Stats Chapter 6

observational study

observes individuals and measures variables of interest but does not attempt to influence the responses. The purpose of an observational study is to describe and compare existing groups or situations

experiment

deliberately imposes some treatment on individuals in order to record their responses. The purpose of an experiment is to study whether the treatment causes a change in the response

cofounded

Two variables (either explanatory variables or lurking variables) are confounded when their effects on a response variable cannot be distinguished from each other

population

in a statistical study is the entire group of individuals (not necessarily people) about which we want information

sample

is the part of the population from which we actually collect information. We use a sample to draw conclusions about the entire population

sampling design

describes exactly how a sample is chosen from the population

inference

we infer information about the population from what we know about the sample

bias

The design of a statistical study is biased if it systematically favors certain outcomes

convenience sample

often produces unrepresentative data

a shopping mall sample will almost surely overrepresent middle-class and retired people and underrepresent the poor. This pattern will recur almost every time we take such a sample. That is, the source of bias is a systematic error caused by a bad sampling design, not just bad luck on one sample. The outcomes of shopping mall surveys will repeatedly miss the truth about the population in the same ways

voluntary response sample

(also called volunteer or self-selected sample), lets individuals choose whether to participate in the study

They are not scientific polls. Instead, these types of samples are biased because people with strong opinions are most likely to respond. The problem is that people who take the trouble to respond to an open invitation are usually not representative of any clearly defined population. Voluntary response samples may also allow individuals to submit any number of entries, further exacerbating the potential for bias

simple random samples

A sample chosen by chance allows for neither favoritism by the sampler nor self-selection by respondents

size 𝑛 consists of 𝑛 individuals from the population chosen in such a way that every set of 𝑛 individuals has an equal chance to be the sample actually selected

table of random digits

stratified random sample

to sample distinct groups within the population separately, and then to combine these samples

multistage samples

Nationwide or statewide governmental surveys use often - practicality

cross-sectional studies

Observational studies that collect data about a population at one point in time

Undercoverage

aka coverage bias

is a form of selection bias that occurs when some groups in the target population are left out of the process of selecting the sample

case-control observational study

case-subjects are selected based on a defined outcome, and a control group of subjects is selected separately to serve as a baseline with which the case group is compared

retrospective approach

Looking back into the past

Cohort

studies enlist a homogeneous group of fairly similar individuals and keep track of them over a long period of time

prospective

studies that record, at regular intervals, all sorts of new relevant information about the study participants

longitudinal

Observational studies that monitor a sample of individuals repeatedly over time are sometimes