Descriptive Stats

Question 1

Descriptive stats vs. inferential stats

Answer 1

D: describe, organize, or summarize data
I: generalize from sample of data to larger groups of subjects using inductive reasoning

Question 2

Population vs. sample

Answer 2

Pop: largest collection of entities about which an investigator wishes to draw conclusions
Sample: subset of population actually being studied

Question 3

Probability sample

Answer 3

Investigator can specify chance of subject being selected

Question 4

4 types of probability samples

Answer 4

simple random
stratified random
cluster
systematic

Question 5

simple random sample

Answer 5

all members of pop have equal chance to be selected; “representative” if resembles source population

Question 6

stratified random sample

Answer 6

population divided into groups with shared characteristics, random samples from each group; may be more representative of population

Question 7

cluster samples

Answer 7

ex: randomly select 5 schools then randomly select equal # students from each
used when too expensive/ labor intensive to use other methods

Question 8

systematic samples

Answer 8

systematic selection of subjects, e.g. every 5th pt admitted to hospital
may be = simple random without randomization but may be prone to selection bias if systematic error involved

Question 9

stratified vs. cluster sampling

Answer 9

strata are homogenous, then members of strata are randomly selected
clusters are heterogenous “natural groupings” and are selected at random

Question 10

probability addition rule

Answer 10

prob (Ex or Ey) = prob(Ex) + prob(Ey)

Question 11

probability multiplication rule

Answer 11

prob (Ex and Ey) = prob(Ex)*prob(Ey)

*assuming events are independent of each other

Question 12

probability binomial distribution

Answer 12

probability that specific combos of 2 mutually exclusive independent events will occur

Question 13

4 types of variables

Answer 13

nominal
ordinal
interval
ratio

Question 14

nominal variables

Answer 14

“categorical”
names or labels with no inherent order, e.g. race and gender
*includes dichotomous/ binomial data

Question 15

ordinal variables

Answer 15

“ranked”

natural order exists but not evenly spaced, e.g. cancer grade, pain score, scale from best to worst

Question 16

interval variables

Answer 16

space between adjacent scale values are equal, but no absolute 0, e.g. temperature in C; ratios cannot be computed (100* C =/= (2 x 50* C)

Question 17

ratio variables

Answer 17

true zero is absence of variables, and ratios can be calculated; e.g. annual income, BP, Kelvin temperature

Question 18

discrete variable

Answer 18

takes only certain limited values, no in-between; e.g. race, gender, # of anything

Question 19

continuous variables

Answer 19

may take any value though may have limited range; e.g. weight, age, BP

Question 20

dependent variable

Answer 20

outcome of interest in study that is expected to change based on intervention

Question 21

independent variable

Answer 21

intervention, exposure, or factor that may influence dependent variable

Question 22

3 ways to summarize data

Answer 22

frequency distribution
measures of central tendency
measures of dispersion

Question 23

frequency distribution

Answer 23

data points within certain categories = frequency -> percent/ relative frequency vs. all data points

Question 24

measures of central tendency

Answer 24

mean, median, mode

Question 25

measures of dispersion/ spread/ variation

Answer 25

range (max and min), interquartile range, variance, SD, variation coefficient

Question 26

variance equation

Answer 26

s^2 = (sum[{xi-xbar}^2]) / (n-1)

xi - xbar = deviation score

Question 27

coefficient of variation equation

Answer 27

SD / mean

Question 28

percent of population within 1, 2, and 3 SDs of mean

Answer 28

1: ~68%
2: ~95%
3: ~99.7%

Question 29

left/negative skew and right/positive skew

Answer 29

normal curve: mode = mean = median

left: mean

Question 30

what is z-score

Answer 30

indicates how many SDs an element is from the mean in a normal distribution

Question 31

z-score equation

Answer 31

z = (X - u)/ sigma
X = sample statistic/ estimate
u = mean
sigma = SD

Question 32

z-score and directionality

Answer 32

in a two-sided z-score table, positive value is for values to left of mean
for right side, use 1 - z-score