Assignment | Study on Cancer

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Introduction
Background
Over the past two decades, cancer has grown to become a major health concern throughout the
world and the 2nd leading cause of death in the United States second only after heart disease
(Siegel, Miller, & Jemal, 2019). (Miller, et al., 2019) reports that in 2019 alone, lung cancer and
bronchus cancer has caused the deaths of up to 76, 650 and 66, 020 males respectively while on
the other hand, up to 41,760 females have died of breast cancer. In an effort to answer various
questions surrounding cancer, WHO sponsored a symposium held in 1950 aimed at
understanding the dynamics of cancer in which it was learned that, “...people who migrated to
other countries, developed types of cancer common to their adopted countries, rather than their
homelands” (Blackadar, 2016).
In a study on the different types of cancer, (Siegel, Miller, & Jemal, 2019) posit that currently,
there are over 100 known types of cancer. Generally, there have been extensive studies that have
been conducted in an effort to learn this modern scourge, as will this paper. Other studies on the
factors that affect the probability of suffering from cancer indicate that one of such factors is age.
According to (Aunan, Cho, & Søreide, 2017), “... aging is the inevitable time-dependent decline
in physiological organ function and is a major risk factor for cancer development.” Another
factor associated with cancer disparity among victims is gender as argued by (Kim, Lim, &
Moon, 2018) who study differences in the development of cancer in relation to epidemiology,
underlying genetics, and therapy. The primary argument proposed by (Kim, Lim, & Moon, 2018)
is that cancer to some extent is related to the genetics of an individual i.e. males are likely to
develop cancer in their lifetime compared to the likelihood of their female counterparts to
develop cancer. The view held by (Kim, Lim, & Moon, 2018) is supported by (Tevfik, 2017)

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who notes that, “...Epidemiological evidence consistently shows that males have a higher
susceptibility to non-sex-specific cancers.”
Based on the literature provided above, this paper will particularly study the relationship between
cancer (the dependent variable) and two independent variables i.e. Age and Gender.
Variable Description
The final project dataset includes a number of variables, nevertheless only the following will be
used in relation to the paper’s research problem.
Dependent variable
As noted in the previous section, this paper will adopt the cancer variable as the dependent
(response) variable. From the supplied dataset, the dependent variable is binomial i.e. it has two
classes which include: 0 (indicating the participant does not have cancer) and 1 (indicating the
participant has cancer).
Independent variables
Similarly, the study uses age and gender as explanatory variables. On the very basic, gender
includes 2 binomial entries with two classes i.e. 0 (indicating that the participant is male) and 1
(participant is female). On the other hand, Age is conceptually a continuous variable as noted in
the supplied dataset where the age of the participants ranges from 18 to 65.
Problem Statement
Gender and age as posited from the discussion provided in the background section are among the
different factors that have been posited to have a relationship with cancer. The objective of this
study will, therefore, be the exploration of this supposition. In order to prove or disprove the
original arguments i.e. that there is a relationship between cancer and age as well as gender, this
paper will seek to answer the following question:

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Research Question
Is there a relationship between Cancer, gender and age?
To answer the research question, the following hypotheses will be tested:
Null Hypothesis
The development of cancer in an individual is independent of their gender or age i.e. there is no
relationship between cancer, age, and gender.
Alternative Hypothesis
There is an association between cancer, age, and gender.
Given the type of research question and hypotheses adopted for this paper, the most appropriate
test that will be used to use both correlation and binomial logistic regression to test for
association between the three variables and whether there is a causal relationship between
cancer, gender, and age. The null hypothesis, in this case, will be tested at a 0.05 level of
significance and rejected if the p-value of regression is below 0.05.