SUALISA (Sokoine University of Agriculture Laboratory for Interdisciplinary Statistical Analysis)

Transcription

1 SUALISA (Sokoine University of Agriculture Laboratory for Interdisciplinary Statistical Analysis) 2014/2015 Annual Report 20 th January 2016

2 Executive Summary SUALISA was founded in 2014/2015as the result of an initiative led by Professor Eric Vance of Virginia Tech University. Professor Vance is the Director of LISA (Laboratory for Interdisciplinary Statistical Analysis) and the leader of the Laboratory for Interdisciplinary Statistical Analysis (LISA) 2020 program that aims to create STATs labs in 20 developing countries worldwide by the year Due to the shared objectives between SUALISA and the Innovative Agricultural Research Initiative (iagri) and the existing partnership with Virginia Tech and iagri, SUALISA was created in the iagri annex building on the SUA campus. For the first month in the initial phases of its operation only two SUALISA collaborators were available to staff the lab, Dr. Benedicto Kazuzuru and Emanuel Msemo. Later on, the lab began to attract more visitors and by November of 2014, the lab had 9 collaborators (including one LISA ambassador from Virginia Tech University). While the majority of collaborators come from the Department of Biometry and Mathematics, there are also some from the Department of Biological Science, Animal Science and the Development Studies Institute (DSI). Two of the collaborators are PhD students and are now fully occupied with their studs. The LISA ambassador from Virginia Tech has returned to the US leaving the lab with six effective collaborators. The lab would aim to recruit more collaborators (about 10) for the academic year 2015/2016. Through the LISA 2020 program and with iagri assistance, and Emanuel Msemo were supported with training in the US and later officially established the lab on 9 th December In addition, Mr. Richard Ngaya from the department of Biometry and Mathematics is also currently undergoing training in the US. The LISA 2020 program brought Adam Edwards, a PhD candidate in Statistics at Virginia Tech, as the first LISA ambassador. Edwards worked collaboratively with SUALISA team between May and November In addition, the LISA 2020 program supported Emanuel Msemo to attend the World Statistical Congress (WSC) Conference in Rio de Janeiro, Brazil where he presented a paper on Impacting Agricultural Productivity in Tanzania through the Wheels of Statistics. SUALISA has managed to attract 295 visitors from different departments at SUA and has carried out more than 50 collaboration projects. SUALISA also conducted a series of short course training sessions in statistics offering a total of six short courses. SUALISA faces a number of challenges including limited funds, inexperienced statisticians, and insufficient collaborators able to work in the lab. After one year experience, SUALISA leadership is planning a number of strategies to overcome the observed challenges. These include increasing the number of collaborators and number of ports for SUALISA services and continuing to build the capacity of collaborators by linking SUALISA with other universities offering statistical services. Despite the challenges facing SUALISA, the lab has attracted a large number of clients. The vast majority report a positive experience and impression of SUALISA services. Currently, 99% of 1

3 clients interviewed report that SUALISA should continue to exist and should be strengthened to continue to provide training and consultation services. Clients have also made a number of suggestions for improving the services of SUALISA. Most clients suggest that the SUALISA team should be encouraged to be involved in key academic issues such as in thesis defenses and /or postgraduate presentation seminars. Others suggest that part of the postgraduate fees should be allocated to SUALISA and/or individual students should pay directly for SUALISA services. Front Cover Photos: September 2013, Professor Eric Vance during a visit to Sokoine University of Agriculture Kazuzuru, Benedicto and Msemo, Emmauel, SUALISA Annual Report , Sokoine University of Agriculture (SUA): Morogoro, Tanzania,

4 Contents Executive Summary... 1 Collaborators... 4 Introduction and Mission... 8 LISA Activities and progress in 2014/ Walk-in consulting Figure 1: Percentages of Walk-in Visitor s by Department Collaboration Projects Determinants of land Conservation Technologies Adoption by Rural households in Tanzania Short courses Challenges Facing SUALISA Future plans The SUALISA success story What should be done to improve SUALISA services? Contacts:

