Method of Detection Effects of the Departures/Violations on Assumptions violations on the Remedial Measures Graphical Statistical model 1. The values of the regressors, the X's, are not fixed or random, or X values are not independent of the error term. 2. There is exact linear relationship or exact collinearity between the X variables. 3. For given X's, the mean value of disturbance ɛ, is not equal to zero. 4. For given X's, there is autocorrelation, or serial correlation, between the disturbances. 5. The number of observations n is less than or equal to the number of parameters to be estimated. 6. The model is incorrectly specified, so there is specification bias. 7. There are errors in the measurement of variables of the model.
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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