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This is a difficult question to answer. The pure answer is no. In reality, it depends on the level of randomness in the data. If you plot the data, it will give you an idea of the randomness. Even with 10 data points, 1 or 2 outliers can significantly change the regression equation. I am not aware of a rule of thumb on the minimum number of data points. Obviously, the more the better. Also, calculate the correlation coefficient. Be sure to follow the rules of regression. See the following website: http:/www.duke.edu/~rnau/testing.htm
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What is the difference between simple and multiple linear regression?
I want to develop a regression model for predicting YardsAllowed as a function of Takeaways, and I need to explain the statistical signifance of the model.
When would you use simple linear regression?
You use it when the relationship between the two variables of interest is linear. That is, if a constant change in one variable is expected to be accompanied by a constant [possibly different from the first variable] change in the other variable. Note that I used the phrase "accompanied by" rather than "caused by" or "results in". There is no need for a causal relationship between the variables. A simple linear regression may also be used after the original data have been transformed in such a way that the relationship between the transformed variables is linear.
How do you do linear regression in Casio fx-991ES PLUS?
go to stat mode then then select (A+BX) mode and enter the data and press AC on cal. then shift+1 and go to the stat and select REG and there you can see options like A,B and r u can select any of these to get what u need .if you want the answer for r select that option. thnx.
What do bar graphs need?
For an ordinary bar graph you need two variables, the dependent variable being numerical. You need at least two observations - unless you want a bar graph that serves no purpose. You could have more than one dependent variables for a stacked or grouped bar graph.
Convert X intervals to z intervals?
The answer depends on the relationship between X and z. This may not be linear, in which case the conversion may need to take account of turning points.
