Core Quantitative Methods (CRT-5)

GRADUATE SCHOOL

COLLEGE RESEARCH TRAINING

Core Quantitative Methods (CRT-5)

Also available as:

Core Quantitative Methods for DTC Students, option G

And alternative exit points:

Appreciating Quantitative Methods

Selected Quantitative Methods

Module Guide

2014-2015

Core Quantitative Methods

INTRODUCTION

All researchers need to understand something about quantitative research, whether or not they will carry it out themselves. Everyone comes across it in literature reviews, and even in the press. This course offers an introduction with three possible exit points, each providing progressively more knowledge and understanding.

TARGET GROUPS

For some students this course is compulsory. For DTC students this would be the whole course, but for other students your department may have specified an alternative exit point.

Subject to space, the course is available to all postgraduate research students, with priority given to social science students. If the course is not compulsory for you, you do not need to specify your exit point in advance. If only part of the course is compulsory for you, you are still welcome to attend later classes.

The course does not presume any previous knowledge of quantitative methods, nor does it involve any difficult mathematics.

MODULE AIMS

The first part of the course (up to the first exit point, Appreciating Quantitative Methods) will consider the sorts of questions that quantitative research methods can answer, and research designs appropriate to quantitative analysis. The strengths and weaknesses of quantitative methods will be considered, including issues of sampling and validity. This part will also include the presentation of basic quantitative results (descriptive statistics) and how computer packages can help with this.

The second and third parts of the course will develop these issues, but principally will cover the most commonly used quantitative analysis methods (inferential statistics), including how to calculate and interpret them using the SPSS software package available on the college’s computers.

Practice is important in this subject, and students will be expected to complete short assignments each week, which will form part of the assessment.

MODULE OUTLINE

Part A

1Introduction to quantitative methods

2Introduction to statistics and to SPSS

3Working with numbers; research questions and designs (1)

4Research questions and designs (2); using graphs to represent data

5Histograms, the normal distribution and introduction to inferential statistics

(Exit point: Appreciating Quantitative Methods)

Part B

6More on significance levels; paired-samples tests

7Independent-sample tests; power; effect sizes

8Quantitative Data gathering

9Regression and correlation

10Surveys and questionnaires

(Exit point: Selected Quantitative Methods)

Part C

11Chi-square tests

12Factorial Anovas

13Multiple regression and correlation

14Data problems and transformations

15Revision, overview, further resources

(Final exit point: Core Quantitative Methods)

TIMES AND PLACE OF MEETINGS

Duration

15 sessions of two hours each (5 in part A, five in part B, five in part C), held in the second half of term 1 and throughout term 2.

Dates

Time and venue:

Thursdays (from 13 November 2014), 5.30 to 7.30 pm.
RB, room 102

There will be no session on 19 February 2015 (Reading Week).

STAFF

Module Tutor:Mike Griffiths ()

ASSESSMENT AND MARKING CRITERIA

This module is assessed by weekly short assignments and take-home exams, each marked from 0-100%. These will be handed out at the appropriate classes. Short assignments will be due by the start of the next class, and deadlines for take-home exams will be notified separately. All assignments should be e-mailed to the tutor ().

For the first exit point (Appreciating Quantitative Methods), assessment will be based on weekly assignments only. For the second exit point (Selected Quantitative Methods), assessment will be based on weekly assignments (adding up to half the total mark) and one take home exam (the remaining half of the total mark). For the final exit point (Core Quantitative Methods) assessment will be based on weekly assignments (adding up to half the total mark) and two take home exams (one quarter of the total mark each). In each case, a weighted average mark of 50% is required to pass.

INDICATIVE READING LIST

General

Most of the reading for this course is optional. Where reading is required between classes, this will be made clear.