5 Collaborators Dr. Benedicto Kazuzuru, Coordinator Emanuel Msemo, Assistant Coordinator Lead Collaborators Dr.Telemu Kassile Dr.Charles Lymo Andrew Rogers Zabron Nziku Nziku Associate Collaborators Zakile Mfumbilwa Edwin Daniel Athumani Nguluma LISA Ambassador to SUALISA Adam Edwards Agness Kapinga (left) was the third SUALISA client. She graduated on time partly because of SUALISA services. She reported a very positive view of SUALISA and supports the idea that SUALISA should be strengthened. 4

6 Hawar Dunor (right) was the first SUALISA client for the year 2014/2015. She also graduated on time partly due to SUALISA services. On the left is Zakile Mfumbilwa, SUALISA collaborator. 5

7 Andrew Rogers (right), SUALISA collaborator 6

8 Some members of SUALISA team (left to right): Dr.Telemu Kassile, Head of the Department of Biometry and Mathematics, Dr.Magesa from University Centre for Information and Communication Technology, Dr. Charles Lymo from the Biological Science Department. Front (left to right) Mr. Emanuel Msemo, Assistant Coordinator of SUALISA,, Coordinator of SUALISA 7

9 Introduction and Mission The Sokoine University of Agriculture Laboratory for Interdisciplinary Statistical Analysis (SUALISA) was endorsed by the University Senate on the 17 th of March 2014 and formally began its operations on the 9 th December of The establishment of SUALISA was an initiative made by LISA 2020 at Virginia Tech (USA), a program that aims to establish 20 statistical laboratories in 20 developing countries by the year So far, through LISA 2020, five statistical labs have been established in three developing countries (Nigeria, Tanzania, Ethiopia and Brazil). The SUALISA is the 2 nd statistical collaboration laboratory (stat lab) in the LISA 2020 Network. The first was the LISAC (Laboratory for Interdisciplinary Statistical Analysis and Collaboration) at Obafemi Awolowo University in Ile-Ife, Nigeria. Stat labs, including SUALISA, are intended to offer advice to researchers (postgraduate students, instructors, NGO s, Governments and Ministries) on how they can best collect and analyze data to support their research. The LISA 2020 program, under the leadership of Professor Eric Vance, convinced SUA s leadership, the Faculty of Science and the Department of Biometry and Mathematics to establish a collaborative statistical laboratory. This idea was warmly received by all stakeholders and further supported by iagri. There were a number of motivating factors for SUA to establish a statistical laboratory. First, even though most and PhD supervisors in the university departments have been trained in statistics, their knowledge is usually confined to a particular discipline. This is a disadvantage when supervising a student whose work is outside of that discipline. For example, a research supervisor may have trained in experimental designs, but not in time series data or in econometrics. A statistical lab has the advantage of gathering together statisticians from different disciplines and allows SUA students to benefit from a variety of statistics approaches. Another reason is that although statistics is taught as a discipline to students to help them in their main discipline of study, students rarely have time to practice. Also, the statistical packages provided to students are not sufficient to teach theoretical implications of the methods they use. Therefore, a statistical lab that offers short course training in the practical applications of statistics, would greatly improve the practical statistical knowledge of graduate students. Even though statistical training is given in most universities in Tanzania, the art of statistical collaboration is never taught to students. As a result most statisticians lack the skills and techniques provided by statistical collaboration. The establishment of statistical collaboration laboratories not only teaches young statisticians how to practice their disciplines, but also on how to collaborate. Collaborative skills obtained by working in a stat lab, increases not only research abilities, but also marketability to companies as employees. Apart from the stated motives for establishing statistical collaboration laboratories, there are associated benefits of having a stats lab at SUA. Through the improvements of statistical techniques for data collection and analysis, graduate students and researchers/research institutions produce higher quality research outputs that could be published in higher impact journals. The improvement in research capabilities could also lead to earlier completion of 8

