Since that fateful and chilly dawn of April 15, 1912, the
world has witnessed the construction of larger ships, some already dismantled
or lying, solitary, in the darkness of the bottom of the oceans and others
still in circulation. However, no other ship has become as famous and
significant for popular naval and imaginary history as the Royal Mail Ship
Titanic. The RMS Titanic joined the imagination of the navy, literature, and
cinema. It fed the dreams and nightmares of generations, from the one from 1912
who was perplexed to receive the news of the disaster to the present generation
that has it in the ambivalence of an engineering feat of its time, as well as a
fruit of the arrogance of its creators.
Its history is known to all and its data is used in many studies. It should be
mentioned that these data are composed of records of various variables and
various natures. In addition, they are easily generalizable to several other
situations.
In this study, the researchers will make use of the regression models. This
model is one of the most important statistical tools in data analysis when the
objective is to study relationships between variables, or more particularly, to
analyze the influence that one or more variables (explanatory variables) may
have on a variable of interest (response variable).
The purpose of this study is to describe in detail the construction of this
type of model using a dataset on the Titanic tragedy. Not forgetting the
limitations. Understanding these limitations is crucial for making informed
decisions about when and how to use linear regression and when alternative
methods might be more appropriate.
Author(s) Details:
Maria Nascimento Cunha,
Instituto Superior de Educação e Ciências (ISEC Lisboa -Portugal),
Member of the Scientific Council of CIAC – Centro de Investigação de Artes e
Comunicação, Portugal.
Jorge Figueiredo,
Universidade
Lusíada de Famalicão, Portugal.
Isabel Oliveira,
Universidade Lusíada do Porto, Portugal.
Macaes, Manuel,
Universidade Lusíada do Porto, Portugal.
Please see the link here: https://stm.bookpi.org/RATMCS-V9/article/view/13324
No comments:
Post a Comment