- London, GB
- £20 /hr
- Available now
I am an experienced Statistical and Data Analyst with an overall aim to develop, evaluate and solve practical business solutions.
MSc Research Methods inmore...I am an experienced Statistical and Data Analyst with an overall aim to develop, evaluate and solve practical business solutions.
MSc Research Methods in Psychology University of Hertfordshire
BSc (Hons) Psychology University of Hertfordshire
SQL Programming Certificate Noble Programmin
Please see the relevant experience section for in-depth descriptions of all the available qualitative and quantitative analytic options.
Area Covered: London
Work Experience Summary: Competencies as a Research Analyst:
Conducted statistical analyses, using SPSS and Excel for The Border Agency or The Department of Children, Schools and Families.
Summarised and presented the data by providing meaningful descriptive statistics following data entry or coding, sorting the data, defining variables, modifying variables (in the same variable or different variable), screening and cleaning. In addition to providing summary statistics such as mean, median, mode, SD, skewness, kurtosis the data had to be presented using graphs such as histograms, bar charts, scatter plots, box plots, line graphs or even crosstabs. The statistics tests used in some of my work projects were Binomial Logistic Regression and Logistic Regression, T-tests, non-parametric tests such as CHI 2 test of independence, and Wilcoxon test.
Surveys construction and conducting the quantitative analyses
Manipulating data using SQL
Improving and monitoring the quality of data related to the specifics of the organisation, manipulating vast amount of data in order to carry out summary analyses to different requirements
I have used SPSS for up to 6 years in relation to the following types of analysis:
• entering data creating a data file, coding , sorting data
• defining variables
• working with data
• modifying data, screening and cleaning
• everything descriptive statistics
• Using graphs in order to describe, explore (histograms, bar charts, scatterplots, boxplots, etc)
• Manipulating data
• Partial correlations
• Multiple regressions
• Factor Analysis (Exploratory and Confirmatory FA)
• T- tests
• 1-way ANOVA
• Within ANOVA
• 2- way between ANOVA
• Non- parametric tests: Chi 2, Mann-Whitney U-test, Wilcoxon , Friedman, Spearman’s test.
• Multivariate data analysis
• Analyse the influence of categorical and quantitative predictors within the context of the GLM
• Syntax editor
Knowledge and Understanding:
Principal aims of fundamental and applied research in psychology and associated research areas.
Core concepts of research methodology (such as theory, causality, observation and objectivity) and relevant positions in philosophy of science.
The nature of psychological knowledge and its dependence on the type of investigation as well as . underlying epistemological position.
Criteria of validity as well as potential sources of bias in research and how these can be applied to a critical appraisal of research publications.
Intellectual Research Skills • able to:
Accurately explain key terms in quantitative and qualitative research methodology.
Formulate proper research questions and devise suitable research strategies depending the nature of the domain and the setting of the research problem.
Critically appraise published research.
Make effective use of mathematical or graphical tools in formalizing research problems.
Plan, conduct and write a critical literature review.
Practical Research Skills • able to:
Write research proposals as well as research reports.
Design and create scientific tables and charts.
Develop, design and evaluate appropriate research tools.
Plan, organise and monitor the progress of a research project.
Handle quantitative and qualitative data using scientific software.
Carry out an electronic literature search.
Present, communicate and disseminate research findings both orally and in writing.
Transferable Skills • able to:
Communicate and discuss ideas effectively.
Use information technology effectively.
Manage time and work to deadlines.
Articulate a well-presented argument.
Contribute constructively to teamwork.
interpret non-subject specific quantitative data critically.
• judge the scientific evidence of an empirical investigation on the basis of established criteria of validity
• develop a deeper understanding of the purpose of specific types of scientific investigations in the area of fundamental as well as applied research (e.g. correlational studies, experimental research)
• translate research ideas into precise research questions or hypotheses
• choose an appropriate study design depending on the type of an empirical investigation
• construct measurements and evaluate their psychometric quality
• choose appropriate statistical procedures depending on the goal of the analysis as well as the nature of the data material
• interpret and present results from statistical data analysis
• identify research problems suitable for the application of a qualitative research approach
• understand theoretical orientations underpinning qualitative research
• gain first hand research experience by engaging in a qualitative 'mini' research project
• understand the idea of rigour in the analysis and interpretation of qualitative data
• how to effectively peruse current research papers according to standards that are normally applied by reviewers of scientific journals
• orally present and discuss their own critical analysis of scientific publications
• write a critical appraisal
• gain an overview of multivariate statistical procedures and their application
• use the General Linear Model (GLM) for a range of data analytical problems
• use regression models for categorical dependent variables
• understand key issues of structural equation modelling (SEM) and use a SEM package to carry out relevant analysis
• practice proper presentation and reporting of a complex statistical analysis
• multivariate statistical data analysis
• the GLM and its application.
• structural equation modelling (SEM)
• regression models for categorical dependent variables
SPSS STATISTICAL AND RESEARCH ANALYST (WITH SQL)