We use time series analysis/tools to do forecasting. Regression analysis methods are also used for forecasting problems as we saw in the previous chapters. Which one do you think is the best approach to apply for forecasting; time series analysis or regression models? Why? Justify your answer in detail.

We use time series analysis/tools to do forecasting. Regression analysis methods are also used for forecasting problems as we saw in the previous chapters. Which one do you think is the best approach to apply for forecasting; time series analysis or regression models? Why? Justify your answer in detail.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Consider the following passage: I ran a regression, with many variables to predict the result of another variable which was the murder rate. One can see that lots of things, can cause the murder rate to increase or decrease. I tried to account for all the important factors, and those factors are the SAT scores, unemployment rate, and international migration per 1,000. The SAT score is, average combined total score participants did on the SAT exam. The unemployment rate is, "a measure of the prevalence of unemployment and it is calculated as a percentage by dividing the number of unemployed individuals by all individuals currently in the labor force." (Wikipedia) International migration per 1,000 is, the number of people who come into a state from other countries per 1,000 people who live in the state. After I run the regression I will look at the t scores and p values and I should hopefully conclude that international migration does not cause crime. Which writing mistakes, if any, did…
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