Coursework/Project 

1 - Project output (other than dissertation) - 100

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<ul><li>The Research Process, Design &amp; Surveys </li></ul>
<ul><li>Measurement in Social Sciences </li></ul>
<ul><li>Introduction to Multivariate Statistics: How to choose a statistical technique? </li></ul>
<ul><li>Data Screening and Preliminary Data Analysis </li></ul>
<ul><li>Regression Models </li></ul>
<ul><li>The Linear Model: assumptions &amp; limitations </li></ul>
<ul><li>Nonlinear Models </li></ul>
<ul><li>Two-level Regression Models </li></ul>
<ul><li>Panel Data Analysis </li></ul>
<ul><li>Modelling Panel Data </li></ul>

Feedback is provided in a number of ways throughout your module. This includes feedback you receive during teaching from both peers and lecturers and that provided for formative assessment. Following an assessment, you will be given your marks and feedback in line with the assessment regulations and policy. More information on the timing and type of feedback that will be provided for each assessment will be available from the module leader. <a href='https://www.citystgeorges.ac.uk/about/governance/policies/student-policies-and-regulations'>https://www.citystgeorges.ac.uk/about/governance/policies/student-policies-and-regulations</a>

This module will support the development of all the graduate attributes. Your module leader will provide you with information about how your learning, teaching and assessment activities support your development of these attributes. The graduate attributes are: - Always learning - Engaged in the world - Technical and digital - Connected Professional - Creating Impact

In-Person - 

Self-directed - 

Interpreting Quantitative Data with SPSS

Research Methods for Business Students

 Statistical Analysis with Missing Data

 Missing Data, vol.136 in Series: Quantitative Applications in the Social Sciences

Applied Longitudinal Analysis,

Change scores as dependent variables in regression analysis.

Sociological Methodology

Time series and panel data econometrics

Multiple Imputation after 18+ years

Journal of the American Statistical Association

Using Multivariate Statistics

Discovering Statistics Using SPSS

Missing Data Analysis in Practice

The SAGE Handbook of Quantitative Methodology for The Social Sciences

SMM830 - Quantitative Methods 3: Analysis of Survey Data: Regressions and Longitudinal Models

Contact hours will be a mixture of lectures, group work and practical computer workshops. 
On your own and in the lectures, you will be asked to consider articles based on a large survey and assess the process of how they moved from their research question to the empirical study, their analysis procedures, how results were reported, etc.  
In the computing workshops, you will use real survey data, and work on different stages of the analysis from preliminary data analysis and screening to running models and interpreting results. Regressions are widely used in research, and you will see that it is not just about running software.  We will use SPSS and Stata, no previous knowledge of the software will be assumed, but you will be expected to practice in your own time.

Quantitative Methods 3: Analysis of Survey Data: Regressions and Longitudinal Models

Write and present results in an academic fashion 

Skills

Identify the limitations of their analysis 

Knowledge

Demonstrate confidence in synthesising analysis and reasoning, based on the empirical evidence 

Values and attitudes

Prepare data to develop any multivariate statistical analysis 

Identify suitable statistical methods to answer a range of research questions 

Understand different regression models of cross-section and panel data 

Explain and reflect on the rationale for the study 

Use SPSS and Stata for survey data analysis 

Be aware of implications of unusual observations and outliers 

Estimate and interpret a range of models 

Interpret and present the research findings cogently 

Draw appropriately on significant literature(s ) for developing the research study 

Be able to judge whether secondary data will be useful to answer their research question(s) 