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Flashcards in Biostatistics Deck (31)
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1

Continuous data

data with numeric values
-age, weight, height, A1c, etc

2

Categorical data

data with categorical values
-gender, race, exposure/disease status

3

Normal Distribution

symmetrical around the mean, bell shaped

4

normal distribution: -1σ to +1σ

68%

5

normal distribution: -2σ to +2σ

95%

6

normal distribution: -3σ to +3σ

99.7%

7

Bimodal distribution

suggestive of two different population

8

right skewed distribution

mode

9

left skewed distribution

mean>median>mode

10

Descriptive statistics for continuous data

measures of central tendency: mean, median, mode

measures of dispersion: variance, SD

graphic representation: histogram, box plot, line graph

11

Descriptive statistics for categorical data

frequency

proportion: rate, ration, prevalence, incidence rate, relative risk, odds ratio, sensitivity, specificity

graphic: pie chart, bar graph

12

Measures of central tendency

Mean: sum of values/total # of values

Median: value in middle of a ranked data

Mode: value that occurs most often

13

Measures of dispersion

Variance: (sum of square of deviance from mean) divided by (total number of variable - 1)

SD: square root of variance

Standard error of mean: SD / (square root of total number of values)

14

Inferential statistics

to make an inference for a population group from a sample group

15

Population group

complete collection to be studied

16

Sample group

Part of the population of interest selected for study

17

Goal of Statistical Hypothesis Testing (SHT)

make decisions about a population from a sample

18

Procedure of SHT

1. state null hypothesis
2. state alternative hypothesis
3 select level of significance
4. collect and summarize the sample data into a statistic
5. refer to a criterion for evaluating the sample evidence producing p-value
6. make a decision to reject/retrain null hypothesis based on p-value

19

Significance level

standard defined by probability of rejecting a true null hypothesis (false positive)

20

P value

quantifies how consistent your sample statistics are with the null hypothesis

21

high p value

same results are consistent with null hypothesis that is true

22

low p value

your sample results are not consistent with a null hypothesis which is true

23

Type I error

false positive

24

Type II error

false negative

25

Power

true positive

26

confidence interval

quantifies the uncertainty in the estimates

the narrower interval implies higher precision with less variability

the wider interval implies lower precision with increased coverage

27

If CI contains a null value

it fails to reject null hypothesis

28

If CI does not contain null value

it rejects the null hypothesis

29

Student's t-test

compares means of 2 independent groups

30

ANOVA

compare means of 3 or more independent groups