4.8 • +11k Ratings
Save
Print
Edit
What are probability and significance in psychology? What role do they play in research? We dig into both theory and methodology, as well as examples of significance tests and probability, in the hopes of bringing these seemingly abstract concepts to life.
Significance tests are commonly used in psychological research to determine whether differences between groups could be due to chance. The results of the tests (inferential statistical data) determine whether to reject the null hypothesis.
Significance tests give researchers a statistical value to measure how likely the research results are due to chance. Another word for this is the alpha level. In psychology, this is written as
.
Researchers have a consensus about what alpha level is acceptable, which is 0.05. If the significance value is too high, the alternative hypothesis cannot be accepted. The significance value is a quantitative value that tells the researcher and readers how likely the results are due to chance.
Chance refers to the data being due to the relationship between the independent and dependent variables and not due to extraneous or confounding variables.
A significance value of 0.05 means a 95% probability that the results are not due to chance.
Researchers cannot determine 100% that their results are due to the variables they are studying. This is because researchers cannot control for every factor (that is not the independent variable) that might affect the dependent variable and, therefore, the experiment results.
The significance values that are commonly used in research are:
Researchers must also decide whether to use a one-tailed or two-tailed test when conducting a statistical test. It depends on the research hypothesis.
Whenever researchers use inferential statistics, they do significance testing. As a result, the researcher can determine if the results can be generalised to the target population. Researchers can also determine if their research needs to be revised, such as the procedure used.
Hypotheses:
Alternative – The observed results are due to the independent and dependent variables' interaction. If this is the case, we should find a significant p-value.
Null – The results are not due to the independent variable but to chance. If this is the case, we should find a non-significant p-value.
Acceptance of:
The alternative hypothesis is accepted if a value is found at or below the significance level.
The null hypothesis is accepted if a value above the significance level is found.
Rejection of:
The alternative hypothesis is rejected if a value above the significance level is found.
The null hypothesis is rejected if a value at or below the significance level is found.
A Type 1 error is when we incorrectly reject the null hypothesis when it is in fact true. If the significance level is at 0.05, this means there is a 5% chance of a Type 1 error. A Type 2 error is when we incorrectly reject the alternative hypothesis when it is true.
Occasionally, non-significant results are due to problems with the methodology used. Significant results can be found once these have been corrected and the experiment retested.
Suppose a research design does not use a standardised protocol. In that case, the results may reflect the conditions under which the participants were experimented on and, therefore, are likely due to chance. The researcher must repeat the experiment but use a standardised procedure to counteract this.
p = significance value.
< = the significance value is less than the number reported (e.g. < 0.05 = significance is less than 0.05).
> = the significance value is greater than the number reported (e.g. > 0.05 = significance is greater than 0.05).
The inferential statistic is a quantitative statistical value that measures the data collected. It can be used to make generalisations about the target population.
If a significant value is found, the inferential statistic can be used to make inferences about the target population supported by evidence. However, if this is not the case, the study should not make inferences about the target population.
If a non-significant value is not found, it does not mean that there is no relationship/interaction between the independent and dependent variables. Instead, it means that other variables are also influencing the dependent variable. Therefore the study cannot provide an accurate (reliable or valid) measure of the interaction between the independent and dependent variables.
An example of a significance level for a correlation analysis that would be accepted is:
r (56) = .63, p = <.05
This example shows:
A correlational analysis was performed (r).
A positive correlation was found (.63).
There were 56 participants (56).
The significance value was accepted because the significance value is below the accepted alpha value of 0.05.
The alternative hypothesis should be accepted.
r (56) = .63, p = < .08
This example shows:
The significance value is non-significant as it is above .05.
The null hypothesis should be accepted.
If less than a 5% probability (0.05 significant value) is found, the probability is significant.
No, the significance value is a number used in psychology to measure probability. The significance value used in psychology is 0.05, so if we get that value in our results, there is a 5% probability that the results occurred by chance, and we can reject the null hypothesis.
The significance value is an element of probability. It tells us the probability of how confidently the researchers can accept or reject the research hypothesis.
If a significance value of 0.05 is found, there is a 95% chance the results are not due to chance.
Significance tests are used in psychology research to determine if the differences between groups could be due to chance. The results of the tests (inferential statistical data) determine whether to reject the null hypothesis. If a significance value of 0.05 is found then it can be assumed that the data is statistically significant.
60%
of the users don't pass the Probability and Significance quiz! Will you pass the quiz?
Start Quiz
Be perfectly prepared on time with an individual plan.
Test your knowledge with gamified quizzes.
Create and find flashcards in record time.
Create beautiful notes faster than ever before.
Have all your study materials in one place.
Upload unlimited documents and save them online.
Identify your study strength and weaknesses.
Set individual study goals and earn points reaching them.
Stop procrastinating with our study reminders.
Earn points, unlock badges and level up while studying.
Create flashcards in notes completely automatically.
Create the most beautiful study materials using our templates.
Sign up to highlight and take notes. It’s 100% free.
