Lecture 8: Data

gathering: the right

tools for the job

Dissertation

Kevin Standish

Overview

Learning Outcomes

• To describe and understand qualitative

data gathering tools

• To describe and understand quantitative

data gathering tools

• Overview methods of data analysis

• Lectures comes from: Thomas, G. (2009)

how to do your research project. London.

Sage. Chapter 8

1. Introduction

• Once you have decided how you are going to approach your question and the broad design frame that will be used, you now need to decide how you are going to collect your data.

• This means the different instruments and techniques with which you will gather information.

• Do not come up with the tool first and then find a way of using it, because if the only tool you have is a hammer you will treat everything as if it were a nail.

• Do not let your method dominate your research process.

2. Method: the way of doing

something systematically

• Method is a systematic structured approach to

gathering data.

• It is a considered thought through way of

approaching your research question in order to

find the answer you are seeking.

• Some of these methods collect data many

comprising words (qualitative research);

• some convert information into numbers

(qualitative research);

• some collect both words and numbers (mixed

method research).

2. Method: the way of doing

something systematically• Tools, methods, techniques and instruments are terms that

are often used interchangeably, resulting in confusion.

• Screwdrivers, chisels and hammers are undeniably tools -not methods.

• But they have to be used with a method: watching an inexperienced person wields a chisel is a painful experience. You need to know how to use the chisel. Until you have learnt the method, the chisel is as good as useless.

• So tool and method go together: hand in glove!

• The method is almost the tool in itself which is why the terms are often seen as synonymous and used together.

• However it is important to keep the concept of method separate from the instruments of data collection.

2. Method: the way of doing

something systematically

• The instruments that you will use in data collection will depend on the type of data being gathered: qualitative and/or quantitative data.

• Whilst different methods have conventions rules and procedures, the different instruments can be used creatively.

• Using the chisel example, a key method in woodcarving is not to of against the grain, however the chisel can create a thing of beauty when used creatively.

3. QUALITATIVE DATA

GATHERING TOOLS

1. Interviews

2. Accounts

3. Diaries

4. Group interviews and focus groups

5. Document interrogation

3. Qualitative data gathering tools

• Reflect on the similarities and differences between

qualitative research and therapy..... Like therapists, the

researcher must choose between competing practices

and theoretical traditions. In their attempt to describe

and interpret personal experience, the researcher

needs to have an open mind about where their

research journey will take them.

• Qualitative researchers want to explore peoples stories.

The focus is on attempting to make sense of

phenomena in terms of the social meanings people

bring.

• Qualitative research begins not with hypothesis to be

tested or causal relationships to be established but

rather with open research questions:

3. Qualitative data gathering tools

• Qualitative research cannot answer the

question such as: "what women develop eating

disorders?" But rather it might ask "how do

women with anorexia make sense of why they

have developed the condition?"

• Rich, textured description is valued along with

focus on the "how's" and the "what's" rather

than the "why" and the "how many". The

research questions like "how mental health

problems represented in the media?" Or "what

is it like to experience a traumatic relationship

breakup?".

3. Qualitative data gathering tools• It is important to avoid questions which contain an implicit

hypothesis. For example "what the perceived benefits to victims of domestic violence of self-help groups?" Contains the assumption that such groups or helpful it is best to have a narrow focused open research question: "how do victims of domestic violence experienced self-help groups?“

• Qualitative researchers understand that the world cannot be understood in clear-cut cause-and-effect terms. complexity and ambivalence par for the course.

• The researchers own role in the research context are understood to be part of the complexity. The researcher recognises they are part of what is being studied, and acknowledge the impact on the research through reflexivity.

3. Qualitative data gathering tools• Counsellors are drawn to qualitative research

because it similar to therapy and resonates with us.

• Both are concerned with mutual discovery, exploring meanings and understanding how the world is experienced by another.

• Both involve a relational process, that promotes collaborative empowering relationships.

• Familiar skills of interviewing and empathic listening transferable to the research arena.

• One of the main differences however is that research aim is to produce knowledge rather than enable individual awareness or change.

