**Research methods**

To explore key aspects of investigation design

Operationalising variables

The term 'operationalising' means to simplify a concept or idea into a simpler form so that it can be studied and measured. It narrows the research focus on a broad term.

For example - Aggressive behaviour

Task:

How would you 'operationalise' these concepts into something that can be measured:

Memory

Attachment

What's the difference between....

Extraneous

**&**

Confounding

....Variables?

Extraneous = Anything other than the IV that can affect the DV

Confounding = An uncontrolled variable that produces an unwanted effect on the DV which affects the results.

Extraneous variables need to be controlled otherwise the researcher may think that the effects on the DV are caused by the IV when in fact they have been caused by the EV...

EV's can occur through RANDOM ERRORS or CONSTANT ERRORS

Random errors cannot be predicted such as state of mind of the participant, levels of motivation, noise, temperature, previous experiences preceding the experiment

Constant errors effect the DV in a constant way and can effect the experiment in more ways than one. Participant differences and errors of measurement are some constant errors.

One way of reducing random errors is by allocating participants randomly to experiment conditions, with the assumption that random errors will balance out over the course of the experiment.

One way of reducing constant errors is by COUNTERBALANCING. This is a method used in repeated measures design to combat order effects, practice, boredom and fatigue in an experiment. It ensures that each condition is likely to occur in a particular order. If there are only 2 variables then these will have an equal chance of being 1st and 2nd.

How do we improve RELIABILITY?

CORRELATIONAL ANALYSIS is a way of assessing the reliability of results. Reliability of the observer can be improved by operationalising key variables.

How would you operationalise these variables?

The ways in which the test itself can be assessed for its reliability can be done using the SPLIT-HALF METHOD or the TEST-RETEST METHOD.

Assessing reliability:

The split-half method is used in question based research where the test is split, either by odd and even numbers, in half or random parts. Each test is conducted separately and the results are then correlated. If there is a positive correlation, then the results are deemed reliable.

The test-retest method tests the stability of a test or questionnaire over time. This is done by presenting the same test to the same participants on two different occasions. It has to be done within a specific time period.

Why do you think this is???

Assessing and improving validity

There are 3 types of validity:

Internal

External

Test

Internal validity

The extent to which it can be certain that the research findings are the result of the variables stated in the hypothesis, and the variations are the result of manipulation of IV and not EV's or CV's

External validity

The extent to which the results can be generalised to the population as a whole. This can take 2 forms:

Population validity - The extent that the results can be generalised to other groups of people

Ecological validity - The extent to which the results can be generalised outside of the research setting.

**Test validity**

Face validity - experts assess whether a test is appropriate.

Content validity - experts assess whether the test instruments are appropriate.

Concurrent validity - comparing the new test with an one that validity has already been established.

Predictive validity - The same as concurrent but 2 sets of scores are obtained at different points in time.

Scales of measurement

Task:

Outline in your own words the definitions for NOMINAL, ORDINAL, INTERVAL & RATIO scales of measurement.

**Presenting data**

Bar charts

Bar charts are for representing NOMINAL or ORDINAL data or from average scores from different samples. EACH BAR IS SEPARATED as there is no order or relationship between categories. Usually, to prevent bias, bars are ordered either alphabetically or in descending/ascending order.

**Histograms**

Histograms are for representing INTERVAL or RATIO scales of measurement. The bars are touching to indicate a relationship between the values on the x-axis (horizontal).

Frequency polygons

Used as an alternative to the histogram, but is particularly useful when presenting data from 2 or more conditions. 2 or more lines can be drawn on the same graph to show a comparison.

**Scattergrams**

Scattergrams are used to show a CORRELATION: a relationship between 2 sets of variables to determine how much they do or do not CO-VARY. Correlations can be positive or negative.... which is this one?

**Frequency tables**

A way of presenting raw data to identify patterns or trends

**Describing statistics**

Measures of central tendency: Average values such as the MEAN, MEDIAN AND MODE

Measures of dispersion: How much the scores vary

Measures of dispersion:

**Range:**

The difference between the highest and lowest scores +1 if the scores are whole numbers.

For example:

7,9,11,12,15,21,27,32,42,58,76

76-7=69, +1 =70

If the data is represented in decimals the +0.1 needs to be added, 2 decimal places 0.01 and so on.

If the data is in half units then 0.5 needs to be added

Interquartile range:

2 3 7 8 10 11 16 18 21 22 26 26

1st you calculate the MEDIAN

2nd you identify 50% of the numbers that lay either side of the median value (in this case 50% is 6 digits so 3 above and below the median score)

Interquartile range

The upper and lower boundaries of the interquartile range are identified and a mean taken.

So what is the interquartile range here?

Standard deviation:

Is the spread of the data from the mean.

LO: