Flashcards in 2.1 and 2.2 Deck (19):

1

## Observational Study

### A study in which the investigator observes characteristics of a sample selected from one or more existing populations.

2

## What is the goal of an observational study?

### Draw conclusions about the corresponding population or about differences between two or more populations.

3

## Experiment

### A study in which the investigator observes how a response variable behaves when one or more explanatory variables are manipulated

4

## What is the goal on an experiment?

### To determine the effect of the manipulated explanatory variables on the response variable.

5

## Confounding Variable

### A variable that is related to both how the experimental groups were formed and the response variable of interest.

6

## Selection Bias

### Tendency for samples to differ from the corresponding population as a result of systematic exclusion of some part of the population

7

## Measurement or Response Bias

### Tendency for samples to differ from the corresponding population because the method of observation tend to produce values that differ from the true value.

8

## Nonresponse Bias

### Tendency for samples to differ from the corresponding population because data are not obtained from all individuals selected for inclusion in the sample

9

## Simple Random Sample

### A sample that is selected from a population in a way that ensures that every different possible sample of size n has the same chance of being selected

10

## Sampling without Replacement

### Once an individual from the population is selected for inclusion in the sample, it may not be selected again in the sampling process

11

## Sampling with Replacement

### After an individual from the population is selected for inclusion in the sample and the corresponding data are recorded, the individual is placed back in the population and can be selected again in the sampling process

12

## Stratified Sampling

### Dividing a population into subgroups and then taking a separate random sample from each stratum.

13

## Cluster Sampling

### Dividing a population into subgroups and forming a sample by randomly selecting clusters and including all individuals or objects in the selected clusters in the sample.

14

## Systematic Sampling

###
A value k is specified (for example k = 50 or k = 200).

One of the first k individuals is selected at random.

Then every kth individual in the sequence is included in the sample.

15

## The Educational Testing Service (ETS) needed a sample of colleges. ETS first divided all colleges into groups of similar types (small public, small private, medium public, medium private, large public, and large private). Then they randomly selected 3 colleges from each group.

### Stratified Sampling

16

## A county commissioner wants to survey people in her district to determine their opinions on a particular law up for adoption. She decides to randomly select blocks in her district and then survey all who live on those blocks.

### Cluster Sampling

17

## A local restaurant manager wants to survey customers about the service they receive. Each night the manager randomly chooses a number between 1 & 10. He then gives a survey to that customer, and to every 10th customer after them, to fill it out before they leave.

### Systematic Sampling

18

## Convenience Sampling

### Using an easily available or convenient group to form a sample.

19