STATISTICS SHORT COURSES FROM 4TH TO 8TH NOVEMBER 2019 TO BE HELD IN SUALISA CONFERENCE ROOM AT iAGRI BUILDING-SUA MAIN CAMPUS

Sokoine University of Agriculture Laboratory for Interdisciplinary Statistical Analysis (SUALISA) would like to announce to the SUA community and to the general public that it will offer short courses in statistics between 4th NOVEMBER up to 8th NOVEMBER  2019. 

At the same time SUALISA wishes to announce the departure of statisticans from UDOM who have been here since July 2019 and the coming of new statisticians  from Mzumbe Univeristy who will stay until February next year. Our offices will be open from 8am up to 2pm. You are all welcomed!

Registration for the short course

The registration fee is 30,000/=Tshs, per a day. Registration would be made upon your arrival in a venue at iAGRI building. Please notice that the fee does not cover cost for lunch. Each peson will cover his/her own cost for lunch.

Contact   Maria Celestine via the following address to confirm your participation. 
Email:   mary.b.celestine@gmail.com
Mobile: 0713-301033

Who should attend?
Any scholar/researcher such as a  postgraduate student /instructor/production manager/an enterpreneur/lab technician   e.t.c  is highly encouraged to attend. You are all welcomed to attend.

How you will benefit from the course(s)
Each course will provide participants with practical skills to be able to effectively implement a real-life related problem needing statistical skills application.

Venue
The venue for all of these courses would be in iAGRI building

Absract
Statistics find its way in all walks of life.There is no discpline in life that does not need statistics! SUALISA is dedicted to promote the use of Statistics at SUA and to the general public. This time  around sample size calculation, survey designs and  multiple linear regression will be taught. Multiple linear regression (OLS) is perherps the most used model and also forms the basis of all other models in Statistics. However its successive use depends on how its assumptions are met.

  • Do you know the assumptions?
  • How sensitve are the assumptions if not met?
  • When are the results valid or invalid?  

Please come and learn/discuss one of the interesting topics in Statistics. Apart from mutple linear regression a couple of models will be taught including time series models, which are so crucial to scholars, business companies and investors.


You are warmly welcomed !