Research Methods- Aims And Hypotheses Flashcards
Aim:
a clearly phrased general statement about what the investor intends to research
What can an aim include ?
Can include the purpose of the study, for example, following on from findings of previous research to develop a theory or perhaps a direct replication. Phrased as either a question or a statement.
E.G. “the aim of this research is to find out if colour can influence recall, due to previous research showing exposure to green plants increased recall”
Difference between aim and hypotheses
While aims say what the researcher is intending to investigate and perhaps why a hypothesis is formulated by the researcher to communicate exactly how the research will be conducted.
Hypothesis
a precise testable statement including levels of the independent variable and dependant variable (or both covariables for a correlational study).
E.G. “there is a difference in the number of words recalled by participants recalling in blue light compared to participants recalling in green light”
Operationalisation:
Operationalised variables are carefully stated, demonstrating exactly how they are to be measured for example the dependant variable would be the “number of words recalled”, not “recall”.
Operationalisation examples:
“reaction time in milliseconds”
“average change in heart rate in beats per minute”
“average change in score on a hostility questionnaire”
“average shock level given to a confederate”
The independent variable needs to clearly state both levels so “participants recalling in green light and participants recalling in blue light”
NOT “The colour of light” or “Green light or not” or “condition A or B”.
Hypotheses are NOT
predictions, they are competing statements of fact that the researcher accepts or rejects based on the data that is collected. This is in line with the scientific principle of the researcher as a neutral observer.
Null hypothesis Ho:
States that there is no change (difference) in the measurement of the dependant variable as a result of the manipulation in the independent variable.
Alternative hypothesis H1:
also known as the research hypothesis, States that there is a change (difference) in the measurement of the dependant variable as a result of the manipulation in the independent variable.
Hypothesis testing:
data is collected and statistical testing is conducted on the data.
This provides evidence, if the evidence is strong enough the null hypothesis can be rejected and the alternate hypothesis is accepted.
Alternate hypotheses
The alternate hypothesis can be written as either a directional hypothesis also known as a one-tailed hypothesis or as a non-directional hypothesis, also known as a two-tailed hypothesis.
Non-directional hypothesis:
+Example
States that there is a difference in the measurement of the dependant variable (as a result of the manipulation of the IV) but not the direction the results will go.
E.g. “There is a difference in the number of words recalled by participants recalling in green light compared to participants recalling in blue light”
Directional hypothesis:
Example
States that there is a difference in the measurement of the dependant variable (as a result of the manipulation of the IV) and says which direction the results will go.
E.g. “There is an increase in the number of words recalled by participants recalling in green light compared to participants recalling in blue light”
When should a researcher only use a directional hypothesis?
A researcher should only use a directional hypothesis if there is previous research that suggests which way the results are likely to go.
Falsifiability:
Any theory, even well-established theories backed up with a significant amount of prior evidence have to be open to the possibility that new research will emerge that contradicts its basic principles. The more a theory is able to withstand attempts to falsify it the greater the confidence we have in that theory but our confidence can never reach 100% certainty.