[ASC-list] WA Event reminder - Effective Evaluations (Wednesday evening)
cassandra.rowles at gmail.com
Tue Jul 24 06:59:58 UTC 2018
JUST IN TIME FOR NATIONAL SCIENCE WEEK
Do you have boxes of old surveys in your office that you never got around to
analysing? Or perhaps you simply wrote on your annual report that ?93% of
participants enjoyed the event? and didn't dig any deeper?
Before you print your National Science Week surveys, it?s time to think about
what you will do with the data you collect. Australian Science Communicators
is pleased to offer this workshop on survey data analysis.
In this Effective Evaluations workshop, you will learn how to:
- write survey questions that tell you something useful
- choose the best graph for your purpose
- compare different groups of participants
- check for a change between pre- and post- tests
- use Excel* to do basic statistical analysis
The workshop is targeted at evaluation data from surveys, particularly those
using Likert scales**. It's designed for people who haven't been near a
statistic since high school and don't want to start now.
*Because you don?t want to learn to code in r, and SPSS is too expensive.
**You know, the ones with little circles that go from Strongly Disagree to
Where: Seminar Room at ICRAR/UWA, 7 Fairway Crawley WA
When: Wednesday 25th July 2018, 5-630pm
How much: Free for members. $10 at the door for non-members.
How to register: Use our Facebook event registration (where we'll also be
monitoring the discussion for any pertinent questions you might have in
advance), or you can use Eventbrite directly.
This will help us make sure we have enough material and contact the
*About the Presenter*
Miriam Sullivan is a lecturer at Curtin University and Co-President of ASC-WA.
As an undergraduate, she studied zoology so she wouldn't need to do any
maths. Unfortunately, she stuffed up that plan by doing a PhD in science
communication that involved lots of surveys and statistics. Ever since then
she's been doing evaluation research, designing surveys and coaching
students in data analysis.
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