Although there are many good books written for a cross disciplinary audience, some of the best ones are written for particular disciplines. Do not be put off by this; none of them presume a specialist knowledge of the discipline concerned and differences in methods tend only to be about which ones are emphasised. In particular, psychologists have a strong reputation for using quantitative methods, and psychology undergraduates have to learn them from the start of their course. The following book (aimed at them) takes things quite gently, especially if you ignore the later chapters or use an earlier edition.

Coolican, H. (2009).Research Methods and Statistics in Psychology (5th Ed.). London: Hodder Education. [In the library: 150.72 COO.]

Research Methods

There are many good books on research methods. They often do not cover statistics in any depth, if at all, but concentrate on research design and data gathering. On the other hand, they often cover qualitative methods as well as quantitative ones.

You may prefer a book aimed at your own discipline, which will use examples relevant to you. For example, the library contains books on research methods shelved at 150.72 for psychology, 300.72 and 300.727 for sociology and social research in general, 301.2072 for anthropology, 302.23018 for media and cultural studies, 361.3072 for social work, and 370.72 and 370.78 for education. Even within these disciplines there may be useful books shelved elsewhere, for example relating to specific research techniques or to branches of your discipline.

Two of the most comprehensive books (covering both quantitative and qualitative methods) are:

Bryman, A. (2012). Social Research Methods 4th ed.). Oxford: OUP. [300.72 BRY]
Cohen, L., Manion, L. and Morrison, K. (2011).Research Methods in Education (7th ed.). London: Routledge. [370.78 COH; also available electronically.]

Some other books which may be of interest are:

Cone, J. D. and Foster, S.L. (2006). Dissertations and theses from start to finish. Washington, D.C.: APA. [150.72 CON]
Huff, D. (1973). How to lie with statistics. Middlesex: Penguin. [Obviously the title is ironic! It’s about how to avoid being misled by statistics. 519.5 HUF]

Statistics and SPSS

You will be provided with a booklet of the SPSS exercises we will do in class. If you want another book on SPSS, it is obviously ideal if it uses the same version of SPSS, but any differences relevant to this course have been very minor since version 15.

As its title suggests, the following book has a very practical and reassuring approach. It covers most of the procedures you are likely to use in SPSS, and is especially good for large data sets and data problems.

Pallant, J. SPSS Survival Manual (5th ed.). [005.30727]

The following books cover statistics alongside the relevant SPSS procedures, and go beyond the material covered on this course:

Dancey, C. P. and Reidy, J. (2011). Statistics without maths for psychology using SPSS for Windows (5th ed.). Harlow: Pearson Education. [150.727 DAN]
Field, A. (2013). Discovering statistics using IBM SPSS Statistics (4th ed.). London: Sage. [519.50285 FIE]

If you want a more advanced, rigorous and authoritative book just on statistics, a good one is

Howell, D. (2013). Statistical methods for psychology (8th ed.). [150.727 HOW; also available electronically]

Excel

Your computer booklet includes an introduction to graphs in Excel. There is also a selection of books in the library on all aspects of Excel.

COURSE OF LECTURES

1Introduction to quantitative methods

This session will provide a general introduction to quantitative research. It will introduce the idea of variables and relationships between them; operational definitions; and quality issues.

Supplementary reading in coursepack

Bryman, A. and Cramer, D. (2001). Quantitative data analysis with SPSS Release 10 for Windows. London: Routledge. [Chapter 1: Data analysis and the research process.]

Seale, C. (2012). Validity, reliability and the quality of research. Chapter 30 in C. Seale (Ed.), Researching society and culture (3rd ed.). London: Sage.

Supplementary reading in recommended Methods books:

Coolican (2009) / Chapters 1-5
Bryman (2012) / Chapter 7 (the nature of quantitative research)
Cohen, Manion and Morrison (2011) / Chapter 4 (the search for causation); Chapter 10 (validity and reliability)

2Introduction to statistics and to SPSS

We will cover the different kinds of variable and why it is important to distinguish between them. We will also look at what is meant by populations and samples, and sampling methods. You will also learn about the main kinds of descriptive statistics and be introduced to the SPSS computer package.

