True or False: 1. If higher levels of one variable are associated with higher le

Question

True or False:

1. If higher levels of one variable are associated with higher levels of another variable, then these variables are said to be positively correlated.

2. McNemar’s test is used for paired data in 2x2 contingency tables

3. If a p-value =.95, we can be 95% confident there is no difference between the groups.

4. Permutation tests are good for testing differences between groups when you don’t want to make assumptions about the shape of the distributions.

5. The standard error measures the variability in the individual data, while the standard deviation estimates the variability in the sample mean or treatment estimate.

6. A chi-square test is only appropriate if the expected counts in each cell of a table are greater than 5.

7. An outlier can cause more problems in a t-test than in a rank test.

8. If the null hypothesis is true, and you do a statistical test and get a p-value that is smaller than your alpha-level, you will reject the null hypothesis and make a type-2 error.

9. The width of a confidence interval increases as the sample size increases.

10. if a screening test has 90% sensitivity and 80% specificity, then 90% of people with disease will test positive.

11. If the sensitivity of a screening test is 95% and the disease is very rare, then the probability you have disease given that you got a positive test will also be close to 95%.

12. A confidence interval for a single mean gives a range of plausible values for that mean, while a population prediction interval gives a range of plausible values for a randomly chosen individual from the population.

13. If a 95% confidence interval for a difference in mean blood pressure between treatment and placebo groups is (.68, 1.3) then a 2-tailed test at =.05 would reject the null hypothesis that the groups are the same.

14. A correlation of 1 means the values for the two variables are exactly the same.

15. If you are comparing two groups with respect to 20 different variables, and do not adjust for the number of comparisons you are making, you will have a probability of making a type-I error that is larger than alpha=.05.

Explanation / Answer

1. True. Because if one variable shows increment and simultaneously another variable shows incremenet with increasing value of the first then they are positively correlated.

2. True.McNemar’s test is used on paired nominal data to examine whether the frequencies rowwise and columnwise are same.

3. False. p-value=0.95 means that there is 95% chance of obtaining a value of test statistic which is same or more extreme than the actually observed one.

4.True. Permutation tests are a particular type of significance test where the distribution of test statistics under null hypothesis is computed by rearrangements of labels on observed data points. So here we do not assume anything about the distribution rather we compute it.

5.False. Rather the statementshould be reversed. The standard error is computed for statistics like mean etc, and measures their variability. However, the standard deviation is computed for the whole data set and measures the variability of the whole dataset.

6.True. Otherwise degrees of freedom will reduce to zero thus providing a menaingless test.

7.True. The higher presence of outliers increases the sample variation and therefore reduces the t-statistic. Hence it reduces the chance of rejecting null hypothesis.

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