20 Series: Residuals Sample 2000M01 2013M04 Observations 160 16 - Mean 4.75e-16 12 Median 0.051482 Maximum 2.085097 Minimum -2.342896 Std. Dev. 1.221305 Skewness -0.181759 Kurtosis 1.897905 Jarque-Bera 8.978390 Probability -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 0.011230 Which of the following do you conclude? Select one: O A. There is evidence that the regression residuals are normally distributed at the 1% level B. There is evidence that the regression residuals are not normally distributed at the 1% level O C. There is evidence that the regression residuals are uniformly distributed O D. There is evidence that the regression residuals are right skewed
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
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