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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.
Empirical Mode Where mode is ill-defined, its value may be ascertained by the following formula based upon the empirical relationship between Mean, Median and Mode: Mode = 3
What is an example of a real life situation when I would use each of these test
Perform clustering of the unlabeled data set. You could use provided initial centroids set or generate your own. Also there could be considered next stopping criteria : - maxim
Read the following data on the economy of Angoia and answer/respond to the questions/instructions that follow. Unless otherwise stated, the monetary figures are in real billions o
limitations of time series analysis
Application of the chi Square Test
who invented the chi square test and why? what is central chi square and non central chi square test? what is distribution free statistics? what are the conditions when the chi squ
Examine properties of good average with reference to AM, GM, HM, MEAN MEDIAN MODE
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Assume that a simple random sample has been selected from a normally distribute population and test the given claim. Identify the null and alternative hypotheses, test statistic,
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