Positive Psychology: WJEC: A-Level Psychology Research Terms Part 2

This is when a researcher remains outside and unobserved during an experiment for observation.

The null hypothesis is a generally accepted statement or notion, which researchers try to nullify by offering an alternate hypothesis.
E.g., 'young people are bad drivers' is a generalisation that can be tested for its robustness.
The null hypothesis Ho may be accepted of course, but a researchers job is to TEST the obvious at times!

This is a research method in which the researcher observes people usually in their NATURAL ENVIRONMENT recording what they do and say.
E.g., Mary Ainsworth studied how infants responded to brief periods of separation from their mothers

1. Natural observation

2. Controlled observation

3. Covert observation

4. Overt observation

5. Participant observation

6. Nonparticipant observation.

This is to make something measurable. E.g. to give a score on an experiment or survey, such as this beautiful person scores an 8.

This is when the researcher chooses people close to where he or she works or socialises to ask them questions for a survey. It is done because it is convenient.

Ordinal data on numbers that are given an order or rank = ORDER
Cardinal data are given an actual numbers =HOW MANY

This is when the researcher is directly involved in the situation been survey aid or observed. Compare this with nonparticipant observation, in which he or she is removed and unobserved.

This is an initial survey usually quite brief that is given out to a few people to get feedback from participants and also for the researcher to review before going on to a more formal study. This gives the researcher a chance to remove any problematic questions or issues.

As one variable increases so does the other.

Primary sources are gathered by the researcher, while secondary sources are gathered from other peoples research.

Quantitated data is numerical and qualitative data is in the form of opinions or words.

This is similar to stratified sample link. Proportions of different groups within the target population are calculated and hence given a quota e.g. 50, and when the quota is satisfied, any other ppts from that Segment will be ignored.
E.g. a researcher may want to question 50 people from East London and 60 from West London, and so on. When 50 are taken from East London, all others from that region are ignored (politely, of course).

This is a method of sampling in which all participants have an equal probability of being chosen, e.g. from electoral registration number or being pulled out of a hat.

The range you will remember from maths is the highest take away the lowest, but it is called a measure of dispersion in statistics. That is, how much the data is dispersed.

Cardinal, ordinal, ratio, interval. Data can be measured in any of these four styles.

Ratio scales are the best when it comes to measurement scales because they tell us about the order, they tell us the exact value between units, AND they also have an absolute zero–which allows for a wide range of both descriptive and inferential statistics to be applied.
Here we can use phrases such as twice as big, or 3:1 ratio.

Interval scales are numeric scales in which we know not only the order, but also the exact differences between the values.

E.g. temperature, because the difference between each value is the same. For example, the difference between 60 and 50 degrees is a measurable 10 degrees, as is the difference between 80 and 70 degrees. Time is another good example of an interval scale in which the increments are known, consistent, and measurable.

Also 'noticed consistency.'
A study is reliable such that when repeated Its findings are similar.
In observational surveys, we check whether different researchers are observing the same categories of behaviour. This is known as inter-rater reliability.

This is when each participant takes part in an experiment on more than one occasion.
The person's performance is then compared under each condition that is changed. E.g. test scores and the different temperatures, or size of room, or number of other confederates.

When researchers behave in ways that may influence investigation. For examples in the language or behaviour that they use that may subtly mean something to ppts and hence change research outcomes.

The act of choosing participants for a study

A method used to select participants from a target population based on characteristics. A population is everybody that could be targeted, while a sampling frame lists particular characteristics or names. E.g. a population study of towns and villages over 1000 people in Somerset, a sampling frame would list all of those towns and villages.

Also known as a scatterplot or scatter graph, it is used to depict potentially correlating data: y versus x axes and data plotted according to the surveys.

A method of getting data from people in which the ppts provide the information themselves through a questionnaire or interview.

Semistructured lies between a fully structured interview in which the same questions are asked each participant, and open interview in which no predetermined questions are formed. In the semistructured interview there are topics that the researcher will cover but in which order is very much up to the particular interviewer..

Used by researchers to find similar ppts, by asking current participants for referrals as they may know people of a similar characteristic being sought. E.g., Welsh speakers in London, Xanax addicts in 6th Form.

This is another measure of dispersion (see the range) which is calculated by formula to describe the average distance that values lie from the mean. A low standard deviation means that the data are grouped around the mean, while a high standard deviation suggests the data are more dispersed.

This is when a researcher divides a population into strata, such as height or gender or profession and then participants are selected randomly from each strata based on a weighted proportion of the population.
E.g., if 65% of a school of 1000 are girls and 45% are boys, then 65% of a survey of 100 ppts should be girls (65 girls, 45 boys).

The same questions are given to each participant in the same order.

Researchers are keen to find the measures of central tendency and measures of dispersion to provide a summary of what they have found.

Choosing every nth person in a list.

| E.g., every fifth person on a list of 200 for a survey of 40.

All the members of a particular group from which ppts for a survey are chosen.
E.g. students aged 16 to 17.

Making observations at certain time intervals within a given period. E.g. every five minutes for 60 minutes

Participants must be fully informed about a study before they agree to take part. Compare deception..

The research investigate what it says it will investigate. In other words the researchers use appropriate measurements for the study.

Anything that is changed or controlled in research. These can be extraneous, independent, or dependent variables.

Sampling method in which participants volunteer to take part perhaps as a result of an advert.

Correlation data in which there is no relationship between variables.
e.g., number of trees planted in 2018 in UK versus number of students taking psychology.

Background study/reflection
Aim - what is it that you want to find out?
Hypothesis - putting your idea more formally
Identify variables - what are you going to measure?
Operationalise the variables - quantify them/score them if possible
Design - consider use of matched pairs/independent groups etc
Sample - target population and sample within
Equipment - what do you need for resources?
Ethical issues - harm?
Validity and reliability - check you're going to study what you're trying to find out etc
Data - collect it
Data - analyse it
Results - significance (find anything?)
Evaluation - strengths, weaknesses, overall conclusion (good or bad research).

Following the same ppts over a long period of time - years or even decades.

Instead of following ppts over a long period of time (as in longitudinal studies), a cross section of the population is surveyed reviewing different ages.

A way of checking internal reliability - questions are divided into two and if the results correlate well, then it is deemed internally reliable.

The significance level, also denoted as alpha or α, is the probability of rejecting the null hypothesis when it is true.

For example, a significance level of 0.05 indicates a 5% risk of concluding that a difference exists when there is no actual difference.

A significance level of 0.05 can be graphed by shading the 5% of the distribution that is furthest away from the null hypothesis.