Week 2 - Research design and reporting Flashcards
Quantitative designs is the process of:
is the process of collecting and analyzing numerical data. ]
It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.
Binary data
Binary data is data whose unit can take on only two possible states.
0 v 1
Discretet
e.g. would you like cake; yes or no?
Continuous data
Real numbers - decimal component
Whole numbers
integer data
4 ways in which the difference values of variables can differ:
The values of the variable reflect different magnitudes and have an ordered relationship to one another – that is, some values are larger and some are smaller.
Identity
There are four ways in which the different values of a variable can differ:
The values of the variable reflect different magnitudes and have an ordered relationship to one another – that is, some values are larger and some are smaller.
Magnitude
There are four ways in which the different values of a variable can differ:
nits along the scale of measurement are equal to one another. This means, for example, that the difference between 1 and 2 would be equal in its magnitude to the difference between 19 and 20.
Equal intervals
There are four ways in which the different values of a variable can differ:
The scale has a true meaningful zero point. For example, for many measurements of physical quantities such as height or weight, this is the complete absence of the thing being measured.
Absolute zero
A_______ variable satisfies the criterion of identity, such that each value of the variable represents something different, but the numbers simply serve as qualitative labels, this is known as a ________ scale
Nominal scale
An ______ variable satisfies the criteria of identity and magnitude, such that the values can be ordered in terms of their magnitude. For example, we might ask a person with chronic pain to complete a form every day assessing how bad their pain is, using a 1-7 numeric scale, this is known as a ______ scale
Ordinal scale
An ________scale has all of the features of an ordinal scale, but in addition the intervals between units on the measurement scale can be treated as equal.
Interval scale
A ________scale variable has all four of the features outlined above: identity, magnitude, equal intervals, and absolute zero
The difference between a ______ scale variable and an interval scale variable is that the ______ scale variable has a true zero point. Examples of ______ scale variables include physical height and weight, along with temperature measured in Kelvin.
Ratio
Observational research variables are known as:
Predictor and Outcome variables
In quasi-experimental and experimental research, the IV will do the explaining and is manipulated by the researcher. TRUE or FALSE
True
Predictor variable: is a factor of interest and is being _______
measured
Outcome variable: is being measured in relation to the predictor; usually an ______
exposure
Real numbers
decimal component, continuous
e.g. how much did the cake weigh?
Variables must have at least 1 possible measures TRUE or FALSE
False - they must have at least 2
_______ designs capture data at more than one point in time.
Longitudinal designs
_______ designs capture data at one point in time.
Cross sectional
_______ designs do not manipulate any variables.
Observation
_______ designs manipulate a variable (termed condition); participants
are assigned to one condition at random.
Experimental
__________ designs do not manipulate any variables participants
are assigned to a condition based on non random criteria.
Quasi experimental
_________subject designs collect data from participants relative to one
condition.
Between
________ subject designs collect data from participants relative to more than
one condition (usually all conditions). This design is also called repeated
measures.
Within
A design can be mixed, with both between and within subject assessments. TRUE or FALSE
True
WEIRD sampling represents only % of the population
12%
The vast majority of published psychological research is on ____ _____ _____ & ______ meaning generalisation is limited
Western, Educated, Industrialised, Rich and Democratic
How symmetrical the data is either side of the mean -
skew
How variable the data is (e.g. data range, standard deviation and kurtosis).
How variable the data is (e.g. data range, standard deviation and kurtosis).
Sampling: representative of the population
e.g. random sample of medicare numbers
Population -based sample
Sampling not representative of the population e.g clinic-based or through social media advertising
Convivence samples
Sampling based on pre-defined groups
e.g. equal numbers of 5-9, 10-10 & 15-19 year olds
Stratification
Quasi-experimental designs…
Do not manipulate any variables; participants are assigned to a condition based on non-random criteria
We ran a study investigating how younger and older adults remember faces. All participants were presented with 20 images of faces, presented one at a time for 5 seconds, and were instructed that they should remember all images. They then engaged in a foil (distractor) task for 20 minutes, after which, they were presented with 40 images of faces, half of which were initially presented to them. They had to indicate whether the image was “old” (i.e. previously presented) or “new” (i.e. not previously presented). Correct responses were recorded and compared between the younger and older adult groups. What study design is being used here?
Between-subjects
We go to a high school and collect data on numeracy and literacy from all students on one day. What can we say about the study design? It is…
Cross-sectional, observational, and between-subjects
A population-based sample…
Represents the structure of the underlying population
We advertise a study investigating the effects of bungee jumping. The poster states that participation involves bungee jumping off a man-made structure in Port Adelaide. We are most likely to observe…
A self-selection bias amongst participants
A self-selection bias amongst participants
Manipulation of at least one variable and randomisation
Scales of measurement and types of variables. Remember that there are two different distinctions here. There’s the difference between discrete and continuous data, and there’s the difference between the four different scale types (nominal, ordinal, interval and ratio).
T or F
T
Inter-rater reliability. This relates to consistency across people. If someone else repeats the measurement (e.g., someone else rates my intelligence) will they produce the same answer?
T or F
T
Parallel forms reliability. This relates to consistency across theoretically-equivalent measurements. If I use a different set of bathroom scales to measure my weight does it give the same answer?
T or F
T
Internal consistency reliability. If a measurement is constructed from lots of different parts that perform similar functions (e.g., a personality questionnaire result is added up across several questions) do the individual parts tend to give similar answers
T or F
T
