In one type of nonlinear regression, the function that summarizes the relationship between the variables is called polynomial regressionbecause the function includes powers of the x-variable that are greater than 1. This one is appropriate when data fluctuates. The more changes of direction in the data, the more powers in the equation. Discover how to use Excel to perform this analysis and expand your ability to make predictions.
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- [Voiceover] Now we turn to Polynomial Regression,…which you use when you have a Y variable…that changes direction when the X variable increases.…This is important to know because these kinds…of X-Y relationships are all around us.…And you can analyze them if you know…how to use Polynomial Regression.…They occur in nature,…like the motion of a particle influenced by gravity.…In medicine, the weight of the patient…versus weeks of hospitalization.…And in business, like the ups and downs of market cycles.…The number of direction changes determines…the highest power of X in the regression equation.…
A linear relationship has no direction changes…and the highest power of X is one.…With one direction change the highest power of X is two.…This is called a quadratic relationship.…With two direction changes, the highest power of X is three…and this is called a cubic relationship, and so on.…As many regression analysis, part of the objective…is to find the values of the regression coefficients…that best fit the data.…
He explains how to organize and present data and how to draw conclusions using Excel's functions, charts, and 3D maps and the Solver and Analysis ToolPak add-ons. Learn to calculate mean, variance, standard deviation, and correlation; visualize sampling distributions; and test differences with analysis of variance (ANOVA). Then find out how to use linear, multiple, and nonlinear regression testing to analyze relationships between variables and make predictions. Joseph also shows how to perform advanced correlations, variable frequency testing, and simulations.
By the end of this course, you should have the foundational knowledge you need to take other statistics-related courses and perform basic analysis in the workplace.
- Using Excel's statistical functions and 3D charts
- Visualizing sampling distributions
- Performing comparisons with ANOVA
- Performing two-way analysis with ANOVA
- Analyzing linear regression
- Performing multiple regression and nonlinear regression analysis
- Making advanced correlations
- Testing variable frequencies
- Running simulations