1: Introduction to Stats and Reseach Design

Question 1

anecdotal evidence

Answer 1

based on haphazardly selected individual cases. These cases need not be representative of any larger group of cases (e.g. your young friend Ashley prefers Powerade over Gatorade so that means most young people do)

Question 2

available data

Answer 2

data that were produced in the past for some other purpose but may help answer a present question

Question 3

observational study

Answer 3

we observe individuals and measure variables of interest but do NOT attempt to influence responses (includes sample surveys)

if researchers (or govt, foundations) intervene in the lives of study participants by providing a treatment, but no randomization is done, the experiment is still an observational study

Question 4

experimental study

Answer 4

deliberately impose some treatment on individuals and observe their responses

Question 5

statistical inference

Answer 5

answers specific questions with a known degree of confidence

Question 6

experimental units

Answer 6

individuals on which the experiment is done (humans = subjects)

Question 7

treatment

Answer 7

a specific experimental condition

Question 8

factors

Answer 8

explanatory variables

Question 9

level of a factor

Answer 9

in a study that studies the joint effects of several factors, each treatment is formed by combining a specific value (level) of factors

Question 10

experimental design

Answer 10

refers to choice of treatments and the manner in which the experimental units/subjects are assigned to treatments

Question 11

matched pairs

Answer 11

each subject receives both treatments in a random order OR subjects are matched in pairs as closely as possible and one subject in each pair gets treatment

Question 12

Basic Principles of Experimental Design

Answer 12

1. Compare two or more treatments to control effects of lurking variables. 2. randomize - use impersonal chance to assign experimental units to treatments 3. repeat each treatment on many units to reduce chance variation in results

Question 13

2 reqs of table of random digits

Answer 13

the digit in any position in the list has the same chance of being any one; the digits in different positions are independent in the sense that the value has no influence on the value of any other

Question 14

block

Answer 14

group of experimental units or subjects that are known before the experiment to be similar in some way that is expected to affect the response to the treatments

Question 15

voluntary response sample

Answer 15

consists of people who choose themselves by responding to a general appeal. VRS are biased b/c people w/ strong opinions are mostly likely to respond

Question 16

simple random sample

Answer 16

SRS of size n consists of n individuals from the population chosen so that every set of n individuals has an equal chance to be the sample actually selected

needs a sampling frame.
divide the popln into non-overlapping subsets/strata
do SRS w/i each stratum
combine subsamples into 1 complete sample

Question 17

probability sample

Answer 17

sample chosen by chance. we must know what samples are possible and what prob each possible sample has

Question 18

stratified random sample

Answer 18

first divide popln into groups of similar indivs (strata). choose a separate SRS in each stratum and combine these SRSs to form the full sample

Question 19

multistage sampling design

Answer 19

selects successively smaller groups within the popln in stages, resulting in a sample consisting of clusters of indivs. each stage may employ an SRS, stratified sample, or another type of sample

Question 20

undercoverage

Answer 20

occurs when some popln groups in popln are left out of the process of choosing the sample

Question 21

nonresponse

Answer 21

occurs when an indiv chosen for the sample can’t be contacted or doesn’t cooperate

Question 22

response variable

Answer 22

what we want to explain (usually Y)

Question 23

explanatory variable

Answer 23

candidate explanation (X)

Question 24

lurking variable vs. confounding

Answer 24

lurking variable - a variable that is not among the explanatory or response variables but may influence the response variable

confounding - occurs when 2 variable are associated in such a way that their effects on a response variable can’t be distinguished from e/o

Question 25

popln vs sample

Answer 25

population = entire group of individuals about which we want info

sample - part of popln from which we actually collect info

we collect data from a representative sample to make inferences about a population