Final Project
GEA 1000

Part A : Section 1
 The aim of the study.
The study aimed to compare trends in vaccine confidence in different demographic groups before
and after the pandemic by analyzing the results of two online surveys conducted in
November/December 2019 and January/February 2022 with 1009 participants.
 Main Independent variable: Year/Time
 Measured as time over the two online surveys run respectively in November/December 2019 and
January/February 2022
 Main Dependent variable: Vaccine Confidence
 The Vaccine Confidence Score (VCS) was calculated by converting the answers to 5 Likert-type questions
to a numerical value (1 point for Strongly Disagree to 5 points for Strongly Agree), and therefore ranges
from 5 (lowest confidence) to 25 (highest confidence).
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The main findings of this study
 Non-parametric tests highlighted a statistically significant decline in vaccine confidence in the 2022 cohort compared to
the 2019 cohort, with median Vaccine Confidence Score dropping from 22 to 20 and 23.8% of participants reporting that
their confidence in vaccines had declined since the onset of the pandemic.
 The subjects and quantity of the research：
 Individuals who were age 18 and above. There were a total of 1009 subjects (739 subjects in 2019 and 270 subjects in
2022 ). Subjects studied ended up being majority female, white, young adults.
 Target population for vaccine study：
Individuals, above the age of 18, who had a change in their vaccine confidence level after the COVID-19 vaccinations
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Section 2i
 Our study was an Observational Study
Confounders controlled by researchers:
Age, Identified Gender, Religious/Spiritual Belief, Graduate Status, Ethnicity.
Graduate Status is a potential confounder because it is associated with vaccine confidence,
potential increased education and awareness of vaccines effect and results, and associated with
time.
Potential confounders -- Attitude on vaccinations
It is associated with vaccine confidence and associated with time.
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Section 3
 Subject selection process used by researchers.
 Participants were recruited by a non-probability sampling method - snowball sampling -
by sharing the survey link on multiple social media platforms and emailing to
appropriate contacts on the investigators mailing list.
 The choosing of suitable contacts in the investigators’mailing lists may also lead to
selection bias. Moreover, the study also showed that there was a majority of female,
white, young adults who participated in the study, which shows that the study was
biased.
 Notice：Do not know how many referrals were sent throughout the study.
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Hypothesis testing is involved
Null hypothesis: There is no significant difference in vaccine confidence between 2019 and 2022.
Alternate hypothesis: There is significant difference in vaccine confidence between 2019 and 2022.
They did have sufficient evidence to reject that null hypothesis.
Non-parametric tests highlighted a statistically significant decline in vaccine confidence in the 2022
cohort compared to the 2019 cohort, with median Vaccine Confidence Score dropping from 22 to 20
and 23.8% of participants reporting that their confidence in vaccines had declined since the onset of
the pandemic.
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The strengths and limitations of the
design of the Study
 All are acknowledged by the researchers
 Strengths
 Both surveys used the same recruitment and allocation methods, and cohort demographics and
trends in vaccine confidence were broadly comparable between the two.
 The study effectively provided a snapshot of two comparable population samples before and after
the COVID-19 pandemic.
 limitations
 The composition of the two cohorts was not necessarily identical or representative of the broader
population.
 Did not provide a longitudinal view of the same cohort's opinions before and after the pandemic.
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Assuming that the conclusions are unreliable,
can such research be promoted to the target
population?
 Hypothesis testing is unreliable, and the snowball sampling
method does not represent the entire population well because
it may have introduced bias.
 Further investigation is needed to confirm to what extent the
decline in vaccine confidence observed between the two
cohorts investigated in this study represents different
populations/countries. Therefore, so far, the findings cannot
be generalized to the target population.
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Part B - Data Analysis
 Numerical variable : Production Budget, Worldwide gross, Domestic gross,
Duration, IMDb rating, Voter numbers, Metascore, Opening weekend(Domestic
Gross)
 Categorical variable : Title, Release, MPAA rating, Genre

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The value of the median is far from the mean, indicating that the
distribution is skewed to the right and asymmetric. So we can determine
that it is more appropriate to use the interquartile range and median to
describe the dispersion and spread of the data.

Statistical expression graph
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Animation movies are the shortest
on average, whereas biographies
have the longest average duration.
Adventure movies have the largest
spread.

Production budgets are positively association with total global
revenue. The independent variable is the production budget, and the
dependent variable is global total income.
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R =0.69928

Data cleaning done
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For MPAA rating - G :
R= 0.57157
For MPAA rating - Not Rated :
R=0.4513

Another shows
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For MPAA rating - PG : R= 0.59858
R= 0.77142
For MPAA rating - R :
For MPAA rating - PG 13 :
R=0.54037
Within each subgroup, there is still a positive correlation
between global gross and production budget. Compared to
the overall association, the strength of the association
between two variables still differs when divided into
subgroups. The strength of the association is strong overall
and moderate when broken down into subgroups. For an
MPAA rating of PG13, it is stronger than the overall
association.

Imdb rating vs Domestic gross

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There is positive association between the imdb
rating and the domestic gross