Presented by: Michael Guo
Thursday 11th January 2022
What this webinar is about
The aim of the webinar is to provide participants with a way of dealing with the collection and analysis of quantitative data in order to convert data into knowledge.
Quantitative analysis of data is a central issue for many if not most masters and doctoral students. This requires some familiarity with statistics and with data modelling as well as some knowledge of appropriate software systems with which to conduct the analysis. There are several software products available and one of the more established and utilised is SPSS.
This webinar provides useful guidance for handling some of the challenges associated with quantitative data analysis and demonstrates how these can be tackled using SPSS, which is available at a large number of universities.
- Understanding the statistical mind set
Performing descriptive analysis
- Presenting data, sorting, frequencies and distributions
- Describing the sample, estimate the population characteristic/parameters and draw inferences,
- Measures of central tendency and dispersion, means, medians and modes, standard deviations, standard errors.
- The assumption of normality
- Hypothesis testing, correlation, and regression
- Establishing the significance of relationships
- Looking for linkages and themes, Cluster analysis
- Factor analysis.
- The analysis can only be as good as the data
This webinar delivers practical useful information which can be put to immediate use. It is relevant to academics from most Faculties, Departments and Schools.
The webinar will be held on Tuesday 11 January 2022 and it will run to GMT time using Zoom. The Zoom Room will open at 1:45 pm (GMT) and the event will begin at 2:00 pm and will finish at 4:00 pm (GMT). The attendance fee is £25.
To book a place on the webinar, please see: https://shop.academic-conferences.org/?ec_store=webinars
For further information contact: firstname.lastname@example.org
For further information please click here: Quantitative Analysis for Academic Research