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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
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.
If the test is two-tailed, H1: μ ≠ μ 0 then the test is called two-tailed test and in such a case the critical region lies in both the right and left tails of the sampling distr
Other Measures of Dispersion In this section, we look at relatively less used measures of dispersion like fractiles, deciles, percentiles, quartiles, interquartile range and f
Jocko's Garage has been accused of insurance fraud. Data on estimates made by Jocko and another garage were obtained for 10 damaged vehicles (available in 'jockogarage.txt'). Here
Primary and Secondary Data: Primary Data: These data are those are collected for the first time. Thus primary data are original in character and gathered by actual observat
Simple Random Sampling In Simple Random Sampling each possible sample has an equal chance of being selected. Further, each item in the entire population also has an equal chan
why we use dummy variable
Large Sample Test for Proportion A random sample of size n (n > 30) has a sample proportion p of members possessing a certain attribute (success). To test the hypothesis that t
Type of Variable in Regression Analysis There are two types of variable in regression analysis. These are: a. Dependent variable b. Independent variable
BCBSRI was able to reduce MSD related Workers Compensation cases with lost workdays by implementing a New Ergonomic Program in March 2000 and increasing workstation evaluations. Ex
How can we analyse data with four bilateral response variables measured with errors and three covariated measured without errors?
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