Supplementary reading in recommended Methods books: variables and statistics

Coolican (2009) / Chapter 11 (Statistics – organising the data)
Bryman (2012) / Chapter 15 (Quantitative data analysis)
Cohen, Manion and Morrison (2011) / Sections 34.1-34.5 (Approaches to quantitative data analysis)

Supplementary reading in recommended Methods books: sampling

Coolican (2009) / Chapter 2
Bryman (2008) / Chapter 8 (Sampling)
Cohen, Manion and Morrison (2011) / Chapter 8 (Sampling)

Supplementary reading: SPSS

Kinnear and Gray, or Pallant.

3Working with numbers; research questions and designs (1)

In the first part of the class we will cover some basic issues about the use of numbers and percentages to describe data. In the second part we will look further at what kind of questions quantitative research can answer, and take an overview of quantitative research designs.

Essential reading (between classes 3 and 4)

Before the next class you will need to read two articles (to be notified) and answer some questions about them (also to be notified). Bring your answers along to class 4 for discussion.

Possible supplementary reading (for sessions 3 and 4)

Working with numbers and graphs

The following is in the coursepack:

Cone, J.D. and Foster, S.L. (2006). Dissertations and theses from start to finish. Washington, D.C.: APA. [Chapter 11: Presenting the results.]

Other helpful books include:

Daly, F., Hand, D.J., Jones, M.C., Lunn, A.D. and McConway, K.J. (1995). Elements of statistics. Wokingham: Addison-Wesley. [Chapter 1: Data.; 519.5 ELE]
McGill, F., McLennan, S. and Migliorini, J. (2000). Complete Advanced Level mathematics: statistics. Cheltenham: Stanley Thomas. [Chapter 3: Data Analysis I.; 519.5 MAG]

Excel

The computer booklet you are provided with includes an introduction to graphs in Excel. There is a large selection of books in the library, covering all aspects of Excel.

Research questions and designs

In recommended Methods books

Bryman (2012) / Chapter 3 (Research designs)
Cohen, Manion and Morrison (2011) / Chapter 6 (Choosing a research design) and Chapter 7 (Planning Educational Research). [Chapter 6 is in the coursepack.]

Others

There are whole books devoted to this topic. A chapter from the first one listed below is included in the coursepack.

Blaikie, N. (2009). Designing social research (2nd ed.). Cambridge: Polity. [300.72 BLA]
de Vaus, D. (2001). Research design in social research. London: Sage. [300.72 DEV]
Mitchell, M. and Jolley, J. (1996). Research design explained (3rd ed.). Fort Worth: Harcourt Brace. [150.72]

This is, of course, a topic where books aimed at your own field of study may be especially appropriate.

4Research questions and designs (2); using graphs to represent data

In the first part of the class, we will discuss the research you have read about (see essential reading above). In the second part we will look at the use of graphs to illustrate data, and how they can be created in Excel.

Reading

See reading list for previous session.

5Histograms, the normal distribution and introduction to inferential statistics

We will look at histograms and in particular the so-called ‘normal distribution’. We will learn what is meant by ‘statistical significance’ and carry out our first inferential test using SPSS.

Supplementary reading in recommended Methods books: theory

Coolican (2009) / Chapters 12-14
Bryman (2008) / Chapter 15 (section on Statistical significance)
Cohen, Manion and Morrison (2011) / Sections 34.5-34.9, 36.11

Supplementary reading: SPSS

Kinnear and Gray, Pallant, or Bryman (Chapter 16)

6More on significance levels; repeated-measures tests

We will look at how to choose a statistical test in the common situation that one variable is categorical and the other is continuous. We will go through how to carry out some of these tests. We will also consider some more issues about statistical significance, including the issues that arise when we carry out more than one test in the same study.