3.1. INTERVIEWS

1. Structured interviews

2. Unstructured interviews

3. Semi-structured interviews

3.1. Interviews• An interview is a discussion with someone in which

you try to get information from them. The

information may be facts or opinions or attitudes or

experiences or any combination of these.

• The three basic sub types of interview: structured

interviews, unstructured interviews, semi-structured

interviews.

• Interviews involve personal contact either directly

or via the telephone.

• This has a profound effect in the where

interviewees will respond to you in comparison to

how they would have reacted to a questionnaire

coming to the post.

3.1. Interviews• Because of the primacy of the personal contact, your

appearance, demeanour and tone are important: how do you want to be seen? As "one of us" or as a neutral observer or as a person in authority? Your decision should influence the way you look sound and behave.

• It is important to establish rapport with your interviewee at the beginning, before the interview proper begins. Discuss some neutral topic example the weather, the journey, etc. It is important in the process of making contact and establishing grounds for the interview to begin. With some clients you may not establish a meaningful rapport.

• You need to ask yourself before the interviews begin what it is that you are trying to get from your interviewees and how the personal contact will help.

3.1. Interviews• Does your design mean that you will be interpreting

what your respondents say, or does it need you to want

to gather straightforward "facts".

• In gathering interpretive data you will be reading your

interviewee's behaviour, mannerisms and gestures as

carefully as the words as these inform you what the

interviewees really means beyond the actual words

they are using.

• Words do change the meaning depending on context,

and meaning goes beyond the words, so we often need

to read into what the other person is saying. How does

this impact on your research data gathering process?

3.1. Interviews• The written transcripts of the original spoken

words does not pick up the behavioural cues that you will experience in the interview.

• How will you record these important nuances? Will you take notes there and then (or very soon afterwards) all you add them to the audio recording subsequently? How accurate with this be?

• It is important to have an accurate record of the interview if you are doing interpretive research.

• You will need to explain your recording methods briefly to the interviewee and what is being done with the data, how it is being stored, analysed and subsequently destroyed.

3.1.1.Structured interviews• A structured interview is a meeting with another person in

which you ask a predetermined set of questions. Beyond the set of questions there is very little scope for further following up.

• The idea behind the structure is that there is a degree of uniformity provided across different interviewees you meet. The interviewees responses will be recorded on a form that will probably be a mix different kinds of response, both open-ended and closed.

• Open-ended questions allow the respondents to reply in whatever way they wish: "what are your feelings about the national lottery?“

• Closed questions of those that demand a particular response: "do you approve of the national lottery? Yes or no"; or "how comfortable are you feel about the national lottery? Very comfortable, comfortable, no opinion, not comfortable, very uncomfortable."

3.1.1.Structured interviews• Strengths of a structured interview:

• 1. Relatively easily administered

• 2. Interviewee's responses can be quite easily coded

• The disadvantage of the structured interview is a to much structure loses the key purpose of the face-to-face interview, go beyond the mere tick in a box and get something other than the assured response.

• If you merely achieved ticks in a box you might as well give a questionnaire.

• Do not be too rigid and lose the key value of the interview. Allow a degree of flexibility in exploring their responses to questions in order to gather the richness of the answer.

3.1.2.Unstructured interviews• An unstructured interview is like a conversation.

There is no predetermined format to the interview beyond your topic of interest.

• There is no pre-defined list of questions and no set agenda.

• The interviewee is allowed to set the agenda, determining the important issues, allowing them to tell you what the issues are, what is important to them.

• As the researcher you go in with an open mind and is important that the frame set for the research allows the interviewee the scope to do this.

3.1.2.Unstructured interviews

• Just how "unstructured" is the unstructured interview?

• If your respondent goes completely off topic then you might wish to bring them back to it in a careful and sensitive manner.

• You need to understand the purpose of "off topic" discussion and how it relates to the topic of interest.

• You would need to prompt interviewee without setting an agenda to bring them back to topic.

• You could say something like "can you tell me more about that?" Or "what happened next" but avoid interpretive questions that might be leading for example "does that make you feel really angry?".

• Avoid putting words in interviewee's mouth.

3.1.3.Semi-structured interviews• The semi-structured interview provides the best of both

worlds combining structure of a list of issues to be covered, with the freedom to follow up points as necessary.

