The Islamic University of Gaza
Faculty of Commerce
Department of Economics & Applied Statistics
Course: Time Series Analysis Dr. Samir Safi
Describe the important characteristics of the autocorrelation func
April, 25, 2008. Exam 2 for S156: Applied time series analysis
1. (a) The following AR(2) model was fitted to a time series of size 30. Explain why the fitted
model is stationary.
ar1 ar2 intercept
Estimate 0.51 0.07
SE 0.18 0.18
May, 16, 2002. Final Exam for S156: Applied time series analysis
Below, cfw_at denotes a sequence of iid random variables with zero mean and finite variance a2 > 0.
1. Let Z1 , Z2 , , Z100 be an MA(2) process: Zt = (1 + 0.5B 0.2B 2 )at . Listed bel
Apr., 2, 2001. Exam 2 for S156: Applied time series analysis
Below, cfw_at denotes a sequence of white noise with zero mean and finite variance a2 = 1.
1. For each of the following ARIMA(p,d,q) model, what are the values of p,d and q. Furthermore,
March, 4, 2008. Exam 1 for S156: Applied time series analysis
1. In this question, we consider an annual series of hare abundance from 1905 to 1935. The data
are square root transformed.
(a) The data appear to be cyclical. Visually estimate the p
Final Examination for S156: Applied Time Series Analysis, Spring,94.
Instructions: This is a CLOSED book exam but you are allowed to have a sheet of paper with formulas,
definitions,.,etc., written on both sides. Examination time is two hours. There
Feb., 25, 2002. Exam 1 for S156: Applied time series analysis
Below, cfw_at denotes a sequence of iid random variables with zero mean and finite variance a2 = 1.
1. Let (Zt )t=0,1,2, be a stationary time series with zero mean, variance equal to 2 a
March, 13, 1995. Exam 2 for S156: Applied time series analysis
1. State whether each of the following model is stationary and/or invertible. Explain your answer briefly. (It suffices to verify the conditions for stationarity and invertibility for th
Solo'lToqs 4w— Ezww Q
Statistics 6201: Fall 2015: Test 2 Statistics 6201: Name
When taking this quiz i agree to follow the Honor Code of the George Washington University
1.(15) Let U be a Uniform random variable on [0,1]. Fin
1. Let X and Y be random variables with nite means. Find a function g (X) such
min E (Y g(X)2 = E (Y g (X)2 ,
where g(x) ranges over all functions.
E[Y g(X)]2 = E[(Y E[Y |X]
Statistics 6201: Fall 2015
From the problems at the end of Chapter 1 in the textbook:
Problems: 1.26, 1.27, 1.33, 1.38, 1.39 and 1.41
1. A single card is randomly selected from a standard deck of 52 cards. From the remainin