A New View of Statistics Go to: Previous · Contents · Search · Home

QUIZ

Each question has either only one correct answer or one incorrect answer. The answers appear in the lower frame when you click on answer. Links to the appropriate sections of the text are also included.

1. A frequency distribution can be shown as

• a statistic
• a histogram
• a scatter plot
• a stem and leaf plot

2. Simple statistics are

• for simpletons
• presented in stem and leaf plots
• things like correlations
• things like standard deviations

3. What would you do with a median?

• Use it do show spread.
• Use it for normally distributed data.
• Cross it against oncoming traffic
• Indicate the middle of some data.

4. The following are measures of spread:

• standard deviation
• root mean square errors
• percentile ranges
• polyunsaturated margarine

5. Which arrow indicates the standard error of the estimate?

6. A relative risk is

• a risk of matrimony
• an outcome statistic
• a relative of the odds ratio
• a relative frequency

7. Differences between means are best thought about in terms of

8. Dimension reduction

• describes loss of precision.
• describes factor analysis.
• is an example of ANOVA.
• is a weight-loss program.

9. Concerning reliability:

• It impacts most on descriptive studies.
• It can be expressed as an ICC.
• It can be expressed as a CV.
• It is quantified by 2-way ANOVA.

10. Concerning validity:

• It impacts most on descriptive studies.
• It is the correlation between true and observed values.
• A valid measure must be reliable.
• A reliable measure must be valid.

11. Correct or incorrect expressions?

12. Confidence intervals...

• are a new form of sprint training.
• are calculated routinely by most stats packages.
• define the likely range of a population value.
• are inferior to p values for indicating magnitude of outcomes.
answer · Confidence Intervals · What is a P Value?

13. A correlation coefficient and its confidence interval are shown in the figure.

We can conclude that:

14. Concerning tests and test statistics:

• One-tailed tests are sometimes justified.
• Test statistics should always be shown.
• Chi-squared is a common test statistic.
• P = 0.06 means there is no effect.
answer · What is a P Value? · Using P Values

15. Many samples, each of 100 observations, are drawn from a population in which there is a correlation of 0.70 between two variables. How often would you expect to find a statistically significant correlation?

• hardly ever
• about one time in 100
• about one time in 20
• almost always.

16. What are appropriate comments about these data, which show mean weekly training durations for three groups of athletes? (Bars are SDs.)

17. An outcome measured on a five-point scale (not at all to always)...

• is an example of an ordinal variable.
• has a behavior problem when it comes to residuals.
• should be analyzed by logistic regression.
• can be analyzed by ANOVA.

18. Log transform a variable...

• if the values are too big.
• if the residuals (error) get bigger for bigger values of the variable.
• if you don't get statistical significance.
• if non-parametric tests are inappropriate.
answer · Log Transformation · Non-Parametric Models

19. Non-parametric tests usually...

• are parametric tests in disguise..
• involve rank transformation of the dependent variable.
• work for grossly non-normal data..
• should be attempted if parametric tests give p > 0.05.

20. If we studied the effect of gender and body mass on sprint performance time, we would use the following model:

21. Concerning multiple linear regression:

• Use it to fit curves as well as straight lines.
• Use it to control for the effect of numeric variables.
• It gives misleading results for highly correlated independent variables.
• Use it to fit multiple straight lines with several groups.

22. Repeated-measures models...

23. In a longitudinal study aimed at enhancing sport enjoyment, the following results were obtained

We can conclude that:

• Initial randomization to the two groups was poor.
• There is one between- and one within-subject factor.
• The time effect in the model is substantial.
• The time effect in the model is significant.

24. Concerning sample sizes for a controlled longitudinal study:

• Sample size is proportional to (1 - r), where r = reliability correlation.
• Controlled studies need 4x as many subjects as uncontrolled studies.
• Get sample size "on the fly" by testing until you get an acceptable confidence interval.
• None of the above.
answer · What Determines Sample Size · Sample Size "On the Fly"

25. The size of a sample needed for a cross-sectional study...

• depends on the size of your research grant.
• is inversely proportional to the square of the validities of your measures.
• is a function of the largest effect you want to detect.
• depends on how many student researchers you have on the project.
answer · The Right Number of Subjects · What Determines Sample Size

26. When you come home from climbing in the statistical mountains, you will tell the folks, amongst other things, that...

• from now on you will show as few numbers as possible.
• statistical modeling is no substitute for knowing your data.
• it's important to play with stats programs.
• from now on you will test rather that estimate.