1. The t pdf has a mean value of:
a. 0
a. 1
b. 2
c. 3
d. 4
2. The one sample 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 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
3. The one sample t statistic, is suitable in the following situation:
a. Comparison of a sample mean to that of a population mean
b. Comparison of a sample proportion to that of a population proportion
c. Comparison of a sample mean to that of a population one, where the sampling distribution is exponential
d. Comparison of a sample distribution to that of a population
e. Comparison of a sample mean to that of a population one over a time period
4. The one sample t statistic, has a degrees of freedom equal to:
a. Number of observations in sample plus one
b. Number of observations in sample
c. Number of observations in sample minus one
d. Number of observations in sample minus two
e. Number of observations in sample minus three
5. The p value associated with the one sample t statistic, assumes the following:
a. Mean of sample is not equal to the comparator
b. Mean of sample less than that of the comparator
c. Mean of sample greater than that of the comparator
d. Mean of sample and comparator are identical
e. None of the above
6. The effect size measure (i.e. clinical importance measure) associated with the one sample t statistic, is calculated as:
a. (sample mean – population mean)/standard error
b. (sample mean – population mean)/standard deviation
c. (sample mean – population mean)/number in sample
d. (sample mean – population mean)/sample mean
e. (sample mean – population mean)/1
7. The effect size measure (i.e. clinical importance measure) associated with the one sample t statistic, provides:
a. The difference between the hypothesised and observed 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 the hypothesised and observed mean
8. The paired sample t statistic, is suitable in the following situation:
a. Comparison of a sample proportion to that of a population proportion of 0.5
b. Comparison of a sample mean to that of a population one, where the sampling distribution is exponential
c. Comparison of a sample distribution to that of a population
d. Comparison of a sample mean of zero to that of a population one over a time period
e. Comparison of a sample mean to that of a population mean of zero
9. If we obtained a p-value of 0.034 (n= 13, two tailed) from a paired sample t statistic, how would we initially interpret this outside of the decision rule approach (i.e. hypothesis testing):
a. We will obtain the same t value from a random sample of 13 observations 34 times in every thousand on average, given that the population mean is zero.
b. We will obtain the same t value from a random sample of 13 observations 34 times, or more in every thousand on average, given that the population mean is zero.
c. We will obtain the same of a more extreme t value from a random sample of 13 observations 34 times in every thousand on average.
d. We will obtain the same or a more extreme t value from a random sample of 13 observations 34 times in every thousand on average, given that the population mean is zero.
e. We are 0.966 (i.e. 1-.034) sure that the null hypothesis is true.
10. If interval/ratio data are paired in a research design such as pre and post test a paired sample t statistic . . :
a. Is the most appropriate test, regardless of the differences being normally distributed
b. Is the most appropriate test, if the differences are normally distributed
c. Is the most appropriate test, if the differences are NOT normally distributed
d. Is sometimes the appropriate test, if the differences are normally distributed and centred around zero
e. Is the least appropriate test, regardless of the differences being normally distributed
11. A p value is a special type of probability with two fundamental characteristics what are they . . :
a) Conditional probability, range of values representing area(s) under PDF curve
b) Conditional probability, of a specific single value representing a x value along the PDF curve
c) Non-conditional probability, range of values representing area(s) under PDF curve
d) Conditional probability, always representing a single area under PDF curve
e) Non-conditional probability, representing a x value along the PDF curve
12. The conditional probability for a p value, is usually re-interpreted as . . :
a. Parameter value = zero = specific alternative hypothesis
b. Parameter value = zero = alternative hypothesis
c. Parameter value = zero = null hypothesis
d. Parameter value = zero = not related to any hypothesis
e. Parameter value not equal to zero = probability of the null hypothesis being true
13. Before calculating a single sample or paired sample t statistic it is essential to . . :
a. Perform graphical statistics. Review study design.
b. Perform descriptive/graphical statistics to assess assumptions. Review study design.
c. Not perform descriptive/graphical statistics to assess assumptions. Review study design.
d. Assess the difference between the mean and median. Review study design.
e. Not perform description statistics to assess assumptions nor review study design.
