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Faculty of Health, Medicine and Life Sciences1 Instructions how to write a short report for the seminar
assignments (see chapter 13)
During each of the eight seminars as scheduled in this module, we (the seminar teacher and you)
will discuss the content of the report. Prepare before each seminar (individually) a report of the
results of all assignments (including the multiple choice questions). Note that a justification
should be given for all multiple choice question. Only giving the answer is not sufficient. You
will be asked to present your answers/findings shortly. Therefore, be sure that the report is
readable for others. Copy the questions in your report for ease of presentation.
- Answer the questions in detail as stated in the assignment and motivate your answers
(multiple choice questions as well).
- If a data analysis is required with a clear research question and if it is stated in the
assignment, then also summarize the analysis according to the following steps (it is not
the intention to write a scientific paper with background information and references etc.).
o Formulate the main research problem and design (shortly).
o What method/statistical technique did you use and why (shortly)
o Report your results/findings. Only include the necessary SPSS output.
o Give an overall conclusion in light of the research question.
2
BBS1003 Syllabus 2020-2021 202020
, Faculty of Health, Medicine and Life Sciences
2.1 Week 2
2.1.1 Seminar 2.1 assignments
Don’t forget watching the videos!
Statistical concepts to be discussed: RR vs. OR, Cross table, expected values, chi-square
statistic
Problem 1
What measure of association is most suitable to express the strength of the relation between
one independent binary variable and one dependent continuous variable (see e.g.
https://www.youtube.com/watch?v=6pIG4W8wPzE) ?
a. Pearson correlation
b. Relative risk
c. Odds ratio
d. Chi-square
Answer:
A continuous-level variable (ratio or interval data) and a binary variable.
Binary variables are variables of nominal scale with only two values. Pearson
correlation is the best to compare a dependent variable (the y value) and an
independent variable (the x value) since it results in a linear relationship.
Problem 2
What measure of association is most suitable to express the strength of the relation between
two continuous variables?
a. Pearson correlation
b. Relative risk
c. R-square of a regression analysis
d. Both options a. and c.
Answer:
Pearson’s correlation coefficient (r) measures the strength of the linear relationship between
two variables on a continuous scale. R-square is a statistical measure of how close the data are
to the regression line. Linear regression can be used for two continuous variables.
Problem 3
For which design(s) is it meaningful to calculate a relative risk?
a. A cohort study
b. A case-control study
c. An experiment with two conditions and a binary outcome
d. For both the designs at a and c
Answer:
Cross-sectional data may serve to calculate relative risks from prevalence’s. Cohort study
designs allow for the direct calculation of relative risks from incidences. It is more
complicated for case-control studies (if meaningful prevelances or incidences are not
BBS1003 Syllabus 2020-2021 212121
, Faculty of Health, Medicine and Life Sciences
available, the OR provides the best effect measure). The relative risk is the ratio of the
probability of an outcome in an exposed group to the probability of an outcome in an
unexposed group (: the two conditions), relative risk measures the association between the
(un)exposure and the outcome (:binary outcome).
Problem 4
For which design(s) is it meaningful to calculate an odds ratio?
a. A cohort study
b. A case-control study
c. An experiment with two conditions and a binary outcome
d. For all of the designs above
Answer:
OR are most commonly used in case-control studies, however they can also be used in cross-
sectional and cohort study designs as well (with some modifications and/or assumptions). In a
cohort study, the odds ratio us then defined as exposed divided by unexposed. The OR
measures the strength between to events (two conditions) similar to RR.
Problem 5
The chi-square test statistic for independence, compares the observed frequencies to
a. the frequencies that are expected if there is no relation between 2 variables
b. the frequencies that are expected if there is a relation between 2 variables
c. the frequencies that have been observed in another, comparable study
d. the frequencies that have been observed in another, completely different study
Answer:
The Chi-square test of independence works by comparing the observed frequencies to the
expected frequencies if there was no relationship between the two categorical variables (the
null hypothesis).
Problem 6
The chi-square test statistic for a contingency table, can be calculated to examine the relation
between:
a. two continuous variables
b. one continuous and one categorical variable
c. two categorical variables
d. one continuous and one binary variable
Answer:
The Chi-square test of independence is used to determine if there is a significant relationship
between two nominal (categorical variables. The data can be displayed in a contingency table
where each row represents a category for one variable and each column represents a category
for the other variable. Categorical variables are independent.
Problem 7
In a study rats were randomized into one of two conditions, one condition in which the rats
were put on a restricted diet, and one in which there were no restrictions in this respect (“ad
libitum”). For each rat it was registered whether the lifespan was less than 2 years (yes or no).
The data are as follows:
BBS1003 Syllabus 2020-2021 222222
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