Chapter 11
... The MLE in the “no-X” case (Bernoulli distribution), ctd: The theory of maximum likelihood estimation says that pˆ MLE is the most efficient estimator of p – of all possible estimators – at least for large n. (Much stronger than the Gauss-Markov theorem). This is why people use the MLE. STATA n ...
... The MLE in the “no-X” case (Bernoulli distribution), ctd: The theory of maximum likelihood estimation says that pˆ MLE is the most efficient estimator of p – of all possible estimators – at least for large n. (Much stronger than the Gauss-Markov theorem). This is why people use the MLE. STATA n ...
Faculty - The University of Texas at Austin
... adding them up, and dividing the total by the number of MBA graduates. In practice, it is too expensive and time consuming to obtain every MBA salary, which means in practice, that we cannot determine µ exactly. The important point to understand from this discussion is that the population mean µ is ...
... adding them up, and dividing the total by the number of MBA graduates. In practice, it is too expensive and time consuming to obtain every MBA salary, which means in practice, that we cannot determine µ exactly. The important point to understand from this discussion is that the population mean µ is ...
Chapter 1
... be roughly equal. Although it is possible for their means to differ by chance alone, we would expect large differences between sample means to occur very infrequently. Therefore under the Null Hypotheses we assume that the experimental manipulation (advertisement) has no effect on the participants, ...
... be roughly equal. Although it is possible for their means to differ by chance alone, we would expect large differences between sample means to occur very infrequently. Therefore under the Null Hypotheses we assume that the experimental manipulation (advertisement) has no effect on the participants, ...
class exam II review
... 2. (a) Find the relative maximum and relative minimum f (x) = 2x3 − 3ax2 where a > 0 is a constant. (b) what is the inflection point of the graph? Solution: (a) f 0 (x) = 6x2 − 6ax . Set equal to zero. 6x2 − 6ax = 0 gives 6x(x − a) = 0 so the critical numbers are 0 and a f 00 (x) = 12x − 6a f 00 (0) ...
... 2. (a) Find the relative maximum and relative minimum f (x) = 2x3 − 3ax2 where a > 0 is a constant. (b) what is the inflection point of the graph? Solution: (a) f 0 (x) = 6x2 − 6ax . Set equal to zero. 6x2 − 6ax = 0 gives 6x(x − a) = 0 so the critical numbers are 0 and a f 00 (x) = 12x − 6a f 00 (0) ...
Sum of the reciprocals of famous series: mathematical connections
... A perfect power is a positive integer that can be expressed as a power of another positive integer. More formally n it is a perfect power if there are natural numbers m > 1 and k > 1 such that n = mk. In the case in which k=2 we will have the perfect squares, in the case of k=3 we will have the perf ...
... A perfect power is a positive integer that can be expressed as a power of another positive integer. More formally n it is a perfect power if there are natural numbers m > 1 and k > 1 such that n = mk. In the case in which k=2 we will have the perfect squares, in the case of k=3 we will have the perf ...
Chapter 7
... 54. Assume the given sample data below is being used to estimate the population proportion, and calculate the margin of error: The confidence level is 90% and out of 690 trials 298 were successful. 55. Assume the given sample data below is being used to estimate the population proportion, and calcul ...
... 54. Assume the given sample data below is being used to estimate the population proportion, and calculate the margin of error: The confidence level is 90% and out of 690 trials 298 were successful. 55. Assume the given sample data below is being used to estimate the population proportion, and calcul ...
German tank problem
In the statistical theory of estimation, the problem of estimating the maximum of a discrete uniform distribution from sampling without replacement is known in English as the German tank problem, due to its application in World War II to the estimation of the number of German tanks.The analyses illustrate the difference between frequentist inference and Bayesian inference.Estimating the population maximum based on a single sample yields divergent results, while the estimation based on multiple samples is an instructive practical estimation question whose answer is simple but not obvious.