W1 - Experimental Design & Inferential Stats

Question 1

Methods of controlling secondary variables include (5)

Answer 1

Elimination, constancy, making a second variable into an independent variable, randomisation, statistical adjustment

Question 2

An example of elimination is

Answer 2

Using a soundproof room to eliminate external noise

Question 3

An example of constancy is

Answer 3

Holding illumination steady in a perception experiment

Question 4

Randomisation process is useful when

Answer 4

There are too many secondary variables to allow for. Results are based on probability.

Question 5

Statistical adjustment is used when

Answer 5

A variable can be compensated for. Eg subtracting a pre-test from a post-test

Question 6

The sources of invalidity include

Answer 6

Testing effects, regressing towards the mean, maturation, subject attrition, repeated measures interactions, dv measurement error, experimenter bias
-TRAMB

Question 7

Generalisability is sought for

Answer 7

Clients, settings, experimenter-therapist discrepancies, dependent variable

Question 8

Internal validity is highest when

Answer 8

All secondary variables are controlled

Question 9

Non-parametric test data assumes

Answer 9

Nominal or ordainl data

Question 10

Parametric test data assumes

Answer 10

Interval or ratio data

Question 11

Parametric tests include

Answer 11

t-test, ANOVA

Question 12

When comparing two means, null hypothesis is

Answer 12

pop1=pop2, or, pop1-pop2=0

Question 13

When comparing 3 means, null hypothesis is

Answer 13

Pop1=pop2=pop3

Question 14

A t-test compares how many means?

Answer 14

2

Question 15

An ANOVA compares how many means?

Answer 15

3 or more