10 degree programs by graduate students at SUA. During the University Senate meeting of 17 th March 2014, the establishment of the statistical lab was endorsed and established with a mission to increase knowledge and application of statistics among SUA undergraduate, postgraduate and academic staff members as well the general public in Tanzania. Specifically SUALISA was given the following responsibilities: (i) (ii) (iii) (iv) (v) (vi) (vii) To establish collaboration between SUA and Virginia Tech on statistical issues To train statisticians to the required level of competency for delivering training and consultancy services in statistics To implement the collaborative mission between SUA and other universities dealing with statistical training and consultancies for researchers/research institutions To provide sensitization workshops/seminars to SUA academic staff and students as well as the public and private research institutions staff on the importance and use of statistical knowledge for problem solving and effective research To provide walk-in consulting to SUA students and staff To deliver short course training in statistics and in statistical packages to graduate students and researchers at SUA and employees in the public and private sectors To offer commissioned consultancy services in statistics and statistical applications This report summarizes SUALISA s main activities for the 2014/2015 academic year. In addition to providing documentation on achievements over the previous year, the report addresses challenges faced and outlines five main goals for the 2015/2016 academic year. LISA 2020 SUALISA is the second statistical lab to be established in the LISA 2020 program. The LISA 2020 program provides initial training to statisticians in developing countries on how to create and manage statistical labs, then sends ambassadors to those labs and maintains regular communication for further advice and for any new developments in the LISA 2020 program. Although part of the 2020 network, SUALISA maintains its own autonomy similar to the other labs in Nigeria, Ethiopia and Brazil. Professor Eric Vance, the LISA Director at Virginia Tech University is the founder and a prominent figure in the LISA 2020 program. He visited Tanzania in 2013 and The 2013 visit was meant to explain the premise of the stats lab to SUA leadership and to ultimately convince SUA about the importance of having a statistical lab. After SUALISA was established, Prof. Vance visited Tanzania again in 2015 to oversee the progress of the lab and to offer further advice for SUALISA. He also visited a number of institutions in Tanzania including the University of Dar es salaam, the East African Statistical Training College, the National Bureau of Statistics, the Ministry of Agriculture, and the embassies of Sweden and Finland. Following his visit in 2013, SUA sent Dr. Benedicto Kazuzuru to train in the US at Virginia Tech University on the LISA 2020 program in Facilitating the creation and operation of a statistical lab was the key focus of the program. Emanuel Msemo also joined during the visit. 9

11 Msemo completed an in Statistics from Virginia Tech University through support received from iagri. Richard Ngaya is another collaborator from SUA who is training on the LISA 2020 program. Ngaya also is studying an in Statistics at Virginia Tech and will complete his studies in September In addition to these activities with SUALISA, Professor Vance also conducted visits to other developing countries (Ethiopia, Nigeria and Brazil) where statistical labs were initiated under LISA Some members of SUA community listening to Professor Vance (not in the picture) on the importance of having a statistical collaboration laboratory at SUA From left to right: Professor Vance, Dr. Urrasa, (and (right) 10

12 in Washington, DC during his visit to the US Emanuel Msemo outside Hutcheson Hall at Virginia Tech 11

13 From left to right, Zakile Mfumbilwa, Emanuel Msemo, Adam Edwards and Dr.Benedicto Kazuzuru 12

14 Activities and Progress in 2014/2015 SUALISA offers three main types of services: (i) Walk-in Consulting (ii) Collaboration Projects (iii) Short Course Training in Statistics. A walk-in consultancy service is a quick consultation service in statistics. It is offered daily from Monday to Friday depending on specified hours. The service is offered from 11am to 1pm in a single port located at the iagri building on SUA s main Campus. A collaboration project is distinguished from walk-in consulting in the sense that a project involves input and discussion from both the collaborator and the researcher whereas walk-in consulting involves a client that receives instruction from the collaborator. A walk-in demands relatively less time and is normally concluded within 30 minutes. A needs assessment shows an increasing trend of clients seeking both walk-in consulting and collaboration projects. SUALISA has served nearly all the departments of SUA with walk-in services and collaboration projects. Walk- in Consulting Animal Science Biological Crop Science and Production DAEA DSI Education Engineering Epidemiology Extension Food Science Forest Biology Forest Economics Forestry biology Forestry Biology Forestry Economics Forestry Science Microbiology Figure 1: Percentages of Walk-in Visitor s by Department 13

15 DSI FOA FOFNC FOS 42.3 VET Figure 2: Percentages of Walk-in Visitor s by Faculty/Institute 39.4 F 60.6 M Figure 3: Percentages of Walk-in Visitor s by Sex 14

