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==== Linear regression ====
{{main|Linear regression}}
In linear regression, a plot is constructed with the previous values of the dependent variable plotted on the Y-axis and the independent variable that is being analyzed plotted on the X-axis. A regression line is then constructed by a statistical program representing the relationship between the independent and dependent variables which can be used to predict values of the dependent variable based only on the independent variable. With the regression line, the program also shows a slope intercept equation for the line which includes an addition for the error term of the regression, where the higher the value of the error term the less precise the regression model is. In order to decrease the value of the error term, other independent variables are introduced to the model, and similar analyses are performed on these independent variables.<ref name=":0" /><ref>{{Cite web |title=Linear Regression |url=http://www.stat.yale.edu/Courses/1997-98/101/linreg.htm |access-date=2022-05-06 |website=www.stat.yale.edu}}</ref> Additionally, multiple linear regression (MLP) can be employed to address relationships involving multiple independent variables, offering a more comprehensive modeling approach.<ref>{{Cite journal |
== Applications ==
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The STAR methods operate using regression analysis, and fall into two methods. The first is the STAR monthly balance approach, and the conditional expectations made and regression analysis used are both tied to one month being audited. The other method is the STAR annual balance approach, which happens on a larger scale by basing the conditional expectations and regression analysis on one year being audited. Besides the difference in the time being audited, both methods operate the same, by comparing expected and reported balances to determine which accounts to further investigate.<ref name=":3" />
Furthermore, the incorporation of analytical procedures into auditing standards underscores the increasing necessity for auditors to modify these methodologies to suit particular datasets, which reflects the ever-changing nature of financial examination.<ref>{{Cite journal |last=Wilson |first=Arlette C. |date=1991 |title=Use of Regression Models as Analytical Procedures: An Empirical Investigation of Effect of Data Dispersion on Auditor Decisions |url=http://journals.sagepub.com/doi/10.1177/0148558X9100600307 |journal=Journal of Accounting, Auditing & Finance |language=en |volume=6 |issue=3 |pages=365–381 |doi=10.1177/0148558X9100600307 |s2cid=154468768 |issn=0148-558X}}</ref>
=== Business Value ===
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