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Sensitivity Analysis
Learn sensitivity analysis from basics in this free online training. Sensitivity analysis course is taught hands-on by experts. Best for beginners. Learn about the advantages and disadvantages of sensitivity analysis & lot more.
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About this course
Sensitivity analysis is a very important part of multiple domains today. It is a way of assessing and analyzing how multiple variables affect the outcome or other dependant variables. This is a critical component to assess especially in domains such as data science and machine learning because of the fact that making changes to data points can have good or adverse effects on the solution. To have solutions in place that are obtained by data-driven algorithms and other processes is very important in today’s world of information technology. Since it is very important for all of you to understand this in detail, we here at Great Learning have come up with this course to help you get started with Sensitivity Analysis and to understand it completely.
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Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
Will I get a certificate after completing this Sensitivity Analysis free course?
Yes, you will get a certificate of completion for Sensitivity Analysis after completing all the modules and cracking the assessment. The assessment tests your knowledge of the subject and badges your skills.
How much does this Sensitivity Analysis course cost?
It is an entirely free course from Great Learning Academy. Anyone interested in learning the basics of Sensitivity Analysis can get started with this course.
Is there any limit on how many times I can take this free course?
Once you enroll in the Sensitivity Analysis course, you have lifetime access to it. So, you can log in anytime and learn it for free online.
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Introduction to Sensitivity Analysis
Sensitivity analysis (SA) is a mathematical technique that assesses the impact of different factors on the outcome of a given system or process. It involves analyzing how a system or method behaves in response to changes in one or more input parameters. Decision-makers can use sensitivity analysis to identify which variables are most important in determining the output of a system or process and identify potential areas for improvement.
Types of Sensitivity Analysis
Sensitivity analysis has two main types: local sensitivity analysis and global sensitivity analysis. Local sensitivity analysis considers the effect of varying a single input parameter on the output of a system or process, helping to determine the relative importance of different inputs. Global sensitivity analysis assesses the impact of varying multiple input parameters simultaneously, helping to understand the overall development of changes to various input parameters on the output of a system or process.
How Sensitivity Analysis Works
An analyst typically performs sensitivity analysis by changing the value of one or more input parameters and observing the resulting changes in the system's output or process. This allows the analyst to determine which input parameters are most critical in determining the system's production or process.
Critical Applications of Sensitivity Analysis
Sensitivity analysis is widely used in various fields, including finance, economics, engineering, and management. It can help understand the risk associated with different financial instruments and strategies, assess the impact of various economic policies on the overall economy, understand the effects of different design parameters on the performance of a system, and assess the impact of different organizational strategies on the overall performance of the organization.
Advantages and Disadvantages of Sensitivity Analysis
Sensitivity analysis is a powerful tool for decision-makers, as it can provide a clear picture of how changes to different input parameters can affect a system or process. It can also be used to identify areas where changes to input parameters could have the most significant effect on the system's output or method. However, it can be time-consuming and labor-intensive, and it is often difficult to accurately assess the impact of changes to multiple input parameters simultaneously.
Practical Demonstration in Python
Python is a powerful programming language that performs various tasks, including sensitivity analysis. To perform sensitivity analysis in Python, analysts can use the SciPy library to define the system or process they wish to analyze and then use the sensitivity analysis functions to calculate the sensitivity of the system or process to changes in the input parameters.