Introducing
DATA ANALYSIS & INTERPRETATION
Data analysis skills are often a rare skill among researchers and students. The majority usually hire a statistician to perform data analysis and remain ignorant to the concepts of data analysis. However, data analysis and interpretation is a valuable skill for researchers and statisticians especially those whose work relating to data analysis is ongoing.
Data Analysis & Interpretation
Course Details
Background
This course is designed to provide the researcher with data analysis and interpretation skills to enable the researcher or statistician utilize and communicate data in a meaningful way.
Rationale
Data analysis skills are often a rare skill among researchers and students. The majority usually hire a statistician to perform data analysis and remain ignorant to the concepts of data analysis. However, data analysis and interpretation is a valuable skill for researchers and statisticians especially those whose work relating to data analysis is ongoing.
Code
DMIFees
K3, 000 per personLocation
OnlineContact
SPSS/GraphPad Prism option: Dr. Sepiso K Masenga, BSc, MSC, CT, PhD STATA option: Mr. BM Hamooya, BSc, MSC, CT, PhD candidateDates
Commencement date: 1st February, 2021Aim
To provide skills and competencies for leaners to be able to code, clean, analyse and interpret data using STATA or SPSS or GraphPad prism
Objectives
At the end of the program Learners should be able to:
- Prepare raw data for analysis
- Understand types of Data and designs
- Perform descriptive statistics
- Know how to perform and interpret statistical tests such as Chi-square, student’s t-test, Wilcoxon rank-sum test, correlation and regression analysis, multiple comparison and analysis of variance etc
- Perform post-hoc analysis and receiver operator curves
- Use either SPSS or STATA or GraphPad prism
Competencies
At the end of this course, learners will be able to do the following:
- Data analysis and interpretation
- SPSS or STATA or Graphpad prism
- Diagnostic tests
Entry requirements
It is encouraged that the candidate must possess a minimum of a degree in any health-related course or be a student or learner at diploma or degree level working on a research project or planning to design a research protocol or analyze data in future.
Expected prior knowledge
Must have conducted or participated in research project before or have some basic knowledge of research activities and what is involved. Beginners are encouraged to take RPD and EDM prior to this course.
COURSE DELIVERY.
Intensive 2 weeks of didactic lectures, hands-on practical and tutorials sessions
QUALIFICATION
Upon successful completion the candidates will be awarded a certificate in Data Analysis & Interpretation. This qualification will only apply to a student who passes the final exam.
Course Content
- Introduction to types of Data
- Descriptive statistics
- Normality tests
- Hypothesis testing
- Parametric tests
- Non-parametric tests
- Diagnostic tests
- Post hoc tests
- Other analysis
- Overview of statistical package software
Lesson Schedule
Day |
Lesson/activity |
Responsible/Lecturer |
Day 1 |
1. Introduction to types of Data 2. Descriptive statistics |
Mr BM Hamooya Dr SK Masenga |
Day 2 |
3. Machine learning |
Mr BM Hamooya |
Day 3 |
4. Normality tests 5. Hypothesis testing |
Dr SK Masenga Mr BM Hamooya |
Day 4 |
6. Parametric tests I |
Dr SK Masenga |
Day 5 |
7. Parametric tests II |
Mr BM Hamooya |
Day 6 |
8. Non-parametric tests |
Dr SK Masenga |
Day 7 |
9. Diagnostic tests |
Mr BM Hamooya |
Day 8 |
10. Post hoc tests & Other analysis |
Dr SK Masenga |
Day 9 |
11. Overview of statistical package softwares |
Dr SK Masenga |
Day 10 |
Exam, Assignments due and Quizzes |
Mr BM Hamooya |
note |
project due 7 days after completion (day 10) |
|
Teaching Methods
Lectures
Hands-on Tutorials
Assignments
Timing and schedules
Monday to Friday
Note: select one option and statistical package (STATA or SPSS/GraphPad Prism) when applying
- Option A: 06:00 – 08:00
- Option B: 10:00 – 12:00
- Option C: 12:00 – 14:00
- Option D: 16:00 – 18:00
- Option E: 18:00 – 20:00
Assessment Method
• Assignment 20%
• Quizzes 20%
• Final Project 60%
Certifications
Mulungushi University certificate will be provided