• It is the most common arrangement in most small-scale research interviews.

• Do not consider using this simply because it is easier as it might influence the data are you collecting, leading to a different kind of research from which you have set out to do.

• For example if you are really interested in interpreting your interviewee's comments and you are a participant observer in the situation you are researching, an unstructured interview remains the best choice.

• In order to get the best out of the semistructured interview, you will need an interview schedule rather than a set of interview questions.

3.1.3.Semi-structured interviews• This is a list of issues which you want to cover but do not have to be in

the form of questions but rather act as an aide memoir of the important

points for discussion.

• You do not need to go to the points in order, or keep in any formal way

to the structure but rather these are a reminder of what you intend to

cover.

• Your interview schedule, drawn up prior to the interview, is a framework

of issues, leading to possible questions, leading to possible follow up

questions, leading to probes.

• Probes are encouragements to interviewees from the interviewer to

proceed with aspects of the answers. These are both the verbal

prompts "go on..." or non-verbal prompts for example a nod, a wave of

a hand to encourage further discussion.

• This schedule is a structure to help you conduct the interview. You

should feel free to ask different questions or supplementary questions

as the need arises.

3.2.Accounts

• Accounts are really the products of unstructured interviews but without the expectation that these will have been affected by an interview.

• The accounts could for example, depending on your informant, have been provided in the form of a long written piece of prose like an essay;

• or it could be an account in an audio form for subsequent transcription.

• An account will be handled in the same way as the data from an unstructured interview.

3.3.Diaries• The diary is an invaluable data gathering tool for the

researcher undertaking a small project. • A diary is a regular, usually day by day, record of thoughts or

occurrences about events and experiences. It may involve the participant in your research making a record of thoughts, feelings, actions responses etc, or it may involve a more structured record being taken of specific activities.

• The advantage of this process is that some people find the more personal and private nature of the process allows them to give more detailed information than they would in a face-to-face interview.

• Diaries can take different formats: written, audio recordings, photographic recordings, video recordings. You need to consider the advantages and disadvantages of each diary format.

3.3.Diaries

• Diaries can be more than a simple record of what happened, often it is a record not only of the events but also the person's interpretations of those events.

• These particular interpretations determined by the clients context, background, culture et cetera.

• A structured diary can collect data about specific events and activities relevant to your topic. This results in easier coding from a variety of participants to ensure uniformity of data.

• What diaries provide is a longitudinal and regular collection of data that interview cannot achieve on its own.

3.4.Group interviews and focus

groups• Interviewing in a group has particular elements

that you need to be aware of: people behave differently in groups and the particular ways a whole group will behave differently from individuals.

• In a group particular individuals may be more talkative order less talkative; some people may take the lead or others follow.

• Also the group may display "risk shift phenomenon": the group will make a riskier decision on an individual. Groups tend to influence the overall information process than what you would get from individuals. The group safety plays a vital role in influencing the information you will gather from a group.

3.4.Group interviews and focus

groups• You must therefore be aware that you will obtain

different responses from the group, than you would have obtained from the same people interviewed individually.

• You need to establish why you are doing a group interview rather than a set of individual interviews.

• One of the most important reasons for wanting a group interview would be those concerning group psychology itself. You want to find out how a group as a whole behave in relation to a particular event, or an attitude that the group may hold as a whole.

• In a group interview the research takes on the role asking questions, and is in control of the discussion.

• this is a discussion between the research and the participants.

3.4.Group interviews and focus

groups• A focus group the role of the group leader is more of

a facilitator or moderator. The aim of focus group is to facilitate discussion among participants are not between yourself and the participants.as a facilitator your role is to stimulate discussion through comments, a range of focused materials and prompts.

• As groups require facilitation it is difficult to be both facilitator and recorder of information. It is common practice to use an observer to record information about context, environment and participants behaviour in group settings. It may be helpful to record proceedings using audio and or video.

3.5.Document interrogation• Gathering data from documents requires an entirely different

process from gathering data from people. It is important to find the right documents, to read them in a structured manner and to analyse them meaningfully. Different documents require different documentary interrogation in order to find the data are you seek.

