probability runcuon probability density runcuon Pix) '0') O 1 2 3 4 4O 60 80 120 160 X-exampiemumber of cigarettes X-examplemeight (mm) Pictured above are the plots of the pmf of a discrete random variable and the plot of the pdf of a continuous random variable. For each of the following variables, determine what might be an appropriate model to fit to data if you had data on it. The number of electric scooters left per block of a Los Angeles street. Choose... A metaanalysis of sequential clinical trials was done to obtain a data set containing a variable that measures, for each trial, how many patients that got treatment it took to get the first that got seriously ill with the treatment. Note: a sequential clinical trial is one in which , the patients in the treatment group are not all given the treatment at once but rather sequentially: first one patient, observe, then Choose___ another patient, observe, etc... A metaanalysis is an analysis of many research articles to gather information on all of them and conduct analysis of the results of all. A variable measuring the number of students in a random sample of 20 from California who know what the "Bill of Rights" is Choose... Body temperature of humans Choose... 3 The duration of the period when an electric scooter is idle and awaiting the next customer Choose... The proportion of hours in a given day that a train arrives late to a train station Choose... e of the variable that could be modeled as a model. For "duration" which, according to the codebook, means duration of diabetes in months, I would estimate the parameter , since many factors affect the onset of diabetes. Perhaps I would also model age as women and men (which are the only gender identified in this trial) have different distributions and it could be that the distribution of age is duration because this is a The Diabetes Control and Complications trial was a trial that had a lot of consequences for diabetes management. It established that intensive glucose measuring and constant management of insulin delivery helped decrease the long term effects of diabetes. A few lines and variables are given below. Match the variable with the parameter and model you would estimate using that data, meaning that you are assuming that the probability model would be the right one for that variable. Notice that we are using the notation used in the lectures and our textbook. For the "adult" variable I (meaning you) would estimate the parameter model. With that parameter I then estimate a model for the number of patients that are adult in a random sample as large as that participating in the trial, which is a random but I am not so sure of that, because it is possible that Im- retbase adult EXPERIMENT 2 SEND D 17 178 STANDARD 2 SEND 1 23 142 STANDARD 2 SEND 1 35 175 EXPERIMENT 2 PRIM D 14 31 EXPERIMENT 2 SEND 1 32 72 STANDARD 2 SEND 1 26 106 STANDARD 2 SEND 1 26 168 EXPERIMENT 2 SEND 1 28 147 EXPERIMENT 2 SEND 1 37 14 STANDARD 2 SEND 1 23 80 STANDARD 2 SEND D 13 148 STANDARD 2 PRIM D 13 3D STANDARD 2 SEND 1 21 126 STANDARD 2 SEND 1 27 116 EXPERIMENT 2 SEND 1 38 133 STANDARD 2 PRIM 1 37 38 EXPERIMENT 2 SEND 1 27 4D STANDARD 2 SEND 1 23 61 EXPERIMENT 2 SEND 0 17 77 EXPERIMENT 2 SEND 1 22 35 STANDARD 2 SEND 1 25 168 EXPERIMENT 2 SEND D 14 71 EXPERIMENT 2 PRIM 1 28 27 STANDARD 2 SEND D 1.5 107 p Bernoullli Binomial $$\\mu$$ Continuous Gaussian Gaussian bimodal geometric negative binomial Poisson Exponential Choose... Beta Exponential Hypergeometric Normal Poisson Binomial Negative Binomial Geometric