Statistical Data Analysis Course - Level 1


Enhance your data analysis skills

Many professionals, project/progamme managers, graduate and post graduates students struggle with statistical data analysis, yet programmes/projects always demand for these practical skills. This course is designed to break these barriers in using statistical approaches and enhance one's knowledge and skills in statistical data analysis

Course Aim

The aim of the course is to build the capacity of professionals, project /programme managers with practical skills on the appropriate application of statistical methods in data analysis.

Who Can apply?

Are struggling with statistical data analysis? This course targets professionals in all fields including health, education, social sciences, business and agriculture among others. Project/progamme managers, monitoring and evaluation persons, graduate and post graduates students who would like to improve their skills on the practical application of statistical techniques in their respective fields can apply. 

Course Outline

  1. Introduction to data analysis using SPSS: Description of types of data, variables, Use of , SPSS Interface, data view, data entry, data cleaning, How to import external data into SPSS, how to recode and data transformation.

  2. Univariate analysis: descriptive analysis based on the type of data, appropriate use of frequency distributions, measures of central tendency and variation, measure of relative standing, data presentation, use of boxplots, histograms and bar charts.

  3. Bivariate analysis: The process of selecting an appropriate statistical test. The process of hypothesis testing. Application of T-tests (One sample t-test, Paired T-test and independent test). Use of correlations and chi-square tests. Interpretation results from statistical analysis.

Course duration

3 days, the course recognizes that many that would be participants cannot take a week off from work to study. The course is designed for only three (3) days, and the learners will make maximum use of their time and gain the required knowledge and skills.

2018 Training Dates

Month Fulltime Class (Dates) Evening Class (Dates)
March 6th-8th 12th-15th
May 8th-10th 21st-24th
July 3rd-5th 16th-19th
September 4th-6th 17th-20th
November 13th-15th  

Eighteen thousand Kenya Shillings (KES 18,000), the fee covers tuition fees, lunch (fulltime option), tea and snacks, water, training materials and certification.

Contact us on: Amref International University 

Department of Community Health Practice
P. O. Box 27691 - 00506 Nairobi, Kenya

Call Vivian or Lilian:  +254-20-6993000/ 6993205 or Cellphone +254 7413871

Click here to apply online, OR

Click here to download the application form (in MS Word)

Testimonials – Statistical Data Analysis

  • The course gave me a lot of confidence in data analysis
    Participant, May 2017 Class
  • The course is very elaborate and informative. It is also well structured and delivered very well by the facilitator. It is very applicable in real life
    Participant, December 2016
  • The course was very helpful as it is useful in academic research as well as work-related data analysis
    Participant, November 2016
  • The course will be very useful in an upcoming survey in our County, it has built my skills in statistical data analysis right from development of data collection tools all the way to report writing and use of data to inform decision making.
    Sub-county Statistician, Makueni County, September 2016
  • The course is very useful to students writing their research theses and projects
    Participant, May 2016
  • The course was delivered in a way that was very easy to understand
    Participant, March 2016
  • I thought the course was difficult but the facilitator made it very simple
    Participant, June 2015

Upcoming Trainings

19.Mar.2018 - 30.Mar.2018
Monitoring and Evaluation (2 Weeks)
09.Apr.2018 - 12.Apr.2018
Statistical Data Analysis Course - Level 2
09.Apr.2018 - 20.Apr.2018
Monitoring and Evaluation (2 Weeks)
16.Apr.2018 - 20.Apr.2018
Fundraising and Resource Mobilization