Kolmogorov-smirnov - normal probability plot, Applied Statistics

Assignment Help:

The Null Hypothesis - H0:  The random errors will be normally distributed

The Alternative Hypothesis - H1:  The random errors are not normally distributed

Reject H0: when P-value ≤ α = 0.05

109_Normal Probability Plots2.png

As the P value is 0.043 it is less than the 0.05 significance level therefore reject H0 and accept H1 as there is sufficient evidence to show that random errors are not normally distributed.  The assumption of normality is possibly satisfied as the normal probability plot is close to the straight line.


Related Discussions:- Kolmogorov-smirnov - normal probability plot

Standard gaussian random variable , You will recall the function pnorm() fr...

You will recall the function pnorm() from lectures. Using this, or otherwise, Dteremine the probability of a standard Gaussian random variable exceeding 1.3.  Using table(), or

Carry out a t-test, Suppose that before the minimum wage law change, the un...

Suppose that before the minimum wage law change, the underlying mean number of part-time employees per Burger King Restaurant in New Jersey was 20.3. It was thought that the increa

Linear programming problem, Melissa Bakery is preparing for the coming than...

Melissa Bakery is preparing for the coming thanksgiving festival. The bakery plans to bake and sell its favourite cookies; butter cookies, chocolate cookies and almond cookies. A k

Classical and modern regression, The data in the data frame asset are from ...

The data in the data frame asset are from Myers (1990), \Classical and Modern Regression with Applications (Second Edition)," Duxbury. The response y here is rm return on assets f

Agreement, Agreement The degree to which different observers, raters or ...

Agreement The degree to which different observers, raters or diagnostic the tests agree on the binary classification. Measures of agreement like that of the kappa coefficient qu

Factor analysis, Factor analysis (FA) explains variability among observed r...

Factor analysis (FA) explains variability among observed random variables in terms of fewer unobserved random variables called factors. The observed variables are expressed in

Compute the roughness of several parametric densities, An approximation to ...

An approximation to the error of a Riemannian sum: where V g (a; b) is the total variation of g on [a, b] de ned by the sup over all partitions on [a, b], including (a; b

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd