sampling and survey designs

Question 1

population of interest

Answer 1

set of all individuals/units we seek to study

Question 2

sample frame

Answer 2

sampling frame is a list of units from which the sample is chosen. ideally, it includes the whole population

Question 3

unit

Answer 3

individual person, item or measurement

Question 4

strata

Answer 4

• subset (part) of the population divides population into strata

Question 5

statistic

Answer 5

• describes a sample

Question 6

parameter

Answer 6

• describes an entire population

Question 7

simple random sampling

Answer 7

Simple random sampling is used to make statistical inferences about a population. It helps ensure high internal validity: randomization is the best method to reduce the impact of potential confounding variables

each possible group of a chosen size from the population has an equal chance to be selected

from population -> (randomly selected) (unbiased sample)
(best method to represent a population from a sample)

Question 8

stratified sampling

Answer 8

stratified sampling is appropriate when you want to ensure that specific characteristics are proportionally represented in the sample. You split your population into strata (for example, divided by gender or race), and then randomly select from each of these subgroups

population is subdivided into 2+ groups based on pre-existing characteristics, then only a few are selected from each grouping to be sampled

Question 9

cluster sampling

Answer 9

cluster sampling is appropriate when you are unable to sample from the entire population. You divide the sample into clusters that approximately reflect the whole population, and then choose your sample from a random selection of these clusters and collect data from every unit in the sample (census)

could lead to (bias sample)

Question 10

systematic sampling

Answer 10

systematic sampling involves choosing your sample based on a regular interval, rather than a fully random selection. It can also be used when you don’t have a complete list of the population

a unit is selected as the starting point and more units are chosen for sampling at a constant interval (k), from the starting point (ex, 1, 5, 9, 13)

Question 11

convenience sampling

Answer 11

where the sample is “convenient to take”, like from friends or family, workplace (easy to reach)

ex) standing at a mall or a grocery store and asking people to answer questions

Question 12

response variable

Answer 12

measures outcome of interest

Question 13

observational study

Answer 13

individuals are observed or certain outcomes are measured, no attempt to affect response variable/outcome (ex, no treatment given, surveys)

Question 14

experimental study

Answer 14

manipulates the explanatory variables with the intent to influence the response variable

Question 15

treatment

Answer 15

any specific experimental condition(s) applied to individuals/objects

Question 16

completely randomized design

Answer 16

units from sample are randomly assigned to treatments

Question 17

randomized block design

Answer 17

units from sample are subdivided into ‘blocks’ based on pre-existing characteristic(s), then randomly assigned from blocks to a treatment

Question 18

matched pair design

Answer 18

2 units are matched and paired based on similarity of characteristics, then randomly assigned treatments which the pair’s responses are compared

Question 19

repeated measures design

Answer 19

each unit is assigned to all treatments usually in random order

Question 20

confounding variable

Answer 20

• a confounder variable influences both the dependent variable and independent variable
  ex) ice cream sales (dependent variable) and relationship of sun burns (independent variable)

sun exposure (confounding variable) is the reason why the dependent and independent variables show a relationship

Question 21

replication

Answer 21

• have more than one individual/unit in each treatment group to reduce chance variation in the results

Question 22

randomization

Answer 22

• random assignment of individuals/units to treatments, or the order of treatments

Question 23

concerns with experimental studies

Answer 23

• confounding variables: use randomization to control
• interacting variables: measure and report variables that may interact
  ex) condiment on food
• placebo, hawthorne and experimenter effects: use double-blind design and placebo/control groups
• ecological validity and generalization: try to perform experiment in natural setting

Question 24

experimenter effect

Answer 24

• observer-expectancy effect
• the observer expects or knows history of the experiment