494
objectives. A total of 15 participants came from each village with members representing each sub-village, providing a total of 30 people for both villages. The groups
involved village community members and village government leaders, with a balance in gender, wealth and age. The FGD method is effective since it is highly flexible, socially oriented and time saving, gives room to generate new ideas and
provides insights on the current position of the topic at hand (Berg and Lune 2012).
2.5 Data Analysis and Presentation of Results
Information obtained from different sources was analysed using descriptive and
inferential statistical tests. Quantitative data were descriptively computed and presented in the form of percentages, graphs, tables, bar charts, pie charts and line
graphs, with the aid of Statistical Package for Social Sciences (SPSS) and Microsoft
Excel. Prior to quantitative analysis, the household survey questionnaire was coded.
The coding was generated after compiling a list of all responses to ensure that a
single code is applied to each response without repetition, for open-ended questions. A coded template was designed in SPSS software and completed survey questionnaires were transferred into the software for data analysis. Data cleaning was
performed to ensure that data values are complete and accurate. Descriptive data
analysis, cross-tabulation and chi-square statistical analysis were conducted to draw
inferences on the collected data.
Qualitative data were transcribed and organised into discussion topics. Content
analysis of the transcribed data was carried out using Excel. In Excel, data were first
sorted into themes and patterns were generated across themes to show relationships
across key issues, such as education level, age and gender. Differences in views on
climate services and information based on farmers’ education level, age, gender and
income were summarised before analysis and then compared by using the chisquare test (Cronk 2008). The chi-square test of independence was also used to find
out whether two or more attributes were independent (p > 0.05).
3 Results
3.1 Socio-Economic Characteristics of the Respondents
Age of Respondents
The age of respondents in the two study villages of Sanje and Msolwa Ujamaa
showed that 26% of respondents in Sanje and 32% of respondents in Msolwa
Ujamaa were aged between 18 and 35 years, 46% in Sanje and 36% in Msolwa
Ujamaa were aged between 36 and 60, while 28% in Sanje and 32% in Msolwa
Ujamaa were aged above 60 years. These findings indicate that the number of
E. P. Ruth et al.
objectives. A total of 15 participants came from each village with members representing each sub-village, providing a total of 30 people for both villages. The groups
involved village community members and village government leaders, with a balance in gender, wealth and age. The FGD method is effective since it is highly flexible, socially oriented and time saving, gives room to generate new ideas and
provides insights on the current position of the topic at hand (Berg and Lune 2012).
2.5 Data Analysis and Presentation of Results
Information obtained from different sources was analysed using descriptive and
inferential statistical tests. Quantitative data were descriptively computed and presented in the form of percentages, graphs, tables, bar charts, pie charts and line
graphs, with the aid of Statistical Package for Social Sciences (SPSS) and Microsoft
Excel. Prior to quantitative analysis, the household survey questionnaire was coded.
The coding was generated after compiling a list of all responses to ensure that a
single code is applied to each response without repetition, for open-ended questions. A coded template was designed in SPSS software and completed survey questionnaires were transferred into the software for data analysis. Data cleaning was
performed to ensure that data values are complete and accurate. Descriptive data
analysis, cross-tabulation and chi-square statistical analysis were conducted to draw
inferences on the collected data.
Qualitative data were transcribed and organised into discussion topics. Content
analysis of the transcribed data was carried out using Excel. In Excel, data were first
sorted into themes and patterns were generated across themes to show relationships
across key issues, such as education level, age and gender. Differences in views on
climate services and information based on farmers’ education level, age, gender and
income were summarised before analysis and then compared by using the chisquare test (Cronk 2008). The chi-square test of independence was also used to find
out whether two or more attributes were independent (p > 0.05).
3 Results
3.1 Socio-Economic Characteristics of the Respondents
Age of Respondents
The age of respondents in the two study villages of Sanje and Msolwa Ujamaa
showed that 26% of respondents in Sanje and 32% of respondents in Msolwa
Ujamaa were aged between 18 and 35 years, 46% in Sanje and 36% in Msolwa
Ujamaa were aged between 36 and 60, while 28% in Sanje and 32% in Msolwa
Ujamaa were aged above 60 years. These findings indicate that the number of
E. P. Ruth et al.