STA 300 covers the statistical methods in Descriptive and Inferential Statistics that can be used in answering research questions in Food Science and Nutrition. In descriptive statistics it covers areas in data presentation, mean and standard deviation. It also covers measures of association like Regression and correlation. In the area of Inferential Statistics the course will cover estimation and test of hypothesis, nonparametric statistical methods and analysis of variance (ANOVA). The course also covers probability distributions like binomial distribution, Poisson distribution, geometric distribution, hypergeometric distribution and chi-square distribution. We will also make use of the SPSS statistical software to carry out data analysis in ANOVA, nonparametric methods and test of hypothesis in addition to performing calculations in these areas.
The technologies we will use for this course include internet access to http://hostclass.academy.zoom.us and to http://hostclass.net/courses/ These sites require a working email and a stable internet connectivity, though they can operate on low bandwidth (e.g. minimum of 600 kbits/sec is typically sufficient, if this minimum bandwidth is stable).
Course Guidelines and materials, Open/Close times
This online course is built on a bi-weekly framework of material. Notes and class recordings will typically be posted during the week. Assignments may be completed and submitted at any time during the week they are due.
Posted course materials, including slide for the lectures, and recordings of the synchronous lectures, will remain open throughout the month. In this fashion, students who are unable to attend the lectures for technical or personal reasons, such as unexpected difficulties with information technology, personal or family illness, or the need to become a family caretaker, will have access to all the same class materials as students who attend the lectures.
- To join HostClass’ online classroom, a monthly fee of N1000 is required to cover your access and maintain your space on HostClass for this course. Click on this link to pay online http://hostclass.courses/
- To get started visit our Web page http://hostclass.net and click on “Student” to subscribe for HCSTAT 300
- After Successful payment, Register for your course HCSTAT 300 to enable you have access to join the zoom class with your lecturer and attend the classes https://hostclass-academy.zoom.us/meeting/register/tJIrdumopz8uE9JU7skIQP33OPu-eVoIEcUu
- After the above step is done, you will automatically receive a mail that Automatically gives you the link to join the class, click on the link where you find “CLICK HERE TO JOIN” and it will take you to the learning platform
- Feel free to let us know in which ever way you are encountering challenges in the registration process through this platform; 08134135683 or email [email protected]
Attendance is expected and encouraged in all Tuesday and Friday lectures. Excuses for absences are not required. Friday class time is reserved for each of the instructors to engage in office hours in a virtual group setting with students from their respective sessions.
Feedbacks and Communications
- All course announcements will be made in the http://hostclass.academy.zoom.us or Hostclass platform. Please check http://hostclass.net regularly, and please view the lecture recordings when you miss a lecture.
- The best way to contact your instructors is via their work emails: [email protected].ng or [email protected] Please give us typically up to 24 hours for email response. Response times may be longer over weekends.
- Please *do not* reply to mass emails sent via [email protected], you should create an email with a new subject line if and when you wish to respond to mass emails.
There will be two assignments for this course and they will be submitted on or before the specified due date. All homework is to be turned in on [email protected]
The schedule below is **tentative and subject to change**. It is given as an indication of pace only.
Week 01: Mean and Standard Deviation
Week 02: Regression Analysis
Week 03: Correlation Analysis
Week 04: Estimation (1)
Week 05: Estimation (2)
Week 06: Test of hypothesis (1)
Week 07: Test of hypothesis (2)
Week 08: Nonparametric methods
Week 09: Analysis of Variance (1)
Week 10: Analysis of Variance (2)
Week 11: Statistical Analysis (Test of hypothesis)
Week 12: Statistical Analysis (Analysis of Variance)
Week 13: Statistical Analysis (Nonparametric methods)
Week 14: Probability (1)
Week 15: Probability (2)