• An example of data documentation analysis could be something like BACP professional conduct procedure outcomes. You gather the last 10 years of boards outcomes and to analyse the decision-making process, and outcomes looking for changes over time.you would have a clear structured checklist in which you are looking for particular themes and ideas while you interrogate the documents.

4.MIXED METHODS: DATA

GATHERING FOR WORDS AND

NUMBERS

1. Questionnaires

2. Scales

Mixed methods involve tools that collect words or numbers or both, or they may commonly convert the words into numbers.

4.1.Questionnaires• Questionnaires: the defining characteristic of a

questionnaire is that it is a written form of questioning.• Questionnaires can be used to collect an array of data

using both open or closed questions; collecting facts, or attitudes; all be part of a procedure to assess something in particular for example personality.

• Questionnaires can be presented in a variety of formats and manner: it can be tightly structured, or allow the opportunity for more open and discussion of responses.

• They can be read out the interviewers, or sent to respondents to complete themselves, they may be sent by post, email or even be an online questionnaire (Google Docs, survey monkey).

4.1.QuestionnairesBasic considerations in constructing a questionnaire

• 1. Keep everything short. Try to limit your questionnaire to one side

of A4. Keep the questions short.

• 2. Be clear about what you are asking. Only ask for one piece of

information at a time. Do not ask for two pieces of information in

one sentence, this will confuse respondents.

• 3. Be precise about what you are asking. Give them a choice of

options rather than an open-ended answer

• 4. Collect all the necessary details. Some obvious information that

may help with data analysis data on, needs to be on the form as

you cannot gather it later. Example gender, years of experience et

cetera

• 5. Be aware of "prestige bias": makes is want to appear with all of

the things they can need to prestige (to appear clever, rich,

educated et cetera). Be aware of this in the way you pose

questions and interpret responses. This can lead to the respondent

assuming there is "a right answer".

4.1.Questionnaires

• Kinds of questions and kinds of responses

• Open questions

• Open questions are similar to unstructured interviews with the same considerations needed. However you are unable to prompt the respondent in a questionnaire with "anything else you would like to say". Rather than asking respondents an open question at the end of the questionnaire: "is anything asked you would like to add" which often results in the syndrome of mind emptying: suddenly you have no idea what to put in that box.

• Rather structure that open-ended question into a series of prompts and will cover the topic you are attempting to answer.

4.1.Questionnaires• Closed questions

• Close questions can be organised in a number of ways:

• 1. Dichotomous questions: these are usually "either-or" ;

"yes - no" answers. You have a single choice to make

between two options. Is often used as screening

questions in which you can then separate respondents

into different groups.

• 2. Multiple choice questions: contain two or more answers

where respondents can be told either to tick one box to

tick as many boxes as needed. Depending on the purpose

of the multiple choice question will change depending on

the data needed. If you are interested in respondents

knowledge rather than their beliefs, there might only be

one right answer; or multiple classes depending on beliefs

being covered.

4.1.Questionnaires

• 3. Rank order questions: respondents have to rank items (put them in order) on a list according to some criterion (best – to –worst), in which you can ask either limited choices or require them to rank the whole list.

• 4. Rating scale questions: require the respondent to rate some experience, attribute, attitude along a continuum: very positive, positive, neutral, negative, very negative. The respondents will tick only one of these boxes.

4.1.Questionnaires• 5. Constant sum method: requires the respondent to

distribute points, usually 100, to a set of answers. You provide them with a taxonomy (an arrangement of ideas) contains a number of features associated with the concept you are exploring and ask them to distribute the points amongst these features. One of the advantages of this method is the attribution of a strength of feeling to various answers revealing the relative importance attributed to different opinions. This allows statistical manipulation of the data that would not be possible with other questionnaires.

• 6. Matrix or grid questions: this provides a series of questions which all have the same answer scale: example all on the same scale of 1 to 5. It is important to make clear to respondents how the scale operates for example adding the words high or low at each end, or an arrow indicating level of importance increasing across the scale.

4.2.Scales• Scales are a set of items and responses that allow for a degree of

measurement. It is not uncommon for scales to be included in questionnaires.

