Experiments And Statistics

Question 1

Experimentation begins by

Answer 1

formulating a number of research hypotheses.

Question 2

Translate the different research hypotheses into a set of

Answer 2

treatment conditions and the selection of an appropriate experimental design within which to embody the different treatment conditions

Question 3

Different treatments are administered to different groups of

Answer 3

subjects or to the same subjects in different orders and performance on some response measure is observed and recorded

Question 4

Designing experiments

Answer 4

• Experimentation begins by formulating a number of research hypotheses.
• Translate the different research hypotheses into a set of treatment conditions and the selection of an appropriate experimental design within which to embody the different treatment conditions
• Different treatments are administered to different groups of subjects or to the same subjects in different orders and performance on some response measure is observed and recorded.

Question 5

The treatment variable is commonly known as an

Answer 5

Independent variable

Question 6

The measure is known as the

Answer 6

Dependent variable

Question 7

An independent variable is the variable that is

Answer 7

Manipulated

Drug / Placebo

Question 8

The dependent variable is the response measure which is

Answer 8

manipulated on the basis of the independent variables

Blood sugar levels

Question 9

There are three kinds of independent variables:

Answer 9

• Quantitative variables are variables that represent variation in amount (e.g. amount of drug, loudness of noise).
• Qualitative variables represent variations in kind or type (e.g. teaching strategy).
• Classification variables systematically vary characteristics which are intrinsic to the subjects of the experiment (e.g. age, sex, IQ, species, word type, etc.)

Question 10

Quantitative variables are variables that

Answer 10

represent variation in amount (e.g. amount of drug, loudness of noise).
A type of independent variable

Question 11

Qualitative variables represent

Answer 11

variations in kind or type (e.g. teaching strategy).

A type of independent variable

Question 12

Classification variables systematically vary

Answer 12

characteristics which are intrinsic to the subjects of the experiment (e.g. age, sex, IQ, species, word type, etc.)
Independent variable

Question 13

Nuisance variables are potential

Answer 13

independent variables which if left uncontrolled could exert a systematic influence on the different treatment conditions.

Question 14

Types of nuisance variables

Answer 14

• Several researchers running the same experiment might produce an experimenter effect.
• The time of day could have an influence.
• The kind of subject selected can effect the influence of the independent variables.

Question 15

(Nusaince variable)

If we do not control for these differences in experimental situation…

Answer 15

we might have a confounding variable in the experiment

Question 16

Once we have designed an experiment and have produced an experimental hypothesis then we need to decide upon

Answer 16

the specific details of the experiment.

Question 17

The idea is to select a measure that will

Answer 17

capture” the hypothesised differences.

Question 18

The measure that is adopted is known as the

Answer 18

Dependent variable

Question 19

We hypothesise that the observed data will be somehow

Answer 19

dependent on the nature of the independent variable

Question 20

Control in experimentation

Answer 20

• Consider an experiment where the data is collected by running the experiment simultaneously in two different laboratories:
• The two labs are identical in every respect except that the temperature for each room cannot be controlled.
• Temperature variations may lead to systematic variations in the performance on a task.
• Randomly allocating different treatment conditions to the rooms gives an equally likely “chance” that different random temperatures will be associated with the different treatment means.

Question 21

Completely randomised designs

Answer 21

• The completely randomized design is characterized by the fact that the subjects are randomly assigned to serve in one of the treatment conditions.
• This is also known as a between subjects design since any differences in behaviour observed among the treatment conditions are based on differences between different groups of subjects.

Question 22

Randomised block design uses

Answer 22

blocks of subjects who are matched closely on some relevant characteristic

• A common procedure is to treat a subject as a ‘block’, wherein the subject serves in all the treatment conditions of an independent variable.
• When subjects complete all the treatment conditions this type of design is commonly referred to as a repeated measures design or a within subjects design.

Question 23

Statistical Hypothesises

5

Answer 23

• The Null Hypothesis
• The Alternative Hypothesis
• Deciding to Accept or Reject the Null Hypothesis.
• Errors in Hypothesis Testing.
• Juggling Type I and Type II Errors

Question 24

A research hypothesis is a

Answer 24

fairly general statement about the assumed nature of the world that gets translated into an experiment.

Question 25

Statistical hypotheses consist of a

Answer 25

set of precise hypotheses about the parameters of the different treatment populations.

Question 26

Two statistical hypotheses are usually stated

Answer 26

• The Null Hypothesis
• The Alternative Hypothesis
• These are mutually exclusive or incompatible statements about the treatment parameters

Question 27

The null hypothesis is the

Answer 27

statistical hypothesis which will be tested. It is often symbolized as Ho.

Question 28

The function of the null hypothesis is to specify the

Answer 28

values of a particular population parameter (usually the mean) in the different treatment populations (symbolized as µ1, µ2, µ3 and so on).

Question 29

The null hypothesis typically chosen gives the same

Answer 29

value to the different populations such that
•Ho: µ1=µ2=µ3=etc.
This is the same as saying that no treatment effects are present in the population

Question 30

The alternative hypothesis

Answer 30

•If the parameter obtained from the treatment groups are too deviant from those specified by the null hypothesis, Ho, then the null hypothesis is reject in favour of the other statistical hypothesis, called the alternative hypothesis, H1.

Question 31

Usually the alternative hypothesis states simply that

Answer 31

the different treatment populations are not all equal. Specifically,
•H1: not all µ’s are equal.

Question 32

Deciding to reflect the null hypothesis or not

Answer 32

• A decision to reject Ho implies an acceptance of H1, which in essence, constitutes support of our original research hypothesis.
• On the other hand, if the parameter estimates are reasonably close to those specified by the null hypothesis, Ho is not rejected.

Question 33

There is a problem with the way in which the null hypothesis and and alternative hypotheses are set up…

Answer 33

• For the null hypothesis
• All µ’s are equal
• For the alternative hypothesis
• All µ’s are not equal.
• These are statements at the level of the population means. However all we have are sample means.

Question 34

We have to adopt a criteria for rejecting the null hypothesis…

Answer 34

• We do this by calculating test statistics based on the properties of the F-distribution.
• The value we adopt is called the significance level and is referred to as a (alpha).
• The value for a that we usually adopt in psychology is 0.05.

Question 35

Errors in Hypothesis Testing

Answer 35

•The procedures we follow in hypothesis testing do not guarantee that a correct inference will be drawn.
•Whenever we make a decision about the Null Hypothesis we can make a mistake.
•There are two basic kinds of errors:
Type 1 error
Type 2 error

Question 36

Type 1 Error

Answer 36

Reality
•Null Hypothesis is true
•Alternative Hypothesis is false
Decision
•Reject the Null Hypothesis
•Accept the Alternative Hypothesis

Question 37

Type 2 error

Answer 37

Reality
•Null Hypothesis is false
•Alternative Hypothesis is true
Decision
•Fail to reject the Null Hypothesis
•Reject the Alternative Hypothesis

Question 38

Juggling Type 1 and Type 2 errors

Answer 38

• Most of the time we do statistical analyses we are trying to juggle Type I and Type II errors.
• Generally, if it is important to discover new facts, then we may be willing to accept more Type I errors.
• On the other hand if it is important not to clog up the literature with false facts then we might be more willing to accept more Type II errors.