Note Card Set 1

Question 1

Variable

Answer 1

A characteristic we measure for each individual or case.

Question 2

Quantitative (Numerical) Variable

Answer 2

Measured on a numerical scale.

Question 3

Categorical Variable

Answer 3

Measured on levels (Low/Medium/High).

Question 4

Discrete Variable

Answer 4

Only specific values, usually integers, are possible.

Question 5

Continuous Variable

Answer 5

Numerical values can be continuous, where all values in the range are possible.

Question 6

Nominal Variable

Answer 6

A categorical variable but the levels don’t have a special type of ordering.

Question 7

Ordinal Variable

Answer 7

A categorical variable but the levels have a
natural ordering.

Question 8

Population

Answer 8

Entire group researchers are interested in.

Question 9

Sample

Answer 9

Represents a subset of the cases and is often a small fraction of the population.

Question 10

Parameter

Answer 10

The overall quantity of interest may be the
mean, median, proportion, or some other
summary of a population.

Question 11

Statistic

Answer 11

Estimated value of a parameter by taking a
sample and computing a numerical summary.

Question 12

Observational Study

Answer 12

Collecting data without interfering with how the data arises.

Question 13

Experiment

Answer 13

Research imposing a treatment to look for
causal relationships between the treatment and the response.

Question 14

Explanatory Variable

Answer 14

For causal relationships (most of the time) first variable (What happens).

Question 15

Response Variable

Answer 15

For causal relationships (most of the time)
second variable (affect or product or what
happened).

Question 16

Treatment Group

Answer 16

A group of subjects that receives a specific
treatment or intervention.

Question 17

Control Group

Answer 17

A group of subjects in an experiment that
does not receive treatment or intervention
and kept separate.

Question 18

Levels

Answer 18

Unit of measurement (High, Medium, Low).

Question 19

Placebo

Answer 19

A seemingly active treatment that contains no active ingredients.

Question 20

Completely Randomized Experiment

Answer 20

A statistical experiment where all subjects or experimental units are assigned to different treatment groups entirely at random.

Question 21

Block Design Experiment

Answer 21

An experimental design where experimental units are grouped into smaller subsets called “Blocks” to control for potential confounding variables that could influence the result, allowing researchers to isolate the effect of the treatment being tested more accurately.

Question 22

Statistical Significance

Answer 22

A result from a stat analysis is unlikely to have occurred by chance, indicating that the observed effect is likely due to real phenomenon rather than random variation.

Question 23

State three principles which help ensure
significance of an experimental study.

Answer 23

Randomization, Replication, and Local
Control.

Question 24

How does direct control of confounding
variables increase the quality of an
experiment?

Answer 24

Ensures the accuracy and validity of study
findings.

Question 25

How does randomization affect the quality of an experiment?

Answer 25

Minimizes selection bias.

Question 26

Why is blinding potentially important for experimental design (particularly when involving humans)?

Answer 26

It prevents bias by stopping participants, researchers,or other study personnel from knowing which treatment group a person is assigned to, making sure the experiment is not influenced by conscious or subconscious expectations about the treatment received, giving more reliable and accurate data.

Question 27

Differentiate between the goals of experimental and observational studies.

Answer 27

Experimental studies aim to establish a causal relationship by actively manipulating variables and introducing interventions while observational studies observe existing relationships between variables without intervention.

Question 28

How are blocking and stratifying analogous? How are they different?

Answer 28

Both involve dividing a population up into smaller more homogenous groups based on certain characteristics. They differ because blocking focuses more on ensuring an equal distribution of treatment assignments in a group, while satisfying aims to ensure that important characteristics are proportionally represented across different groups.

Question 29

Differentiate between stratified random sampling and cluster random sampling.

Answer 29

In stratified random sampling, a population is divided into homogenous subgroups called strata and then a random sample is drawn from that for representation of all groups, while cluster random sampling, the population is divided into groups and a random selection of clusters are chosen.

Question 30

Why can’t observational studies establish causal relationships?

Answer 30

This is due to the lack of ability to manipulate variables.

Question 31

What does it mean for a statistic to be an unbiased estimator?

Answer 31

When the expected value(average of all possible sample values) is equal to the true value of the population parameter it is trying to estimate.