In one type of nonlinear regression, the function that summarizes the relationship between the variables is called exponential regression because the x-variable appears in the function as an exponent -- a power to which you raise the constant e. This type of regression model is appropriate when data changes at increasingly higher rates. Discover how to use Excel to perform this analysis and expand your ability to make predictions.
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- [Voiceover] Now I'm going to tell you about a kind…of nonlinear regression called exponential regression.…It's important to know about exponential regression…because many processes in nature, like the change…in concentration of substances in the blood stream…and business like compound interest, seem…to follow an exponential process.…If you understand exponential regression, you'll be…able to successfully model and analyze them.…Here's the equation for exponential regression.…In which, e is the base of natural algorithms.…Like in any regression analysis, part of the objective…is to find the values of a and b that best fit the data.…
Here's an extremely crucial example…from nature that effects business.…Here's a data along with a scatter plot…and regression curve, equation and r square.…Column A holds the time in seconds,…Column B has the height of the US brand in centimeters.…Column C will hold the natural algorithms…of the heights in Column D.…Why the logarithms of the heights? I'll explain.…We'll use Excel's Regression tool for the complete analysis.…
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