16 Figure 4: Weekly trend of clients visiting the lab from 9/12/2014 up to 31 st December 2015 Figure 4 indicates weekly trends of clients since when the lab was established (9/12/2014) up to the 30 th of December The figure shows first an increasing trend of clients coming to the lab later followed by a decreasing trend, suggesting a unimodal distribution of the number of clients. Figure 5: Monthly trend of clients visiting the lab from January 2015 to December

17 Even though this is a one year observation, Figure 5 above suggests that clients reach their peak between May and June. More observations in the future would be needed to confirm this observation. Table 1: Time Table for Walk-In Consulting (11am-1pm) for 1 st, 3 rd &5 th semesters- 2014/2015 Venue: IAGRI annex building opposite the SUA Nursery School Monday Tuesday Wednesday Thursday Friday Rogers Andrew Mobile: Edwini Daniel / Dr. Telemu Kassile Mobile: Emanuel Msemo Mobile: Zakile Mfumbilwa Mobile: Dr. Benedicto Kazuzuru mobile: Table 2: Time Table for Walk-In Consulting (11am-1pm) for 2 nd, 4 th & 6 th semesters- 2014/2015 Venue: iagri annex building opposite the SUA Nursery School Monday Tuesday Wednesday Thursday Friday Edwin Daniel Emanuel Msemo Dr.Telemu Kassile Andrew Rogers Zakile Mfumbilwa Mobile: / Charles Lymo: Mobile: Mobile: Adam Edwards* Mobile: Mobile: Adams Edwards* Mobile: Mobile: Zabron Nziku Mobile: Mobile: Athumani Nguluma Mobile: *Adam Edwards was a LISA ambassador to SUALISA who worked in the lab for one semester. 16

18 Collaboration Projects SUALISA has gone through 58 projects since it was established. In reality, there might have been more than 58 projects, because some of the clients coming in walk in consulting occasionally spend more than 1 hour in consultation with SUALISA collaborators Nevertheless, the projects listed below are ones clients specifically requested for collaboration. The table below provides details including the client s name, education level and names of collaborators involved on the projects for 2014/2015. No. Client Name Project Title Education Level 1 Dunor, Hawa School Based Sex Education MA Programmes and Teenage Pregnancy in Mtwara Region, Tanzania 2 Regina Christopher A Study on Institutional PhD Malima Capacity of Social Protection for Elderly in Mainland Tanzania 3 Loth Msafiri Microfinance Institutions and Women Economic Empowerment in Arumeru District, Tanzania 4 Mlelwa Tito Growth performance and PhD Yield of Nile Tilapia and Chinese Cabbage in Aquaculture Integration 5 Gloria Daniel Kaale Community Knowledge, MA Attitude, Practice and Perception on Mkukuta: A Case Study of Morogoro Municipality And Mvomero District 6 Asha Omar Fakih Agriculture Services MA Support Programme and Socio-Economic Empowerment of Rural Women in Zanzibar, Tanzania 7 Aloyce Mbujilo The Impact of Credit PhD Guarantee Scheme on Agricultural Productivity Among Smallholder Farmers in Tanzania Collaborators & Zakile Mfumbilwa & Zakile Mfumbilwa & Zakile Mfumbilwa & Zakile Mfumbilwa & Zakile Mfumbilwa 8 Kapinga, Agnes Gisbert Impacts of Redd+ Activities to Rural Communities: Livelihood Analysis of Kondoa Advancing Redd+ 17

