# Biostatistics, MS (PSM Program)

## Student Outcomes

- Outcome MS-B Written Communication
- Outcome MS-C Statistical Modeling for Continuous Response
- Outcome MS-D Statistical Modeling for Categorical Response
- Outcome MS-E Consolidating Data
- Outcome MS-F Sampling Plan
- Outcome MS-G Sample Size Determination

## 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.#### 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.#### 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.#### 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.#### 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.#### 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.#### 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.