• The two main scale measurements that are used: . Likert scale & Semantic differential scale

• 1. Likert scale: primarily used for measuring attitudes. • Respondent indicate their level of agreement to statements provided by

the research relating to the attitude, belief or characteristic. • The respondent response to each item on the five point scale usually with

answers from strongly agree, agree, neither agree nor disagree, disagree, strongly disagree. With the tendency for some people over choose the middle option, neither agree nor disagree, this middle option is sometimes removed.

• A Likert scale can be used in any situation where belief or attitude is to be measured.

• The important thing to remember is that you are asking for agreement or disagreement with a statement that you provide. It is important that your statement is clear and unambiguous.

4.2.Scales

• 2. Semantic differential scale: using opposite meaning adjectives, such as "kind/cruel" or "exciting/boring", the scale requires the respondents to rate something on a seven point scale in relation to those adjectives.

• Exciting……………………..boring

• Kind …………………………cruel

• Generous……………………tight

• You use the semantic differential scale to draw a more textured picture of respondents thinking and look at interesting differences where they occur between subgroups within your sample. If you do not intend to be present in the questionnaire you need to provide an example of an already completed (but irrelevant one) to explain what needs to be done.

5. OBSERVATIONS

1. Structured observation

2. Unstructured observation

Observation is one of the most important ways of collecting data in social research. Observing means watching carefully, watching in some very different ways, depending on the purpose of the research. There are two kinds of observations: structured observation, and unstructured observations

5.1.Structured observation• In structured observation you are making the assumption

that the social world can be broken down into quantifiable elements, bits of data that you can count. The first thing that the observer has to do is to define what these bits are to be. These may be individual pieces of action that occurs, or use of particular language. The observer has to devise a way of counting these elements.This is non-participants observation

• 4 Ways of counting in observations:1. Duration recording: the Observer measures the overall time that a target behaviour occurs in a particular time period2. Frequency count according: the Observer records each time the topic behaviour occurs in a particular time period

5.1.Structured observation

• 3. Interval recording: you decide on an interval (three seconds, 10 seconds, 20 seconds depending on the complexity of what you're looking for); target individuals; and categories of behaviour (on-task, off task). You will have data which can be processed in a number of ways, including numerical analysis.

• 4.Time sampling: refers to the fact that you are selecting intervals after the total time available for observation and then only observed during the selected periods. This is used in conjunction with the three elements above. This is used in particular for gathering information of classroom activity.

5.2.Unstructured observation• Unstructured observation is undertaken when you

are immersing yourself in a social situation, usually as some kind of participant, in order to understand what is going on there.

• This kind of observation is often called participant observation, because it is associated with research is becoming a participant in the situations they are researching.

• It entails talking to people, watching, reading documents, keep units that enable you to understand the situation. It is more than simple observation. It is difficult to disentangle where one kind of participation begins and another ends.

6.

QUANTITATIVE

DATA

GATHERING

TOOLS

1. Measurements and tests

2. Official statistics

Quantitative data gathering tools

• Quantitative data gathering is a process by

which numbers come to represent the

experience of the person. The use of numbers

as a clean conveyor of "truth" is associated

with the positivist paradigms, where knowledge

about the world can be obtained objectively. As

a result it is seen as the "absolute" truth

because it is measurable. This is merely the

positivist paradigms point of view.

• But this notion of clean, simple efficiency in the

transport of knowledge is misleading, for in

social research numbers are only as reliable as

a concepts that underlie them eg IQ scores.

6.1. Measurements and tests• The use of measurements and tests is a process whereby you

are checking the extent of something. • The results of a test will nearly always be in a numerical form.• In social sciences they take varied forms from being formal, or

informal measurements of some attribute, personal feature, or attainment.

• These tend to be associated with complex well standardised forms.

• Test construction and standardisation is a large and separate field of study, beyond the capacities and scope of most undergraduate dissertations.

• Trying to create your own concept test is what is discouraged, not questionnaires!

6.1. Measurements and tests• Tests can be divided into:

• 1.norm referenced: compares the person being tested just sample of their peers.

• this kind of test aims to compare individuals one against the other: eg .intelligence tests.

