key science skills Flashcards
The scientific
method
The scientific method is a procedure used to obtain knowledge that involves hypothesis formulation, testing, and re-testing through processes of experimentation, observation, measurement, and recording.
theory
a theory is a proposition or set of principles that is used to explain something or make predictions about cause and effect.
modeles
a model is a representation of a concept, process, or behaviour often made to simplify or make something easier to understand
Aims
in psychological research, an aim is a statement outlining the purpose of the investigation.
the aim of this study is to investigate the
Hypothesis
a hypothesis is a testable prediction about the outcome of an investigation.
what should a hypothesis include
I. P. A. D
the independent variable and the dependent variable.
the population,
‘direction’ of results; for example, that some outcome was ‘more likely’ or ‘less likely’,
independent Variables (IV)
I manipulat
independent variable (IV) is the variable for which quantities are manipulated (controlled, selected, or changed)
dependent variable (DV)
the dependent variable (DV) is the variable the researcher measures in an experiment for changes it may experience due to the effect of the independent variable.
Controlled variables
controlled variables are variables other than the IV that a researcher holds constant (controls) in an investigation, to ensure that changes in the DV are solely due to changes in the IV.
what is the point of Controlled Experiments – Research Designs
strictly manipulate variables of interest (independent variables) in a controlled environment and measure their effect on another variable (the dependent variable).
infer a more causal relationship between variables.
how does a In controlled experiment work
an experimental group refers to the group of participants in an experiment who are exposed to a manipulated independent variable (i.e. a specific intervention or treatment).
- A control group refers to the group of participants in an experiment who receive no experimental treatment or intervention in order to serve as a baseline for comparison.
Within Subjects Design
A within-subjects design is an experimental design in which participants complete every experimental condition.
Between Subjects Design
A between-subjects design is an experimental design in which individuals are divided into different groups and complete only one experimental condition.
Mixed Design
Combines elements of within-subjects and between-subjects designs.
This allows experimenters to note differences that occur within each experimental group over time, and also compare differences across experimental groups.
case studies
A case study is an in-depth investigation of an individual, group, or particular phenomenon that contains a real or hypothetical situation
Correlational studies
A correlational study is a type of non-experimental study in which researchers observe and measure the relationship between two or more variables without any manipulation of them. The variables under investigation are only measured and not manipulated, unlike in experiments.
Correlational research aims to find relationships between variables, describe them, and make predictions on the basis of them.
Population
The population of an experiment refers to the group of people who are the focus of the research and from which the sample is drawn. For example, year 12 VCE Psychology students
sample
from the population, a sample is drawn, they are a subset of the population who participate in a study. The sample could be 10 Psychology classes across the state
A sample’s results can then be used to make conclusions about the wider research population; this is referred to as generalising results.
Sampling Techniques
1. Convenience Sampling
refers to any sampling technique that involves selecting readily available members of the population, rather than using a random or systematic approach.
- Random Sampling
Refers to any sampling technique that uses a procedure to ensure every member of the population has the same chance of being selected.
- Stratified Sampling
Within any given population, there are different subsets of people called strata. Strata reflect different demographic characteristics, such as age, socioeconomic status, or gender. Stratified sampling involves selecting people from the population in a way that ensures that its strata (subgroups) are proportionally represented in the sample.
The process of stratified sampling involves:
- dividing the research population into different strata based on characteristics relevant to the study.
- selecting participants from each stratum in proportion to how they appear in the
population. This selection
Allocation
Allocation refers to the process of assigning participants to experimental conditions or groups.
For example, in a study testing the effect of a new drug, there may be a control group (receives no active treatment) and an experimental group (receives the trial drug).
Half of the sample will need to be allocated to each group:
Random allocation: ensures every sample participant has an equal chance of being allocated to any group within the experiment
A study is either using random or non-random allocation
Extraneous Variables
is any variable that is not the independent variable but may cause an unwanted effect on the dependent variable
these variables should be controlled (kept constant between experimental groups), or at least monitored, so that they do not interfere with the results.
Confounding Variables
efers to a variable that has directly and systematically affected the DV, apart from the IV
may have been an extraneous variable that has not been controlled for, or a variable that simply cannot be controlled for
interfere with the investigation by providing alternate explanations for the results, it cannot be confirmed whether the IV or confounding variable caused the changes to the DV
can only be identified at the end of a study
Examples of Confounding and Extraneous Variables:
Participant related variables
- Order effects
- Placebo effects (expectancy effects)
- Experimenter effects
- Situational variables
Participant Related Variables
Also known as individual participant differences or subject variables, refer to characteristics of a study’s participants that may affect the results.
This includes characteristics like participants’ age, intelligence, and socioeconomic status.
Can be extraneous or confounding variables as they are likely to vary within the sample, and subsequently impact the results of the study.
large sample size
large sample size increases the sample’s representativeness of the population, which means that the sample is more likely to have a similar level of diversity as it does in the population.
random or stratified sampling (rather than convenience)
also ensures a more representative sample, which again, helps to ensure a sample which is unbiased.
Order effects
practise effects: participants perform better in later conditions due to having done it before.
fatigue effects: participants perform worse in later conditions due to being tired or bored from completing a prior task.
Counterbalancing
Counterbalancing is a method to reduce order effects that involves systematic manipulation of the presentation of the different levels of the IV.
A common example may involve splitting the participants in half: one half completes one experimental condition (A) first, followed by the other condition (B). The other half of participants complete the conditions in reverse order (B, then A).
