Instructor’s contact information:

Instructor: Marlen Acosta Alamo

Email: [email protected]

Office Hours (virtual): by appointment. Contact me via email to set up an appointment in Collaborate.

Course description

This is an introductory statistics class focused on the concepts of biological data analyses and on how statistics can help extract scientific insight from data. With the use of real examples from biology and medicine we will learn what statistic methods to use in each case and why. During the course, we will demonstrate how to carry out the calculations for the methods learned and how to implement these methods in the computer program R.

Learning outcomes

• Describe and effectively display your data.
• Describe what statistic test to use and why.
• Perform hypothesis tests.
• Draw biologically meaningful conclusions from the tests results.
• Carry out data analyses using the statistic computer program R.

Structure of online course

This course will be fully online and synchronous, which means that lectures, computer labs and tests will be live, and students will have to log in to Zoom at the time of the class.

Before each class, students must read the textbook pages corresponding to that week’s lecture. The pages for each week’s reading are indicated on the Course Schedule tab under the column called Book Chapter (pages).

Most weeks, we will have in-class activities. These activities can be found on the In-class Activities tab.    

In addition, there will be weekly asynchronous individual homework that you will have to submit via email. Textbook questions and pages corresponding to each week’s homework are indicated on the Course Schedule tab under the column called Homework.

Required textbook

Introductory Statistics for the Life and Biomedical Sciences by Vu and Harrington (2020), 1st edition. This is an Open Educational Resource that is available for free.

Technical requirements

Students will need a laptop, desktop computer or chromebook, as well as internet access to participate in this class.

Students will need to download and install on their computers BOTH free softwares R and RStudio to perform the lab component of the class. Instructions on how to download and install these softwares can be found on the Resources tab.

Technical help resources

For help with R and RStudio installation contact me via email.

Online participation

I expect students to log in Zoom at the time of the class for the live lectures and computer labs and to participate in group activities. I expect students to submit their homework via email by their due dates. Online participation will be assessed by active participation in the synchronous activities.

Communication and turnaround

Students can expect to have grades and feedback for their assignments within a week of their due dates.

Students can contact me via email (email provided above) at any time, my response time is usually within 24 hours.

CUNY Statement on Disability:    Any student with a documented disability may be eligible for reasonable accommodations.  To determine eligibility and to receive related services, students should contact the Center for Student Accessibility. 

Important policies

Absence Policy: According to CUNY policy, more than two unexcused absences (15% of credit hours) results in an automatic failure of the course. If you believe that you will be absent from a class or miss a lab, please contact me (via email) BEFORE the class time.

CUNY Policy on Academic Integrity (From page 61 of the 2017 Student Handbook). Academic Dishonesty is prohibited in The City University of New York and is punishable by penalties, including failing grades, suspension, and expulsion.