19 In Kolo Hills Forests Arkfor) Project In Tanzania 9 Ogessa, Catherine Coverage Of Agricultural Information in Tanzanian Newspaper 10 Lymo Clara Economics of Credit Utilization in Paddy Production 11 Chipili, Given Implementation of Nutrition sensitive Agriculture in the Central Province of Zambia 12 Mollel Godfrey Gendered decision making at household level among the small holder community in Arumeru district 13 Hidaya Effectiveness of Private Health Centers In Maternal Health Care in Morogoro District 14 Kinyemi Kigoda Climate Change and the Risk of Trypanosomiasis in Neighboring Communities at Ikorongo-Grumet Game Reserve Serengeti, District 15 Loserian, Morwo Land conflicts between farmers and pastoralists and its implication on gender relations: The case of Mvomero district, Morogoro region. 16 Mlaki Daniel Religious Institutions and Environmental Conservation Efforts 17 Mweta Mjema Sustainability of Community Based Donor Funded Development Projects 18 Emmanuel Hongo Mroto Gender Analysis in the Sunflower Value Chain: A Case Of Mvomero District, Tanzania 19 Joel Elia Mwanga Determinants of Community Participation in planning Hiv and Aids Interventions under National Multisectoral Strategic MA MA MA MA MA MA PhD MA MA & Emanuel Msemo Zakile Mfumbilwa & Emanuel Msemo & 18

20 Framework in Mtwara Region, Tanzania 20 Tenneh, Stephen Newily Kilimo Kwanza and Youth Engagement in Agriculture: Prospects and Challenge in the Kilombero District 21 Suma Fahamu Kibonde Conservation of Medicinal Plants for Managing Hiv/ Aids Opportunistic Infections Around Mount Rungwe Nature Reserve in Mbeya Region, Tanzania 22 Winfrida Vegetable Producers, Traders and Consumers Perception of using Low- Quality Water for Vegetable Production in Morogoro, Tanzania 23 Laizer Thomas Land Tenure system and Land conflicts 24 Mchome, Rehema S Economic Analysis Of Human-Wildlife Conflicts Mitigation Options Around Selous Game Reserve In Kilombero District 25 Nephat Mkula Influence of interaction among actors in production of quality sugarcane in Tanzania. A case of Kilombero Outgrowers Scheme 26 Developing Maize Hybrids Resistant to Maize Lethal Necrosis Disease. 27 David Mauki Genetically characterization of the present Tanzanian dairy cattle reared by smallholder farmers 28 Utoni Nkokelo Consumer acceptability and willingness to pay for selected processed orange fleshed sweet potato (OFSP) products in Morogoro Municipality 29 Lilian Shechambo Management of weed and insect pest in organic production of tomato and sweet pepper MA PhD MA MA Adam Edwards & Dr.Charles Lymo Dr.Charles Lymo & Zakile Mfumbilwa Emanuel Msemo 19

21 30 Japhet Steven Determinants of Consumer's Preferences for Rice 31 Stella Fungo To establish association between lifestyles behaviors of the adolescents and their potential for chronic health risks 32 Martha Tesha Effectiveness of diversification of secondary school education in Tanzania: A case of Agriculture subject curriculum in selected schools 33 Edmund Mutayoba Development of a Framework For Improving Climate Change Model Predictions in Water Resources: A Case Study of Great Ruaha Sub-Basin, Tanzania Probabilistic model frame work 34 Emiliana Asenga Vulnerability to Food insecurity and Copping strategies 35 Nkokelo Utoni Consumer acceptability and willingness to pay for selected processed orange fleshed sweet potato (OFSP) products in Morogoro Municipality 36 Mikail Ali The impact of policy and social economic changes on land cover change and plant diversity in Falgore Game Reverse in Nigeria 37 Eliezeri Sungusia Understanding the technical framing of community based forest management in Tanzania 38 Charles Effectiveness of law enforcement in natural resources 39 Baba Sani Species Diversity and Population Dynamics of Cassava Green Mite (Mononuchellus tanajoa) on Selected Cassava Varieties in Tanzania PhD PhD PhD PhD.. & Edwin Daniel Emanuel Msemo & Zakile Mfumbilwa. Dr. Telemu Kassile. PhD & Emanuel Msemo Adam Edwards & 20

