Poisson distribution - Study guides, Class notes & Summaries

Logistic Regression - Commonly used for modeling binary response data. The response variable is a binary variable, and thus, not normally distributed. In logistic regression, we model the probability of a success, not the response variable. In this model, we do not have an error term g-function - We link the probability of success to the predicting variables using the g link function. The g function is the s-shape function that models the probability of success with respect to the predict...

1. Question: A coin is flipped 30 times. What is the probability of getting 15 or more heads? Round answer to 4 decimal places. 2. Question: It is known that 50% of adult workers have a high school diploma. If a random sample of 8 adult workers is selected, what is the probability that less than 6 of them have a high school diploma? 3. Question: If random variable X has a binomial distribution with n=9 and P(success) =p= 0.4, find the standard deviation of X. 4. Question: If random variable X...

ISYE 6414 Final Exam Questions and Answers Already Graded A 1. If there are variables that need to be used to control the bias selection in the model, they should forced to be in the model and not being part of the variable selection process. True 2. Penalization in linear regression models means penalizing for complex models, that is, models with a large number of predictors. True 3. Elastic net regression uses both penalties of the ridge and lasso regression and hence combines the benefits ...

1. Question: Suppose a random variable, x, arises from a binomial experiment. If n = 14, and p = 0.13, find the standard deviation. Round answer to 4 decimal places. 2. Question: A coin is flipped 30 times. Find σ². Round to 1 decimal place. 3. Question: It is known that 50% of adult workers have a high school diploma. If a random sample of 6 adult workers is selected, what is the probability that 3 or more of them have a high school diploma? 4. Question: Suppose a random variable, x, arise...

Factor Based Models classification, clustering, regression. Implicitly assumed that we have a lot of factors in the final model Why limit number of factors in a model? 2 reasons overfitting: when # of factors is close to or larger than # of data points. Model may fit too closely to random effects simplicity: simple models are usually better Classical variable selection approaches 1. Forward selection 2. Backwards elimination 3. Stepwise regression greedy algorithms Backward elimination...

1 A website simulates the outcome of throwing four fair dice. Ten thousand people take part in a challenge using the website in which they have one attempt at getting four sixes in the four throws of the dice. The number of people who succeed in getting four sixes is denoted by the random variable X. (a) Show that, for each person, the probability that the person gets four sixes is equal to 1 . [1] (b) Explain why you could use either a binomial distribution or a Poisson distribution to mo...

The discrete random variable A takes only the values 0, 2 and 4, and has cumulative distribution function F(a) ¼ P(A  a) a 0 2 4 F(a) 0.2 0.6 1 Find P(A ¼ 2) Circle your answer. [1 mark] 0 0.4 0.6 0.8 2 The time, T days, between rain showers in a city in autumn can be modelled by an exponential distribution with mean 1.25 Find the distribution of the number of rain showers per day in the city. Tick (3) one box. [1 mark] Distribution Mean Exponential 0.8 Exponential 1.25 Poisso...

Factor Based Models classification, clustering, regression. Implicitly assumed that we have a lot of factors in the final model Why limit number of factors in a model? 2 reasons overfitting: when # of factors is close to or larger than # of data points. Model may fit too closely to random effects simplicity: simple models are usually better Brainpower Read More Previous Play Next Rewind 10 seconds Move forward 10 seconds Unmute 0:01 / 0:15 Full screen Classical var...

Actuary Exam 1: 2 of 3 Questions & Answers 2023/2024 What distribution would you use? Number of insurance claims during a given time period. - ANSWER-Poisson What distribution would you use? Number of deaths per year from a given group of people. - ANSWER-Poisson What distribution would you use? Number of mail pieces recieved in a day? Or number of phone calls recieved in a hour? - ANSWER-Poisson What distribution would you use: Suppose on average that a web page gets 2 hits per mi...

ISYE 6501 Midterm 2 Part 1 Latest 2023 Rated A greedy algorithm at each step, the algorithm does the thing that looks best without taking future options into consideration; more classical variable selection methods stepwise - (forward, backward, combination) lasso elastic net available metrics for variable selection criteria p-value r2 AIC / BIC lasso Giving regression a budget to use on coefficients which it uses on most important coefficients Have to scale first elastic net constrain combi...