stats module 0

Question 1

what is a census

Answer 1

special sample that includes everyone and “samples” the population

Question 2

issues with census

Answer 2

expensive, undercoverage (might not include everyone), time consuming

Question 3

what are sample statistics

Answer 3

data that is collected from a sample and the summaries

Question 4

two types of inferences

Answer 4

population inference, causal inference (cause and effect)

Question 5

population inference

Answer 5

results from the sample that can be generalized to an entire population

Question 6

causal inference

Answer 6

difference in responses that is caused by the difference in treatments when comparing the results from two treatment groups

Question 7

when should you only make population inferences

Answer 7

when there is random sampling

Question 8

what is randomizing

Answer 8

helps to eliminate the effect of unknown extraneous factors, on average, sample looks like the rest of the population, individuals are selected randomly from population

Question 9

what is non-random sampling

Answer 9

leads to biased results, no way to fix biased sample or salvage useful information, best way to avoid is to sample at random

Question 10

what are the different ways to randomly sample

Answer 10

simple random samples (SRS), stratified random sampling, systematic random sampling, cluster random sampling

Question 11

what is simple random sampling (SRS)

Answer 11

each sample size of n in population has same chance of being selected, samples are drawn at random, generally differ from one another (sampling variability)

Question 12

what is stratified random sampling

Answer 12

population is divided into different homogenous groups (strata), then taken an SRS within each stratum before results are combined, can reduce random sampling and variability)

Question 13

what is systematic random samplign

Answer 13

start from a random selected individual, then sample every kth person, can give representative sample, less expensive than random sampling

Question 14

what is cluster random sampling

Answer 14

splitting the population into similar groups (or clusters), selecting one or a few at random and perform census on them, gives unbiased sample

Question 15

what is bias?

Answer 15

then tendency for a sample to differ from the corresponding population in some systematic way

Question 16

what are the sources of bias

Answer 16

selection bias, response bias, voluntary bias, nonresponse bias

Question 17

what is selection bias

Answer 17

some portion of the population is not sampled at all, or has smaller representation in the sample than in population, usually those are aren’t covered differ from the rest of the population

Question 18

what is response bias

Answer 18

anything within the survey design that influences the responses, respondents may lie

Question 19

what is voluntary bias

Answer 19

occurs when individuals can choose on their own whether to participate in the sample

Question 20

what is nonresponse bias

Answer 20

occurs when a large portion of those sampled failed to respond

Question 21

what are lurking variables

Answer 21

caused when there is no random allocation, variables that are related to both group membership and to the response, could possibly explain the result

Question 22

what are the 2 main types of study design

Answer 22

observational studies and randomized experiments

Question 23

what are observational studies

Answer 23

investigator observes individuals and measured variables of interest, but does NOT attempt to influence responses, can be either retrospective or prospective

Question 24

what is a retrospective study

Answer 24

use of historical data, data collected after the fact

Question 25

what is a prospective study

Answer 25

subjects identified before data is collected, more costly than retrospective but can avoid observational error

Question 26

what is a randomized experiment

Answer 26

study design that allows us to prove a cause-and-effect relationship (causal inferences)