Biostatistics

Question 0

alpha

Answer 0

cutoff point of 0.05, aka significance level

Question 1

p < .05

Answer 1

reject the null hypothesis, meaning there is an alternative hypothesis for the results

“statistically significant”

Question 2

p > .05

Answer 2

accept the null hypothesis because random error likely explains discrepancy in data

Question 3

Type I (alpha) error

Answer 3

incorrect rejection of a null hypothesis

Question 4

Type II (beta) error

Answer 4

incorrect failure to reject a false null hypothesis
or
Ha is true, but we do not reject null

Question 5

Power (statistical)

Answer 5

ability of a study design and its methodology to detect a true difference if one truly exists (level of accuracy in correctly accepting/rejecting the Null Hypothesis)

Question 6

sample size

Answer 6

the larger the sample size, the greater the likelihood of detecting a difference if on exists (Inc in power)

Question 7

What are the 3 key attributes of data

Answer 7

magnitude, consistency of scale, rational zero

Question 8

1 SD around the mean %

Answer 8

68%

Question 9

2 SD around the mean %

Answer 9

95%

Question 10

3 SD around the mean %

Answer 10

99%

Question 11

Positively skewed

Answer 11

right side tail longer
mean > median
skewed to the right

Question 12

Negative skewed

Answer 12

Left tail longer
mean < median
skewed left

Question 13

Interpretation of an a priori p value

Answer 13

the probability of making a type 1 error if the null hypothesis is rejected

Question 14

Interpretation of an a priori p value

2nd definition

Answer 14

The probability of erroneously claiming a difference between groups when one does not really exist

Question 15

Interpretation of a 95% CI

Answer 15

We are 95% confident that the “true” difference between the groups is contained within the confidence interval range