Topic: Assumptions of the Linear Regression Model
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Answers to Common Questions
What are the implications if the assumptions made on the errors o...
The answers won't be valid or the uncertainty will be more or less than expected. Read More »
Source: http://answers.yahoo.com/question/index?qid=20071029060457AAkdVdR
What is a linear regression model?
Linear regression attempts to model the relationship between two variables by fitting a linear eq... Read More »
Source: http://www.chacha.com/question/what-is-a-linear-regression-model
What is linear piecewise regression model?
Variant: break point A model that describes the situation where the graph relating the expectation of the random variable Y and the variable x is linear for x≤x0 and is also linear for x≥x0 but with a different slope. For example, Read More »
Source: http://www.answers.com/topic/linear-piecewise-regression-model
More Common Questions
Answers to Other Common Questions
I'm not sure what level you are at so it is difficult to recommend a website. A model is unbiased if the estimated mean value of β2 is equal to the true value of β2, in other words, there is a minimum variance between the two. When you look...
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Source: http://answers.yahoo.com/question/index?qid=20081221075104AAEsZT9
You are wrong, A is not correct answer, I am sure about it. All the answers sound tricky, but D is definitely not a valid assumption. So, the answer is D. But this question does not seem right anyway.
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Source: http://answers.yahoo.com/question/index?qid=20090823190137AA74z8t
looks like all of them to me (D)
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Source: http://answers.yahoo.com/question/index?qid=20111211164236AAsyAt5
R-Square metric assumes that there is a Gaussian error added to the measured y values, and produces a model that is simple to evaluate. If your errors follow a different distribution, you may want to use a more complicated model, Of you mig...
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Source: http://www.experts-exchange.com/Q_23359374.htm
There are many possible reasons. Here are some of the more common ones: The underlying relationship is not be linear. The regression has very poor predictive power (coefficient of regression close to zero). The errors are not independent, i...
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Source: http://wiki.answers.com/Q/Why_are_your_predictions_inaccurate_usi...
Classical assumptions for linear regression include the assumptions that the sample is selected at random from the population of interest, that the dependent variable is continuous on the real line, and that the error terms follow identical...
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Source: http://answers.yahoo.com/question/index?qid=20081214141108AANoTC4
The value depends on the slope of the line.
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Source: http://wiki.answers.com/Q/What_is_true_about_the_y-intercept_in_t...
