These data come from a case-controlled study to examine the potential relationship between age at first pregnancy and cervical cancer. In a case-control study a random sample of cases (i.e. people with the disease in question) and controls (i.e. people similar to those in the case group, except they do not have the disease) and the proportion of people with some potential risk factor are compared across the two groups. In this study we will be comparing the proportion of women who had their first pregnancy at or before the ages of 25, because researchers suspected that an early age at first pregnancy leads to increased risk of developing cervical cancer. The data is presented in the table below: Age at First Pregnancy 25 Cervical Cancer 42 7 Control 203 114 Which graph is an appropriate graph to represent this data?

Question

These data come from a case-controlled study to examine the potential relationship between age at first pregnancy and cervical cancer.  In a case-control study a random sample of cases (i.e. people with the disease in question) and controls (i.e. people similar to those in the case group, except they do not have the disease) and the proportion of people with some potential risk factor are compared across the two groups.  In this study we will be comparing the proportion of women who had their first pregnancy at or before the ages of 25, because researchers suspected that an early age at first pregnancy leads to increased risk of developing cervical cancer.  The data is presented in the table below:

Age at First Pregnancy <=25	Age at First Pregnancy>25
Cervical Cancer	42	7
Control	203	114

Which graph is an appropriate graph to represent this data?

BlackTom AI · Accepted Answer

This question is asking which graph best represents the comparison of two groups (cases with cervical cancer and controls) across two categories of a risk factor (age at first pregnancy ≤25 vs >25). 
Option analysis: 
- Clustered bar graph: In this plot, you place the two categories of the risk factor (≤25 and >25) on the x-axis, and for each category you display two side-by-side bars representing the proportions or counts for cases and controls. This layout makes it straightforward to compare the relative frequency of exposure (early age at first pregnancy) between cases and controls within each category, which is precisely what a case-control study aims to illuminate. It also preserves the binary nature of the risk factor and the dichotomy of disease status in a readable, comparative format. 
- Other graph types (in general considerations): A pie chart would misrepresent the comparison between groups by focusing on proportions within a single category and would not facilitate direct cross-group comparisons across the two exposure categories. A simple histogram could be used for a single variable distribution but would not clearly juxtapose cases and controls across the exposure strata. A stacked bar chart could show totals per category but may obscure the direct comparison between cases and controls within each exposure level, potentially biasing interpretation of the association. 
In summary, the clustered bar graph is the most appropriate choice because it cleanly displays two disease groups across the two exposure categories, enabling direct visual comparison of the proportions in cases versus controls within each age-at-first-pregnancy group.

STAT_3615_20055_202501 Mod 9 HW Chi Squared Tests

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