Normal probability plots, Applied Statistics

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

1701_Normal Probability Plots.png

As the P value is 0.005 it is less than the 0.05 significance level therefore reject H0 and accept H1 as there is sufficient evidence to suggest 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.

Posted Date: 3/4/2013 5:13:09 AM | Location : United States







Related Discussions:- Normal probability plots, Assignment Help, Ask Question on Normal probability plots, Get Answer, Expert's Help, Normal probability plots Discussions

Write discussion on Normal probability plots
Your posts are moderated
Related Questions
The following table shows the results of fitting a linear regression model of starting annual salaries on a constant, GPA (4 point scale), and a variable (Metrics =1) indicating wh

Discriminant analysis (DA) helps to determine which variables discriminate between two or more naturally occurring groups. Mathematically equivalent to MANOVA, it ' is extensively

Having 11 numbered balls -0 to 10 -into a basket and have 6 spaces to be numbered with the balls selected in each 6 chances and it returned it back to the basket each time. Chanc

Lorenz Curve   It is a graphic method of measuring dispersion. This curve was devised by Dr. Max o Lorenz a famous statistician.  He used this technique for wealth it i

Consider an MBA program as a processing network where the flow unit consists of a student in the program.  Suppose the organizations that hire and promote MBAs are considered to be

Examples of grouped, simple and frequency distribution data

Scatter Diagram The first step in correlation analysis is to visualize the relationship. For each unit of observation in correlation analysis there is a pair of numerical value

Correlation Analysis Correlation Analysis is performed to measure the degree of association between two variables. The measure is called coefficient of correlation. The coeffic

The weight of the engine in kN is given in P2 and is suspended from a vertical chain at A. A second chain round the engine is attached at A, with a spreader bar between B and C. Th

Let X 1  and X 2  be two independent populations with population means μ 1  and  μ 2  respectively. Two samples are taken, one from each population, of sizes n 1  and n 2  re