Biostatistics, MS (PSM Program)
Student Outcomes
Assessment of Student Outcomes
Outcome MS-B Written Communication
Biostatistics graduates will be able to effectively communicate in a
manner typically required by a biostatistician. Graduates can
effectively communicate scientific observations, analyses, and arguments
in a written format.
Objective 1
Students will effectively communicate scientific observations, analyses,
and arguments in a written format.
Measure 1
2022 Status
Achieved
Data were collected in Winter 2022. Data indicate the objective was met.
2021 Status
Achieved
Data were collected in Winter 2020 (STA 630 is only offered in winter
terms, and assessment data were not collected in Winter 2021 due to
covid). The data indicate the objective was met.
2019 Status
Achieved
Data were collected in Winter 2019.
2018 Status
Achieved
Data were collected in winter 2018.
Outcome MS-C Statistical Modeling for Continuous Response
Biostatistics graduates will be able to develop and interpret
statistical models.
Objective 1
Students will be able to develop, assess and interpret statistical
models associating relevant predictors with a continuous response.
Measure 1
2021 Status
Not Yet Achieved
Data were collected in Fall 2021 (STA 621 is only offered in fall terms,
and assessment data were not collected in Fall 2020 due to covid). The
data indicate the objective was not achieved.
2019 Status
Not Yet Achieved
Data were collected in Winter 2019.
2018 Status
Achieved
Data were collected in fall 2017.
Outcome MS-D Statistical Modeling for Categorical Response
Biostatistics graduates will be able to develop and interpret
statistical models.
Objective 1
Students will be able to develop, assess and interpret statistical
models associating relevant predictors with a categorical response.
Measure 1
2022 Status
Achieved
Data were collected in Winter 2022. Data indicate the objective was met.
2021 Status
Achieved
Data were collected in Winter 2020 (STA 623 is only offered in winter
terms, and assessment data was not collected in Winter 2021 due to
covid). The data indicated the objective was achieved.
2019 Status
Achieved
Data were collected in Winter 2019.
2018 Status
Achieved
Data were collected winter 2018.
Outcome MS-E Consolidating Data
Biostatistics graduates will be able to combine multiple data sets and
prepare these data for analysis.
Objective 1
Students will be able to effectively merge information from multiple
data sources and prepare these data for statistical analysis.
Measure 1
2022 Status
Achieved
Data were collected in Winter 2022. Data indicate the objective was met.
2021 Status
Achieved
Data were collected in Winter 2020 (STA 616 is only offered in winter
terms, and assessment data were not collected in Winter 2021 due to
covid). The data indicate the objective was met.
2019 Status
Achieved
Data were collected in Winter 2019.
2018 Status
Achieved
Data were collected in winter 2018.
Outcome MS-F Sampling Plan
Graduates have the ability to design and implement a sampling (or
randomization) plan.
Objective 1
Students will be able to demonstrate the ability to identify the study
design employed in the scenario and develop a randomization strategy
that can be used to randomly assign treatments to subjects.
Measure 1
2022 Status
Achieved
Data were collected in Winter 2022. Data indicate the objective was met.
2021 Status
Achieved
Data were collected in Winter 2020. The data indicate the objective was met.
2019 Status
Achieved
Data were collected in Winter 2019.
2018 Status
Achieved
A scenario was given to the biostatistics students that requires the
students to identify the study design employed in the scenario,
ascertain the potential statistical methodology that will ultimately be
utilized to analyze the data, and develop a randomization strategy that
can be used to randomly assign treatments to subjects.
2018 Status
Achieved
A scenario was given to the biostatistics students that requires the
students to identify the study design employed in the scenario,
ascertain the potential statistical methodology that will ultimately be
utilized to analyze the data, and develop a randomization strategy that
can be used to randomly assign treatments to subjects.
2017 Status
Achieved
A scenario was given to the biostatistics students that requires the
students to identify the study design employed in the scenario,
ascertain the potential statistical methodology that will ultimately be
utilized to analyze the data, and develop a randomization strategy that
can be used to randomly assign treatments to subjects.
2017 Status
Achieved
A scenario was given to the biostatistics students that requires the
students to identify the study design employed in the scenario,
ascertain the potential statistical methodology that will ultimately be
utilized to analyze the data, and develop a randomization strategy that
can be used to randomly assign treatments to subjects.
Outcome MS-G Sample Size Determination
Graduates have the ability to determine sample sizes necessary to
identify differences of a specified amount with a given probability.
Objective 1
Students will be able to determine the sample size necessary to conduct
a study that will detect a difference of a specified amount with a given probability.
Measure 1
2022 Status
Achieved
Data were collected in Winter 2022. Data indicate the objective was met.
2021 Status
Achieved
Data were collected in Winter 2020. The data indicate the objective was met.
2019 Status
Achieved
Data were collected in Winter 2019.
2018 Status
Achieved
A parametric problem was given to each student that requires them to
determine the sample size necessary to conduct a study that will detect
a difference of a specified amount with a given probability. Each
student will write SAS programs that employ proc POWER to determine the
appropriate sample size. In the end, the students will need to write up
their solutions in the context of the problem.
2018 Status
Achieved
A non-parametric problem was given to each student that requires them to
determine the sample size necessary to conduct a study that will detect
a difference of a specified amount with a given probability. Each
student will write SAS programs that employ proc POWER to determine the
appropriate sample size. In the end, the students will need to write up
their solutions in the context of the problem.
2017 Status
Achieved
A parametric problem was given to each student that requires them to
determine the sample size necessary to conduct a study that will detect
a difference of a specified amount with a given probability. Each
student will write SAS programs that employ proc POWER to determine the
appropriate sample size. In the end, the students will need to write up
their solutions in the context of the problem.
2017 Status
Achieved
A non-parametric problem was given to each student that requires them to
determine the sample size necessary to conduct a study that will detect
a difference of a specified amount with a given probability. Each
student will write SAS programs that employ proc POWER to determine the
appropriate sample size. In the end, the students will need to write up
their solutions in the context of the problem.