Supplementary reading in recommended Methods books: theory

Repeated-measures etc / Multiple comparisons / 1 and 2-tailed tests
Coolican (2009) / Chapter 14 / Chapter 18 / Chapter 14
Cohen, Manion and Morrison (2011) / - / - / Section 34.6

Supplementary reading: SPSS

Kinnear and Gray, or Pallant.

7Independent-sample tests; power; effect sizes

We will finish going through the family of tests that we started last week. We will also look at the issue of statistical ‘power’. This will bring us onto a consideration of the size of effects, and whether results that are statistically significant are necessarily of practical significance.

Supplementary reading in recommended Methods books: theory

Coolican (2009) / Chapter 15
Cohen, Manion and Morrison (2011) / Section 34.10

Supplementary reading: SPSS

Kinnear and Gray, or Pallant.

8Quantitative Data gathering

We will look at the main ways that data are gathered for quantitative analysis, other than surveys and questionnaires (which will be dealt with in session 10).

Recommended reading – combining quantitative and qualitative research

Bryman, A. (2012). Social Research Methods (4th ed.). Oxford: OUP. [Chapter 27: Combining qualitative and quantitative research – in coursepack. Students might also find it useful to read Chapter 26: Breaking down the quantitative/qualitative divide.]

Supplementary reading in recommended Methods books: quantitative data gathering

Coolican (2009) / Chapter 5, 6 and 9
Bryman (2012) / Chapters 12-14 cover some common methods; also 9-11 which are more relevant to week 10.
Cohen, Manion and Morrison (2011) / Chapters 11-19.

This is of course another topic where you may find a Methods book aimed at your own discipline particularly appropriate.

9Simple regression and correlation

In this session we will look at how regression and correlation can be used to analyse outcomes of studies with two continuous variables, including how to illustrate the results with scatterplots. We will see how to do this analysis in SPSS, and review the main restrictions on this kind of analysis.

Supplementary reading in recommended Methods books: theory

Coolican (2009) / Chapter 17
Cohen, Manion and Morrison (2011) / Sections 35.4, 36.8-9
Bryman (2012) / Pages 341-344

Supplementary reading: SPSS

Kinnear and Gray, Pallant, or Bryman (2012, page 368).

10Surveys and questionnaires

Surveys and questionnaires are a common way of gathering data. We will look at these in more detail, emphasising how to ensure they can be analysed quantitatively. We will also look at techniques in SPSS which are particularly helpful for the large data sets usually produced by such methods.

Essential reading

Robson, C. (2011). Real world research (3rded.). Malden, MA: Blackwell. [Chapter 10: Surveys and questionnaires – in course pack.]

Supplementary reading in recommended Methods books: surveys and questionnaires

Coolican (2009) / Chapters 7, 8
Bryman (2012) / Chapters 9-11
Cohen, Manion and Morrison (2011) / Chapter 13

Supplementary reading: SPSS for surveys and questionnaires

Pallant.

Core Quantitative Methods (CRT-5)

MODULE AIMS

MODULE OUTLINE

ASSESSMENT AND MARKING CRITERIA

INDICATIVE READING LIST

COURSE OF LECTURES

1Introduction to quantitative methods

Supplementary reading in coursepack

Bryman, A. and Cramer, D. (2001). Quantitative data analysis with SPSS Release 10 for Windows. London: Routledge. [Chapter 1: Data analysis and the research process.]

2Introduction to statistics and to SPSS

3Working with numbers; research questions and designs (1)

Working with numbers and graphs

Excel

4Research questions and designs (2); using graphs to represent data

5Histograms, the normal distribution and introduction to inferential statistics

6More on significance levels; repeated-measures tests

Essential reading

Robson, C. (2011). Real world research (3rded.). Malden, MA: Blackwell. [Chapter 10: Surveys and questionnaires – in course pack.]

More advanced supplementary reading

The College will not be responsible or liable for the accuracy or reliability of any of the information in third party publications or websites referred to in this booklet.