A straight line is not always the best way to summarize the relationship between two variables. When it's not, nonlinear regression is the appropriate way to model the relationship. In three types of nonlinear regression, natural logarithms and exponentials play a major role. Thus, understanding natural logarithms and exponentials is key to understanding these regression models. Joe shows you the fundamentals of these concepts so that you have a solid foundation for understanding nonlinear regression.
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- [Voiceover] Sometimes a straight line is not…the best way to summarize a scatterplot,…which takes us to nonlinear regression.…Before we get to nonlinear regression, though,…I first have to tell you about logarithms and exponentials.…Why?…Because you absolutely have to understand…these concepts in order to fully understand…and work with several kinds of nonlinear regression.…And nonlinear regression has far-ranging applications.…Let's begin with logarithms.…A logarithm is an exponent.…It's a power that you raise a number to,…like 10 squared equals 100…and 10 to the third equals a thousand.…
In the first case, we'd say that the logarithm…of 100 with base 10 equals two.…In the second case, we'd say that the logarithm…of 1,000 with base 10 equals three.…What about numbers that aren't powers of 10?…For example, how would you find the logarithm of 756?…You can check all this out in Excel…by using Excel's LOG10 function.…In cell F1, I'll type 756.…In cell F3, let's type…=LOG10(756)…And there's its logarithm.…
Now reverse the process.…
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