22 40 John Makota The contribution of trophy hunting on rural livelihoods and environmental conservation in Ulanga District-Tanzania 41 John Mwingira Health Risk Assessment of Acrylamide Through Consumption of Potato Chips Among University Students 42 Mfune Ruth Lindizyani Seroprevalence of Bovine brucellosis in smallholder dairy cattle 43 Jimson Mbwiga Classification and Contribution of the Chagga Agriforest Homegardens to Communities' Food, Wood energy, and income likelihood of Rombo District, Kilimanjaro Region Tanzania 44 David Mauki Genetically characterization of the present Tanzanian dairy cattle reared by smallholder farmers 45 Jacob Kiyyo Developing Maize Hybrids Resistant to Maize Lethal Necrosis Disease 46 Mfune Ruth Lindizyani Seroprevalence of Bovine brucellosis in smallholder dairy cattle 47 Agnes Kwaloe Seed health Status of Certified and Farmer's saved rice seed from Morogoro Region 48 Suleiman Atik Improvement of complementary foods for infants and young children (6-23 months) old in seaweed farming livelihood zone 49 Honesmo Serajio Determinants of land Conservation Technologies Adoption by Rural households in Tanzania 50 Nice Wilfred Ntupwa Livelihoods and social economic impact of wetland utilization in recent ASDP Adam Edwards Rogers Andrew & Dr. Charles Lymo & Dr. Benedicto Kazuzuru Dr. Charles Lymo & Dr. Benedicto Kazuzuru Athumani Nguluma and Zabron Nziku Nzuki Dr. Charles Lymo Dr. Charles Lymo Dr. Charles Lymo Dr. Charles Lymo Dr. Charles Lymo PhD PhD 21

23 investments in Tanzania: A case of the kilombero Valley floodplains in Kilombero district. 51 Victor Lazaro Assessment of newly introduced AVRDC technology on Vegetable production 52 Maeda Simon Macro and Micro determinants of Corruption 53 MA. Rural student Factors influencing the use of agricultural input to farmers (the case of Morogoro Rural area 54 Elina Efficacy of Quality Protein Maize-based Supplementary Foods to Support Growth and Rehabilitation of Undernourished Children in Mvomero District, Tanzania 55 Zipporah To improve yield of lowland rice grown in iron toxic soils of Liberia by using high yielding lowland rice varieties with tolerance to iron toxicity. 56 Mary Revelian Contribution of Hunting Tourism to economic growth of Tanzania 57 Aldegunda Matunda Uses of pineapple vinegar on shelf life of carrot and mango in Tanzania MA MA MA Emnuel Msemo & Zakile Mfumbilwa Athumani Nguluma Emanuel Msemo and Andrew Rogers Emanuel Msemo 58 Suzana Samson Regulatory environment and incentives surrounding the use of low quality water in agricultural production. Emanuel Msemo NB. (1) In some cases, we have not been able to fully capture a student name (2) The topics are mentioned in accordance with how the students presented them to SUALISA. This does not mean that the topics maintained the same titles up to the end of the study. 22

24 Short Courses Short course offered in the academic year 2014/2015 Course Title Trainer Date Survey designs Dr. Benedicto Kazuzuru 15 th October 2015 Data management and analysis using SPSS Dr. Benedicto Kazuzuru 20 th October 2015 Calculation of breeding values using R Mr.Zabron Nziku 22 nd October 2015 Introduction to R Zakile Mfumbilwa 27 th October 2015 Experimental Design Emanuel Mbazi Msemo 3 rd November 2015 Time series Design Rogers Andrew 10 th November 2015 Challenges Facing SUALISA Some of the challenges faced by SUALISA are outlined below: (i) Financial Challenges SUALISA is currently being funded by iagri but mainly through the payment of collaborators who work in the lab (15,000 per a day). But SUALISA has a lot of activities that require additional funds. For example, SUALISA could invite experts from other universities to SUA to train SUALISA collaborators on statistical issues. (ii) Lack of enough collaborators It has been very hard for SUALISA to secure collaborators who are willing to work in the lab, partly because the university instructors who are the current collaborators in SUAISA are occupied with other activities. Another reason contributing to this problem is the lack of both undergraduate and graduate students pursuing statistics as their major discipline. These students could have contributed a great deal by working in the lab as part of their training in statistics. (iii)lack of experienced statisticians SUALISA is only able to rely on willing statisticians who are not necessarily well experienced in application of statistics to fields such as Forestry, Agriculture and Veterinary Medicine. As a result, SUALISA clients are not always able to obtain advice on how to solve their research problems in specialized disciplines. SUALISA would like to make a call for senior members in the university s departments to join SUALISA and support clients projects. This could be done by SUALISA sending clients and their projects directly to the volunteers or by SUALISA collaborators consulting directly with experienced academic staff members. (iv) Lack of time by the collaborators Owing to the fact that our collaborators are also university academic staff, they often lack sufficient time to attend to clients in the lab in addition to collaborative projects. This is an issue especially during examinations when additional time is required for invigilation, marking and grading. Contrary to SUALISA, the mother lab (LISA) at Virginia tech rarely uses academic staff for collaboration. Instead, LISA primarily relies upon postgraduate students pursuing advanced degree in statistics ( and 23

