null hypothesis
e. a value you set to create a decision rule regarding acceptance/rejection of the null hypothesis
5. Traditionally a critical value is set at one of the following. . .?
a. 0.05, 0.01, 0.00001
b. 0.05, 0.01, 0.001
c. 0.5, 0.1, 0.001
d. 0.5, 0.01, 0.001
e. 0.005, 0.001, 0.005
6. The two independent sample t statistic, is suitable in the following situation:
a. Comparison of two independent sample means where the samples are <30
b. Comparison of two independent sample means where the samples are >30 or normally distributed
c. Comparison of two independent sample means where the samples are exponentially distributed
d. Comparison of a sample distribution to that of a independent population
e. Comparison of a specified mean to that of a population one over a time period
7. The two independent samples t statistic, has a degrees of freedom equal to:
a. Number of observations in both samples plus one
b. Number of observations in both samples
c. Number of observations in both samples minus one
d. Number of observations in both samples minus two
e. Number of observations in both samples minus three
8. The p-value (two sided) associated with the two independent samples t statistic, assumes the following:
a. Mean of samples identical
b. Mean of sample one is not equal to that of sample two
c. Mean of sample one is less than that of sample two
d. Mean of sample one is greater than that of sample two
e. None of the above
9. Given that s1 = sample one and s2 = sample 2. The effect size measure (i.e. clinical importance measure) associated with the two independent samples t statistic, is calculated as:
a. (s1 mean – s2 mean)/standard error
b. (s1 mean – s2 mean)/standard deviation
c. (s1 mean – s2 mean)/number in sample
d. (s1 mean – s2 mean)/sample mean
e. (s1 mean – s2 mean)/1
10. Given that s1 = sample one and s2 = sample 2. The effect size measure (i.e. clinical importance measure) associated with two independent samples t statistic, provides:
a. The difference between s1 mean and s2 mean
b. The probability of obtaining the observed difference in means
c. The probability of obtaining the effect size observed
d. The probability of the null hypothesis being true
e. A standardised measure of the difference between s1 mean and s2 mean
11. The two independent samples t statistic, is suitable in the following situation:
a. Comparison of a sample mean to that of a population mean of zero
b. Comparison of more than two sample means
c. Comparison of a sample mean to that of another sample mean
d. Comparison of a sample distribution to that of a population
e. Comparison of two sample means to that of zero
12. If we obtained a p-value of 0.034 (n=7,8, two tailed) from an independent samples t statistic, how would we initially interpret this outside of the decision rule (i.e. hypothesis testing) approach:
a. We will obtain the same t value from two independent random samples of the specified size 34 times in every thousand on average, given that both samples come from a population with the same mean.
b. We will obtain the same, or a more extreme, t value from two independent random samples of the specified size 34 times in every thousand on average.
c. We will obtain the same or a more extreme t value from a single random sample of the specified size 34 times, or more in every thousand on average, given that both samples come from a population with the same mean.
d. We are 0.966 (i.e. 1-.034) sure that the null hypothesis is true.
e. We will obtain the same, or a more extreme t value from two independent random samples of the specified size 34 times in every thousand on average, given that both samples come from a population with the same mean.
13. If two independent samples (with both less than 30 observations) of interval/ratio data are produced in a research design an independent samples t statistic . . :
a. Is the most appropriate test, regardless of the scores being normally distributed or not
b. Is the most appropriate test, if the scores are normally distributed
c. Is the most appropriate test, if the scores are NOT normally distributed
d. Is sometimes the appropriate test, if the scores are normally distributed and centred around zero
e. Is the least appropriate test, regardless of the scores being normally distributed