• Standardisation is an important element in the construction of Norm referenced tests.

• This involves constructing the test under particular specific, repeatable conditions with large samples from a population.

• a good test is one that is both reliable (refers to the tests ability to measure something consistently) and valid (is a measure of how well it is assessing what it is supposed to measure).

• 2.criterion referenced: assesses whether someone is able to meet some criteria, irrespective of how well other people perform on the test.this test merely compares the individual against the criteria: eg Driving test.

6.2. Official statistics

Official statistics can form the basis of a good research project, or complement your project, drawing on relevant statistics.A wide range of statistics gathered by the Organisation for Economic Cooperation and Development (OECD) are available online.Office for National statistics is another source of dataCollege statistics can be obtained through a request to the Administration in the front office of the particular statistics you are seeking. if this data is available they will be obtained, but could take some time.

7.OVERVIEW OF DATA

ANALYSIS METHODS

1. Analysing words

2. Analysing numbers

7.Overview of data analysis

methods

• Following the collection of your data you need

to analyse it.

• Your data may be in any variety of forms, and

the method for analysing the data will vary

accordingly.

• There is a wide array of analytical methods for

handling the data you have gathered.

• You need to ensure the importance of the

coherence of your story of your research.

• Your analysis should fit the approach you've

taken in your research.

7.Overview of data analysis

methods• The most commonly used methods for analysing words:

• 1.constant comparative method;

• 2.network analysis;

• 3.construct mapping and theme mapping;

• 4.grounded theory;

• 5.discourse and content analysis

• The most commonly used methods for analysing numbers:

• 1. Statistics that describe

• 2. Statistics this understand relationship between variables

• 3. Statistics that help deduce or infer

• This will provide a simple overview of these methods. More detailed lecture on data analysis will follow

7.1. Analysing wordsWhen you have gathered data in words, you're seeking

to use those words in an illuminative analysis of the

situation in which you are interested.

When working with words be aware that you are

working from a interpretivism paradigm:

• Knowledge is everywhere and is socially

constructed

• All kinds of information valid and worthy of the

name "knowledge", even things "of the mind“

• Specific accounts inform each other

• The act of trying to know should be conducted such

that the knower's own value position is taken into

account in the process.

interpretivism

• The main point about interpretivism is that we are interested in people and the way they interrelate, what they think and how they form ideas about the world, how their worlds are constructed.

• The key is understanding. What understandings do the people we are talking to have about the world, and how can we in turn understand these?

7.1.1.Constant comparative

method• The basic analytic method of the interpretive researcher is

constant comparison. • This involves going to your data again and again - this is the

constant bit• Comparing each element - phrase, sentence or paragraph- with

all the other elements - this is the comparative bit• There is nothing more complicated than that, although there

may be many different ways of going about the comparison.• From the constant comparison you merge with themes that

capture or summarise the content of your data.• These themes or categories of the essential building blocks of

your analysis• There are various ways in which you map your themes to show

the interconnections between them. The two methods used for mapping themes are network analysis and construct mapping

7.1.2.Network analysis

Network analysis: you and to show how one

idea is related to another using a network,

which is a bit like a tree, with a trunk which is

the basic idea, and branches coming off the

trunk representing constituent ideas.

This is useful where there is a core theme,

which comprises a range of subthemes.

Network analysis shows how the themes

related to one another with each branch

holding a range of ideas

It provides a hierarchical organisation of ideas

contained in your data.

7.1.3.Constructed mapping and

theme mapping

Construct mapping quits themes into sequential order from the

interview and uses lines and arrows to make connections between

the ideas and themes. It developed out of the idea of George

Kelly's personal construct theory. This is a complex theoretical

lens in which to analyse data.

In a similar manner, theme mapping, using constant comparative

method, helps establish the themes.

Once you've established themes, you go through your working

data files and look for good quotations that illustrate those

themes.

Then,in order that those quotations appear in the interview, put

them into boxes on the page. The page now becomes your map.

Enable the boxes with the names of the themes and draw dotted

lines if they seem to be connected and solid lines with errors

where one seem seems to account or explain another theme.