25 PhD). These students perform collaborative research as part of their training. Few of them serve as volunteers. In some cases, some collaborators are paid by LISA to finance their studies. This is possible because LISA at Virginia tech is funded by the University and sees LISA as a necessary unit, both for research growth and for the production of high-quality research outputs. (v) Lack of commitment by collaborators and delays in university promises For reasons mentioned previously, some collaborators lack encouragement to work in the lab. On the other hand, University delays in fulfilling commitments is one of the greatest barriers faced by SUALISA. For example, University administration has delayed to fulfill a commitment to provide an administrative secretary. This is despite an agreement with iagri to fund the employee for a period of one year. (vi) Lack of cooperation from the University Supervisors One of the roles of SUALISA is to coordinate those with statistical knowledge to disseminate it to those in need. By offering statistical consultative services, SUALISA does not imply that this advice is final. If a university supervisor finds that the advice is incorrect, SUA supervisors should explain how it can be improved. Some students have expressed that advice obtained from SUALISA collaborators has been rejected by their supervisors who provide no further explanation. Other supervisors feel undermined when his/her student obtains consultative services from SUALISA. These negative attitudes prevent collaborative learning and problem solving that is meant to assist students in their research. SUALISA is not a person but rather a unit mandated by the university to offer statistical advice, to willing students, instructors and others. We call upon all university supervisors to contact SUALISA for an open discussion if the advice provided to students is in question. This open communication would enhance both the knowledge of SUALISA collaborators and of the supervisors themselves. Future Plans The following are the main goals of SUALISA for 2015/2016 (1) Securing additional ports for offering SUALISA services. SUALISA operates in the iagri building located a few meters away from the SUA administration block. This location is strategically located for students in the Faculty of Forestry, the Development Studies Institute and Veterinary Science. SUALISA plans to secure another port between the Engineering Department and the Animal Science Department to easily reach students from these disciplines. In addition, another port at Mazimbu Campus is being planned to meet the needs of postgraduate students at the SUA Mazimbu Campus. (2) Additional university collaborations. SUALISA plans to establish linkages with other universities in addition to Virginia Tech University. SUALISA is already in contact with the Statistical Service Center of Reading University as well as their Research Methods Support team to see how we may collaborate on various statistical issues including the training of SUALISA statisticians. (3) Short-term training. SUALISA aims to preparing and conduct training workshops/seminars in the future for SUA academic staff and students as well as public 24

26 and private research institutions staff on the importance and use of statistical knowledge for problem solving and effective research work. (4) Additional staff. SUALISA will recruit 10 more collaborators to work in SUALISA in the coming year. (5) Commissioned services. SUALISA will be implementing a plan to secure commissioned services in statistics to increase the sustainability. The SUALISA Success Story SUALISA activities can only be evaluated by SUALISA clients who use the services. In a survey conducted between November and December 2015, 200 clients were reached through and were asked 3 questions about their experiences with SUALISA. The first question asked whether or not the SUALISA services are helpful? The second question asked whether or not SUALISA should continue to exist? Third question asked how SUALISA helped their research. (i) Are SUALISA services helpful? Figure 5 (i): 25

27 (ii) Should SUALISA continue to exist? Figure 5(ii): (iii)how has SUALISA helped you in your research? Figure 5 (iii): 26

28 What should be done to improve SUALISA services? Figure 6 Contacts: 1. Dr. Benedicto Kazuzuru bwenke.1999@yahoo.com; kazuzuru@vt.edu; kazuzurub@gmail.com ; Mobile: Emanuel Msemo kakunya@vt.edu Mobile: ;