John Wilson

Preferred presentation format: Poster

Affiliation(s): AgResearch

Title: Mr John Wilson Position: Data analyst Organisation: AgResearch, Hamilton, New Zealand Contact email: john.wilson@agresearch.co.nz Contact phone: +64 7 8385234

Keywords: survey, statistics, attitudes, behaviour, policy, extension

Policy and extension can be better targeted through the use of information from quantitative surveys to establish a base line for peoples’ attitudes and behaviour and to evaluate the most effective way of encouraging behavioural change. For example, a survey of farmer attitudes and beliefs about dairy effluent disposal helped Victorian agencies refine their extension strategy for farmers. A quantitative survey was also a vital component in a project that the Auckland Regional Council is using to encourage voluntary environmental care amongst farmers. A knowledge of simple statistics can aid the design and interpretation of survey information, but for people unfamiliar with them, they can be very off-putting. As a consequence, some people avoid using quantitative results in their work or make errors of judgement when they do. This poster will provide an introduction for beginners to the use of statistics to help interpret social research and extension results.

• Sampling a population should be designed to provide a sufficient number of responses for obtaining statistical power and an acceptable margin of error.
• Theory should be used to ensure that the dependent social and psychological variables are at the same level of specificity e.g. general attitudes towards the environment and an index of environmentally friendly behaviours or specific attitudes and specific behaviours.
• Concepts are best measured using a number of items and not just the answer to one question. Cronbach’s alpha coefficient helps discern the consistency of a set of questions.
• The strength of relationships between concepts or questions can be calculated using correlations, but their results don’t imply cause and effect. Calculating the statistical significance of correlations can assist in their interpretation.
• A comparison of means of continuous variables can be tested for significance using the t test and categorical variables tested using Chi-square. The use of statistical tests increases confidence in the interpretation of results.

Key learning points

• Quantitative surveys of attitudes and behaviour can help extension and policy
• Surveys design should be statistically sound
• Simple statistics help interpretation of survey results

APEN

The Australasia-Pacific Extension Network (APEN) is a professional organisation for extension professionals - people involved in community and rural development, adult education, communication and other related fields.

The network represents about 500 extension professionals across Australia, Asia and New Zealand. It has active chapters in every state of Australia with new chapters being added.

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"People successfully managing change"

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"To provide a platform for networking, professional development and representation of members' and the profession's interests.

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• a forum for professionals to share new knowledge, information, skills and experience across Australia and the Pacific
• a network which opens doors to future employment prospects and provides relative continuity for those working on short term contracts
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• a quarterly newsletter, ExtensionNet, covering industry news, case studies, extension theory and upcoming events
• education and training to develop professional competencies and standards
• the opportunity to improve the practice of extension by developing more rigorous methodologies that are informed by theory
• a guide to public information available on extension
• discount rates for APEN workshops, conferences and publications.

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