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Discuss the purpose of correlational analysis.
Please include 400 words in your initial post with two scholarly references.Attached you can find the rubric

ANSWER
Purpose of Correlational Analysis

Correlational analysis is a statistical technique used to assess the strength and direction of the linear relationship between two or more variables. It is a descriptive statistical method that does not establish causality but rather quantifies the extent to which two variables move together. Correlation coefficients range from -1 to 1, with -1 indicating a perfect negative correlation, 0 indicating no correlation, and 1 indicating a perfect positive correlation.

Key Purposes of Correlational Analysis

Identifying Relationships: Correlational analysis helps researchers identify potential relationships between variables that may not be readily apparent. This can be particularly useful in exploratory research where the goal is to uncover patterns and connections within a dataset.

Assessing Strength and Direction: By quantifying the correlation coefficient, researchers can assess the strength and direction of the relationship between variables. A strong correlation suggests that the variables are closely related, while a weak correlation indicates a less pronounced relationship. The direction of the correlation indicates whether the variables move together in the same direction (positive correlation) or in opposite directions (negative correlation).

Predicting Outcomes: Correlational analysis can be used to predict future outcomes based on the observed relationship between variables. For instance, if there is a strong positive correlation between ice cream sales and temperature, it might be possible to predict ice cream sales based on temperature forecasts.

Generating Hypotheses: Correlation analysis can generate hypotheses about causal relationships between variables. While correlation does not imply causation, it can provide a starting point for further research to investigate whether one variable causes changes in the other.

Examples of Correlational Analysis

Examining the relationship between study habits and exam grades.

Investigating the association between exercise levels and body mass index (BMI).

Assessing the correlation between social media usage and self-esteem.

Exploring the connection between sleep duration and academic performance.

Analyzing the relationship between air pollution levels and respiratory health outcomes.

Scholarly References

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
2. Dancey, C. P., & Reidy, J. (2006). Statistics for the social sciences: An applied approach (8th ed.). Boston, MA: Pearson.

Sources
www.causal.app/formulae/correl-google-sheets
libguides.library.kent.edu/SAS/PearsonCorr