SCI1A03_F23_MRI 4_Leading Questions_FINAL
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McMaster University *
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1A03
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Geography
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Dec 6, 2023
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docx
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Uploaded by DrHummingbird3844
Resource B – Leading Questions Worksheet
Group:
Student Names:
By handing this in, you are stating that this was a collective group effort.
Question 1. Discuss the distribution of the total incidence rates for cancer. Try to relate this to specific
regions of Hamilton such as Ancaster, Lower City, etc.
Question 2. Select the LAYERS button and switch to the “Lung Cancer Incidence per 1000 People…”
layer, turning off the “Cancer Incidence per 1000 people…” layer. Next, switch to the “Breast Cancer
Incidence per 1000 People…” layer. Are there any regional differences in incidence between these two
types of cancer?
Question 3. Still viewing the “Breast Cancer Incidence per 1000 People…” layer, apply a filter to the
data: select “Filter By Median Family Income”, “LESS THAN OR EQUAL”, and set the threshold to 60000.
This will hide all regions of Hamilton where the median family income is GREATER than 60000,
allowing us to consider the breast cancer incidence within only those regions where MFI is less than or
1
Saqib Nadeem, Natasha Jaspal, Aemen Obaid, Jennifer Zhu, Ocean Mehata
The incidence rate of cancer is much higher in regions with lower median household
incomes. For example, Ancaster has a median household income between 110,000-
120,000 CAD with an incidence rate of 114 to 119 per 100. However, when looking at
Lower City, it had much higher incidence rates and a much lower median household
income.
Breast cancer incidence is much higher in regions such as Binbrook, Copetown, and
Stoney Creek as opposed to lung cancer incidence. In general, Lung Cancer incidence is
much higher in urban centers/densely populated areas, while Breast Cancer incidence is
spread out more evenly between urban and suburban/less populated areas.
After setting focus on the areas of Hamilton with a median family income of less than
$60000, it can be seen that there is not a strong correlation between income and breast
cancer incidence. For example, one of the regions with the highest breast cancer incidence,
equal to $60,000 (i.e. the poorest regions in Hamilton). What are some observations you can make
from the application of this filter? What is another filter that can be applied in this GIS application to
control for confounding variables?
Question 4. As a group, start to think of some research questions you may want to investigate in the
next tutorial.
Does living in an urban area versus a suburban area have any impact on likelihood
of getting cancer? And if so, what about urban or suburban areas increases the
likelihood of cancer?
What, if any, correlation exists between cancer incidence rates and death rates in
areas of Hamilton with a MFI less than 60,000? How does this correlation compare
to the same correlation between areas with an MFI greater than 60,000?
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