Fitting a linear trend to 36 monthly data points (January 2000 = 1, February 2000 =2, March 2000 = 3, etc.) produced the following tables. Coefficients Standard Error t Statistic p-value Intercept 222.379 67.35824 3.301438 0.002221 9.009066 3.17471 2.83776 0.00751 df SS MS F p-value Regression 1 315319.3 315319.3 8.052885 0.007607| Residual 34 1331306 39156.07 Total 35 1646626 The projected trend value for January 2003 is _
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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