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My role for this project is Human Resources RepresentativeJob responsibilities: Accomplishes human resource objectives by recruiting, selecting, orienting, training, assigning, scheduling, coaching, counseling, and disciplining employees; communicating job expectations; planning, monitoring, appraising, and reviewing job contributions; planning and reviewing compensation actions; enforcing policies and procedures.or this activity, your group will examine two project management cases […]

Let be iid, each with the distribution having pdf The Pareto distribution is a frequently used model in the study of incomes and has the distribution function Where is a random sample from this distribution, find the maximum likelihood estimators of and . (Hint: This exercise deals with a nonregular case.)

Let be the order statistics of a random sample of size n from the uniform distribution of the continuous type over the closed interval . Find the maximum likelihood estimators for θ and ρ. Are these two unbiased estimators?

Let be a random sample from  (a) If the constant b is defined by the equation  find the mle of b. (b) If c is given constant, find the mle of

The data file normal50.rda contains a random sample of size n = 50 for the situation described in Exercise 6.4.6. Download this data in R and obtain a histogram of the observations. Exercise 6.4.6 Let be a random sample from  (a) If the constant b is defined by the equation  find the mle of b. (b) If

Consider Part (a) of Exercise 6.4.6. (a) Using the data of Exercise 6.4.7, compute the mle of b. Also obtain the estimate based on 90th percentile of the data. (b) Edit the R function bootstrapcis64.R to compute a bootstrap confidence interval for b. Then run your R function on the data of Exercise 6.4.7 to

1. Show that if Xi follows the model (6.4.14), then its pdf is  2. Verify the partial derivatives and the entries of the information matrix for the location and scale family as given in Example 6.4.4. Example 6.4.4

Consider two Bernoulli distributions with unknown parameters  and . If Y and Z equal the numbers of successes in two independent random samples, each of size n, from the respective distributions, determine the mles of  and  if we know that

Suppose are iid  Show that Xi follows a location and scale family as given in Example 6.4.4. Obtain the entries of the information matrix as given in this example and show that they agree with the information matrix determined in Example 6.4.3. Example 6.4.4

Suppose the pdf of X is of a location and scale family as defined in Example 6.4.4. Show that if  then the entry  of the information matrix is 0. Then argue that in this case the mles of a and b are asymptotically independent. Example 6.4.4