# Experimental Design Flashcards Preview

## PS3021 Stats > Experimental Design > Flashcards

Flashcards in Experimental Design Deck (23)
1
Q

What a should a sample be?

A

A representative sub-set of the concrete (study) population.

2
Q

What is the problem with using WEIRD participants in studies?

A

Some basic and complex processes differ in people from different backgrounds, so inference from a study is limited.

3
Q

Define sampling bias.

A

When a sample is not representative due to a systematic aspect of the sampling method.

4
Q

Define sample aliasing.

A

When a sample is not representative due to the interval/point in the data that was selected.

5
Q

Give 2 reasons self-selected/volunteer sampling could create a bias.

A

People may go for the payment and people may go out of interest (WEIRD).

6
Q

Give a reason snowball sampling could create a bias.

A

It entirely depends on the first contact and who they represent.

7
Q

Give 2 strengths of snowball sampling.

A

Good for initial ideas and effective for sensitive information/populations.

8
Q

Give a reason for and against cluster sampling over simple random sampling.

A

For: less expensive.
Against: more error.

9
Q

Describe systematic stratified sampling.

A

Lists set up using stratification, order in each list randomised, systematically choose entries in each list.

10
Q

In what type of studies is non-random sampling most often used?

A

Experimental.

11
Q

Define internal validity.

A

Can the statistical and/or causal conclusions be believed?

12
Q

Define external validity.

A

Can the conclusions be generalised?

13
Q

Why are internal and external validity sometimes in opposition?

A

Because internal validity required tighter control but this can decrease external validity.

14
Q

What are secondary dependent variables?

A

Simple secondary measures that may be affected by/as well as the initial DV.

15
Q

Give 2 ways you can maximise the chance of detecting effects of IV.

A

Setting high/low values of IV (but not too extreme) and using the minimum number of values for each IV.

16
Q

Describe error about a participants true value.

A

The trial or mean of trials may not he representative of the participant.

17
Q

Vaguely, what are the 4 things we observe on each trial of an experiment?

A

Population mean, participant noise, trial noise and other factors.

18
Q

How do we reduce participant noise?

A

By increasing n participants.

19
Q

How do we reduce trial noise?

A

By increasing n trials each participant does.

20
Q

How can we calculate how much data we need and why should we do this?

A

We can use “power analysis” because we should only get enough data to answer our questions and no more and because collecting data costs time, effort and money.

21
Q

When should we account for blocked control variables?

A

Only when we are sure that they matter (to avoid reducing chance of detecting effects needlessly).

22
Q

Give the term for changes in performance because someone is aware they are participating in a study.

A

Reactivity.

23
Q

Briefly describe the Neyman-Pearson lemma.

A

One of the null and alternate hypotheses must be true.