Biostats

Question 1

What is the mode?

Answer 1

data point that occurs most frequently

Question 2

What is the mean?

Answer 2

average of all the data points

Question 3

What is the median?

Answer 3

halfway between highest and lowest value

Question 4

What is the range?

Answer 4

distance between highest and lowest value

Question 5

Describe a right skewed distribution and relation to mean, median & mode

Answer 5

Right skewed = tail is to the right, peak to the left

from tail –> peak: mean, median, mode

Question 6

Define incidence

Answer 6

the rate at which new disease occur

Question 7

Define prevalence

Answer 7

total number of cases in a population at any given time

Question 8

Define Precision

Answer 8

data points around 1 point = points in a cluster. Doesnt mean they have to be right, just clustered

Question 9

Define Accuracy

Answer 9

= validity. Are the points in the correct spot? *gold standard tests

Question 10

Define Reliability in terms of tests

Answer 10

can a test outcome be reproduced

Question 11

What % is 1 SD? 2SD? 3SD?

Answer 11

1SD = 68%
2SD = 13.5% more (95% total)
3SD = 2.5% more (99.7% total)

Question 12

If 40,000 students take step3 each year. The mean score is 222 with a SD of 16. How many students scored above 254? explain your answer.

Answer 12

1st how many SD above the mean is 254? (222-254)/SD(16) = 2
2nd what do they want? they want those that scored ABOVE 254 aka those that are 3SD area. 3SD = 2.5% at each tail. we want those at the tippy tippy top. ==> 2.5% of 40,000 = 1,000

Question 13

What is the Standard Error of the Mean(SEM)?

Answer 13

a measure of how tightly grouped data is

Question 14

What does a small Standard Error of the Mean(SEM) tell you?

Answer 14

the data is tightly grouped = more precise.

Question 15

What is a Z-score?

Answer 15

tells you how many SD up or down from the mean the data is.

Question 16

What is the Z-score: Average 240, SD 18. Zscore for 254?

Answer 16

254-240 = 14. 14/18(SD) = 0.78.

Zscore = 0.78

Question 17

What is a confidence interval?

Answer 17

tells you how precise a group of data is. tells you where 95% of the data is located

Question 18

What does it mean if a confidence interval contains 1?

Answer 18

CI contains 1 = data is not reliable, way too spread out = useless =(

Question 19

What is a correlation Coefficient(r)? What does a +r mean? -r? what if r=0?

Answer 19

R = relation between data
R = +  positive correlation
R = - negative correlation
R = 0 no correlation

Question 20

When would you want to use a T-test?

Answer 20

when comparing 2 groups of data

Question 21

When would you want to use ANOVA test?

Answer 21

when comparing 3+ groups of data

Question 22

When would you want to use Chi-Squared test?

Answer 22

when comparing non-numerical data; are these groups related?

Question 23

What is a Randomized Controlled Trial?

Answer 23

RCT = prospective trial

*avoids many forms of bias

Question 24

What is a Cohort Study?

Answer 24

Cohort = follow the fish! ~ observes prospectively over time what happens to a group of patients with certain exposures or underlying illnesses. *used to assess risk

Question 25

What is Relative Risk? Which study type is used to calculate this?

Answer 25

RR = risk of disease based on who was exposed in the past. *cohort studies are used to calculate this

Question 26

What is a Case Control Study? Whats the bias?

Answer 26

CCS = retrospective studies looking for the odds of a previous exposure on the development of a rare disease manifestation. (taking ppl with disease and looking for exposures) Bias = subject to recall bias

Question 27

What is an Odds Ratio?

Answer 27

OR = those who have a disease and looking at the chance of exposure. ==> (case exposured/cases not exposed)/(control exposed/controls not exposed)

Question 28

What is Berkson Bias? How can you solve this?

Answer 28

hospitalized patient are used as trial subjects instead of the general population resulting in different results from the general population. solution: random selection of trail subjects

Question 29

What is the Hawthorn Effect? How can you combat this?

Answer 29

those being studied know they are being studied and change their behavior. solution: using a placebo and blinding both the investigator and the participants.

Question 30

What is lead time bias?

Answer 30

early detection is confused with increased survival

Question 31

What does it mean if a P = 0.05?

Answer 31

there is a 95% chance the ALTERNATE hypothesis is true(reject null)

Question 32

What does it mean if a P <0.05

Answer 32

Null hypothesis is rejected

Question 33

What does it mean if a P > 0.05

Answer 33

accept null

Question 34

What is a type 1 error?

Answer 34

false positive

Question 35

What is a type 2 error?

Answer 35

false negative

Question 36

What is sensitivity? How do you calculate this?

Answer 36

the likelihood a test will detect all the ppl with the disease. TP/(TP + FN) = sensitivity

Question 37

What is specificity? How do you calculate this?

Answer 37

the likelihhood that ppl without a disease are correctly identified as disease negative TN/(TN+FP) = specificity

Question 38

What is NPV? How do you calculate this?

Answer 38

If the test is negative, what is the likelihood you really dnt have the disease? TN/(TN+FN) = NPV

Question 39

What is PPV? How do you calculate this?

Answer 39

If the test is positive what is the likelihood you really do have the disease? TP/(TP+FP) = PPV

Question 40

What is Absolute Risk Reduction(ARR)?

Answer 40

% decrease in the risk of death or disease from a treatment compared to 100% of ppl in a population ex: 3% no tx vs 2 % with tx arr=1%

Question 41

What is Number Needed to Treat(NNT)? How do you calculate this?

Answer 41

NNT = 1/ARR ~number of ppl you have to treat to save 1 life

Question 42

What is the Number Needed to Harm(NNH)? How do you calculate this?

Answer 42

NNH = number of ppl you have to treat to harm 1 person. NNH = 1/Absolute Risk Absolute Risk = incidence w/exposure - incidence without exposure

Question 43

How do you calculate Absolute Risk?

Answer 43

Incidence with exposure - incidence without exposure