Statistical significance is crucial in psychology for discerning if study results are due to intervention or chance. It involves hypothesis testing, comparing null and alternative hypotheses, and assessing p-values against a significance level. Effect size and sample characteristics also play vital roles in validating research findings and their practical implications in the field.
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Hypothesis testing involves comparing the null hypothesis and alternative hypothesis to determine if a difference is due to chance or a specific experimental intervention
Definition and Calculation
Effect size is a quantitative measure of the strength of a phenomenon being studied, calculated using the difference between sample and population means
Importance in Interpreting Results
Effect size is crucial for understanding the practical significance of results and should be considered alongside statistical significance
A representative and larger sample can increase the accuracy of effect size and reduce the likelihood of Type II errors
The p-value is a statistical measure that indicates the probability of obtaining observed results if the null hypothesis were true, calculated using a predetermined significance level and chosen test statistic
Researchers often use a stringent significance level to mitigate the risk of Type I errors, which occur when the null hypothesis is incorrectly rejected
Many statistical tests assume a normal distribution, such as the z-test used to compare sample means
Statistical significance is crucial in psychology research due to the abstract nature of psychological constructs and the variability in human behavior
Researchers must also consider effect size and the broader context to assess the real-world relevance of their findings
An example of hypothesis testing in action is comparing the college attendance rate of a specific school to the national average
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A statistically significant outcome enables researchers to dismiss the ______ hypothesis, which posits no effect, in favor of the ______ hypothesis that suggests a meaningful difference.
null
alternative
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Definition of effect size
Quantitative measure of strength of a studied phenomenon, indicates practical significance.
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Role of sample representativeness
Ensures sample mirrors population, reduces bias, enhances generalizability of results.
