Final answer:
Meta-analysis is the statistical technique that combines the results of several studies to improve result reliability, contrasting with ANOVA, Regression analysis, and Descriptive statistics, which serve different purposes.
Step-by-step explanation:
The correct answer is option b) Meta-analysis. Meta-analysis is a statistical technique used for combining the results of multiple studies on a particular subject to improve the reliability of the findings. By aggregating data from individual studies, a meta-analysis can provide a more comprehensive understanding of the subject and increase the statistical power of the analysis. It's important to understand that meta-analysis evaluates all relevant studies collectively, which allows for a more objective and accurate assessment of the research question.
In contrast, ANOVA (Analysis of Variance) is a statistical method used to compare the means of three or more groups to see if at least one group differs from the others. Regression analysis is typically used to determine relationships between variables and predict outcomes, and Descriptive statistics summarize and describe the characteristics of a dataset without making predictions or inferring from the data.
Meta-analysis is a statistical technique for combining the results of several studies to improve the reliability of the results. It involves evaluating the results of virtually all previous studies on a specific subject together. By analyzing a large pool of data, meta-analysis can provide a more comprehensive and reliable understanding of a particular topic.
For example, if multiple studies have been conducted on the effectiveness of a certain medication, meta-analysis would combine the results of these studies to determine the overall effectiveness of the medication. This approach can help identify patterns, trends, and confirm or refute hypotheses based on the collective evidence of multiple studies.