Placebo effect
The Placebo Effect is an extraneous variable that has the potential to confound the results of a study if not controlled for. This would make the results invalid.
The placebo effect is a type of expectancy effect. Where a participants expectations about the treatment/ condition cause changes in their behaviour (the DV). This makes it impossible to tell if the results (DV) are because of the actual effects of the IV OR because of expectancy.
Placebo
tudies that test the efficacy of new drugs or treatment interventions typically have at least two experimental groups.
One group is generally provided with the active substance or intervention
Another group may be given a placebo (an inactive substance or treatment e.g. sugar pill
Demand Characteristics
Refer to cues in an experiment that may signal to a participant the intention of the study and influence their behaviour.
These can be extraneous variables as participants may be more likely to conform to the study’s hypothesis and meet the study’s ‘demands’.
Experimenter Effects
Also known as experimenter bias, refers to when the expectations of the researcher affect the results of an experiment.
If experimenters have strong expectations or wish to see a certain result, they may inadvertently bias the way they collect and record data, or how they interact with participants.
A single-blind procedure
A single-blind procedure is a procedure in which participants are unaware of the experimental group or condition they have been allocated to.
Helps reduce participants’ expectations; e.g. they may not know whether they are receiving a placebo or the active medication.
Can reduce placebo effect, demand characteristics and other participant expectations
A double-blind procedure
s a procedure in which both participants and the experimenter do not know which conditions or groups participants are allocated to.
E.g. in a study testing the efficacy of a new medication, neither the experimenter nor the participants would know if they were receiving the active drug or a placebo. Instead, a research assistant would record the allocations.
Helps to prevent the EV experimenter and participant expectations.
Situational Variables
Refer to any environmental factor that may affect the dependent variable such as: temperature, lighting, weather, and time of day
When these can or do affect the dependent variable in an unwanted way, they become extraneous and/or confounding variables.
Non-standardised instructions and procedures
Non-standardised instructions and procedures occur when directions and procedures differ across participants or experimental conditions. This introduces unwanted situational variables for either specific participants or entire experimental groups.
Standardised testing, conditions and procedures
Ensuring that each participant in an experiment receives the exact same instructions and follows the same procedures in each condition allows researchers to more conclusively infer that results are due to the independent variable.
Controlled Variables
Remember that experimenters may hold certain variables, other than the independent variable, constant.
This is when they become ‘controlled variables’, so that their impact is systematically minimised and accounted for.
Primary data
Primary data refers to data collected first-hand by a researcher. It may be collected in a variety of ways, such as through experimentation, observation, or survey
secondary data
secondary data refers to data sourced from others’ prior research, not collected directly by the current researcher. Secondary data may be obtained from processes like accessing data from publicly available databases or using data that other researchers have previously collected.
Quantitative data
Quantitative data is data that is expressed numerically, such as test scores
Qualitative data
Qualitative data is data that is expressed non-numerically; for example, a participant’s verbal description of how they are feeling.
Qualitative data may be collected through methods such as open-ended questionnaires and interviews
Qualitative data may sometimes be converted into quantitative data using systematic methods and analyses.
Objective Data
Objective data is factual data that is observed and measured independently of personal opinion.
Objective data is collected using measurement tools that ensure the same results are obtained by different researchers.
subjective data
data that is informed by a person, opinion or perception
Self reports
Self reports are often used in psychological studies, they can be in the form of surveys, questionaries, interviews…
They aim to gather data related to the subjective experience of the person and can if the questions are open ended, can results in rich descriptive data.
Outliers
values that differ significantly from other values in a data set,
Percentages
Divide the given number/score/mark by that total number. E.g. if a participant scored 15 marks out of 30 on the test, you would divide 15 by 30.
Multiply that ratio (e.g. 15/30) by 100 to get your final percentage. E.g. 15/30 × 100 = 50%.
Mean
The mean is a measure of central tendency that describes the numerical average of a data set as a single value.
It is often referred to as the ‘average’ of a data set and is
Calculated by adding up the total of all data values and then dividing this total by the number of data values in the data set.
Median
The median is a measure of central tendency that is the middle value in a data set ordered from lowest to highest.
Mode
The mode is a measure of central tendency that is the most frequently occurring value in a data set.
Range
the range is a measure of variability that is a value obtained by subtracting the lowest value in a data set from the highest value.
Standard deviation
Shows how much data ‘deviates’ from the mean
Standard deviation is calculated using a mathematical formula (which you do not need to know how to calculate)
Accuracy
Refers to how close a measurement is to the true value of the quantity being measured.
Precision
Refers to how closely a set of measurement values agree with each other but gives no indication of how close the measurements are to the true value
Systematic Errors
systematic errors are errors in data that differ from the true value by a consistent amount.
All the readings are shifted in one direction from the true value
Random Errors
random errors are errors in data that are unsystematic and occur due to chance.
While random errors also result in measurements that differ from the true value, they do not occur in a consistent way like systematic errors.
Repeatability
Repeatability is the extent to which successive measurements or studies produce the same results when carried out under identical conditions within a short period of time (e.g. same procedure, observer, instrument, instructions, and setting).
Repeatability is the extent to which the same study or measure used under the same conditions will produce the same results.
Reproducibility
Reproducibility is the extent to which successive measurements or studies produce the same results when repeated under different conditions (e.g. different participants, time, observer, and/or environmental conditions).
Repeatability is the extent to which the same study or measure used under the same conditions will produce the same results.
Internal Validity
Is the extent to which an investigation measures or investigates what it claims to.
External Validity
External validity is the extent to which the results of an investigation can be applied to similar individuals in different settings
