Understanding Statistical Concepts and Basic Tests

Date:

30/11/2017

Organised by:

Social Research Association

Presenter:

Dr Pamela Campanelli

Level:

Entry (no or almost no prior knowledge)

Contact:

Lindsay Adams E: lindsay.adams@the-sra.org.uk
T:0207 998 0304

Map:

View in Google Maps  (EH1 1SD)

Venue:

Hilton Carlton Hotel, North Bridge, Edinburgh (tbc)

Description:

Choosing an appropriate statistical procedures and understanding basic statistics are an essential part of a survey researcher’s skill set. This course is about understanding the statistics behind the software packages. No software packages are used. Instead there are 6 workshops over the day so each stage can be practiced. This course is informal and designed to encourage participants to ask that ‘embarrassing’ statistical question they have always wanted to ask.

Topics covered

  • Overview of statistical terms and concepts
  • Overview of analysis considerations
  • Some do’s and don’ts of graphs and tables
  • Measures of central tendency and dispersion
  • Confidence Intervals
  • Hypothesis testing
  • Two-sample t-test
  • Chi-square test of independence

PARTICIPANTS SHOULD BRING A CALCULATOR WITH A SQUARE ROOT FUNCTION.

Objectives

By the end of the course, participants will:

  • Have a good understanding of basic statistical terms and concepts
  • Have understood the practical implications of descriptive versus inferential statistics
  • Understand how, when and why to create confidence intervals for means and proportions, use a two-sample t-test or chi-square test of independence
  • Have the knowledge to use appropriate graphs and tables for the reporting of their data

 

Who will benefit?

  • The course will benefit anyone who wishes to understand statistics and survey analysis, whether they are conducting their own survey or commissioning one.
  • Participants who have had some prior experience of statistics but feel “rusty” will find it a useful revision.

 

Learning outcomes

  • Participants will have a good understanding of statistics and their use in descriptive situations, in graphs and tables and in basic hypothesis testing.
  • Participants will have the knowledge to conduct two-sample t-tests and chi-square tests of independence.

 

Course tutor

The day will be led by Dr Pamela Campanelli. Pamela is a Survey Methods Consultant and U.K. Chartered Statistician and Chartered Scientist. She received her Ph.D. in statistics from the London School of Economics, and an M.A. in survey research methods and B.A. in psychology from the University of Michigan. Prior to becoming an independent consultant, she was a Research Associate at the at the University of Michigan, a Survey Statistician at the U.S. Bureau of the Census, Chief Research Officer at the UK Institute for Social and Economic Research at the University of Essex, and a Research Director at the Survey Methods Centre at the National Centre for Social Research, London.

 

Her main interests and publications are in the study of survey error and data quality issues, with special emphasis on questionnaire design, question testing strategies, survey sampling and survey analysis. In addition to her consultancy work, she has led a UK ESRC grant on survey nonresponse and been a team member of a UK ESRC grant to explore measurement error in mixed mode surveys. She regularly teaches short courses in the UK for the SRA, the Cathie Marsh Institute for Social Research and the Royal Statistical Society. She also provides courses both in the UK and internationally for government departments (e.g., Australian Bureau of Statistics), UK Survey Research companies (e.g., TNS-BMRB), universities (e.g., University of Wollongong Australia, University of Hong Kong, University of Michigan Summer Institute), as well as for various other institutions and businesses (e.g., Brazilian Network Information Center; UNESCO Asia Pacific, Civil Service College Singapore) (see www.thesurveycoach.com).

Cost:

£260 - SRA members pay £195

Website and registration:

Region:

Scotland

Keywords:

Quantitative Data Handling and Data Analysis, Statistics , Weighting

Related publications and presentations:

Quantitative Data Handling and Data Analysis

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