7.1.4. Grounded theory• Grounded theory offers a neat encapsulation of the

essence of interpretive enquiry: elect the ideas (the theory) emerge from your immersion in the situation rather than going in with fixed ideas (fixed theory) but what is happening.

• Many of the assumptions behind grounded theory seemed inappropriate and outdated now. In essence the constant comparison method is a kernel of grounded theory. The nuts and bolts of grounded theory procedures complex and you're advised to avoid them where possible.

• Stick to constant comparison method.

7.1.5. Discourse and content

analysis• Discourse analysis is the study of language in social

use. However it is spoken about in different ways in different branches of social sciences, resulting in confusion of the method.

• Psychologists think of discourse as the language that goes on between people, tending to focus on small units of language such as the choice of individual words and micro analysis involved.

• Whereas sociologists tend to think of discourse as forms of language that define social relationships particularly power relationships between, and among, people and look at macro analysis involved.

7.1.5. Discourse and content analysis

• The term content analysis is sometimes used when the

analysis refers to the written text rather than the spoken

word.

• For simplicity's sake the general method in analysing an

interview is broadly the same as in the constant comparative

method.

• The difference is in the focus of the discourse analyst: rather

than being at the first level on the general ideas, the focus

tends to be on the use of particular words, phrases,

metaphors et cetera.

• In each case the discourse analyst will look to see how

notions constructed by the choice of words and language

form used in the discourse.

• Discourse analysis stresses the coding aspect of the

analysis of an interview, paying more attention to the choice

and use of words and phrases rather than the overall theme.

7.2. ANALYSING NUMBERS

1. Statistics that describe

2. Statistics that understand the relationship between 2 variables

3. Statistics that help you to deduce or infer

7.2. Analysing numbers• Do not be intimidated by numbers! Statistics are not as hard

as you think; can be quite useful and help you determine

which research has found out.

• You need to understand that you know more about statistics

than you realise.

• Remind you the use of numbers in statistics comes in three

forms:

• 1. The categories of things: male or female. These are called

nominal or categorical data

• 2. Things we can put in order: first, second, third or top,

middle, bottom. These are called ordinal data. Although

there is an order indicated here there is no value implied

beyond this. Likert scale is an example of ordinal data

• 3. The everyday numbers: interval data because the

intervals between the numbers always the same

7.2. Analysing numbers

• By understanding the difference between the three levels of numbers you are able to utilise these in a meaningful way without confusing the data.

• Example you cannot multiply nominal data

• With small amounts of data you do not need to make use of SPSS.

• Your Microsoft Excel spreadsheet is more than sophisticated enough to handle the data and any statistical analysis needed.

7.2.1. Statistics that describe• Descriptive statistics or about this implication, organisation,

summary and graphical plotting of numerical data.• They are easy!• Descriptive data covers questions such as "how many; how

often; how frequent"• They are the simple statistics such as percentages and

averages• Do try and make numbers in your dissertation meaningful to

the reader by using statistics at the most basic level.The most common statistical data useful for all dissertations the following:Mean Mode MediumFrequency distributionStandard deviation

7.2.2. Statistics that understand the

relationship between 2 variables

You may want to look at two features of the situation and see whether the two are interrelatedYou're exploring the concept of co-variance: how things vary together.In a silly example we can show that shoe size and reading age co-vary: one goes up with the other !You're attempting to describe the extent of the connection between one variable and another: the correlation coefficient. This will be a number between -1 and +1. The nearer +1 the result is, the closer is the relationship between the two sets of scores.

7.2.3. Statistics that help you to

deduce or inferStatistics that help you deduce or infer are called inferential statistics. The former large part of statistics in social sciences.They used particularly when we are trying to interpret the results of an experiment.What the tests do is to enable you to say whether the results you have obtained are extendable beyond the date you have gathered in your sample.It answers the question: is the difference you have noted between the experimental group and the control group one in which you can rely for this purpose of extension, or is it one that may have occurred by chance in your study? This involves the discussion of ofprobability....the probability is less than 5 in 100 would have been by chance! "p < 0.05"This is all about significance testing: the figures relating to chance.The two most frequently used in statistics are chi-squared and the t-test.

How Not to gather data