Summary ''Quantitative Research''

QUANTITATIVE RESEARCH
 What is quantitative research?
Quantitative research is defined by Bryman and Bell (2005, p. 154) that
‘‘entailing the collection of numerical data and exhibiting the view of relationship between theory and research as deductive, a predilection for natural science approach, and as having an objectivist conception of social reality’’.
So the this specific form of research uses the quantitative data to analysis.The specificity of quantitative research lies in the next part of the definition. In quantitative research, we collect numerical data. This is closely connected to the final part of the definition: analysis using mathematically.
DOING QUANTITATIVE RESEARCH IN EDUCATION WITH SPSS
Qualitative data are not necessarily or usually numerical, and therefore cannot be analysed by using statistics. Quantitative research is essentially about collecting numerical data to explain a particular phenomenon, particular questions seem immediately suited to being answered using quantitative methods. All questions  can look at quantitatively, as the data we need to collect are already available to us in numerical form.  Like :
1. How many males get a first-class degree at university compared to females?
2. What percentage of teachers and school leaders belong to ethnic minority groups?
3.Has pupil achievement in English improved in our school district over time?
Foundations of quantitative research methods
‘’Realism, subjectivism and the ‘paradigm wars’’’
Qualitative research is actually an umbrella term encompassing a wide range of methods, such as interviews, case studies, ethnographic research and discourse analysis, to name just some examples. The difference between quantitative and qualitative research is often seen as quite fundamental, leading people to talk about ‘paradigm wars’ in which quantitative and qualitative research are seen as warring and incommensurable fractions. Many researchers define themselves as either quantitative or qualitative. To label all quantitative researchers positivists is equally inaccurate. Quantitative researchers have taken up many criticisms of positivist views, and there is now a variety of epistemologies underlying theory and practice in quantitative research.
When do we use quantitative methods?
1. The first type of research question is that demanding a quantitative answer. Examples are: ‘How many students choose to study education?’
2. Numerical change can likewise accurately be studied only by using quantitative methods. Example:Are the numbers of students in our university rising or falling?
3. As well as wanting to find out about the state of something or other, we often want to explain phenomena. Example: What factors predict the recruitment of maths teachers?
As we will see later on in this book, this kind of question can also be studied successfully by quantitative methods, and many statistical techniques have been developed that allow us to predict scores on one factor, or variable (e.g. teacher recruitment) from scores on one or more other factors, or variables (e.g. unemployment rates, pay, conditions).
 4. The final activity for which quantitative research is especially suited is the testing of hypotheses. We might want to explain something . For example, whether there is a relationship between pupil’s achievement and their self-esteem and social background.
What is a hypothesis?
 A hypothesis is a tentative explanation that accounts for a set of facts and can be tested by further investigation. For example, one hypothesis we might want to test is that poverty causes low achievement, or that there is a relationship between pupils’ self-esteem and the amount of time they spend watching television.
Units and variables
 When we collect data in quantitative educational research, we have to collect them from someone or something. The people or things (e.g. schools) we collect data on or from are known as units or cases. The data that we are collecting from these units are known as variables. Variables are any characteristic of the unit we are interested in and want to collect (e.g. gender, age, self-esteem). The label ‘variable’ refers to the fact that these data will differ between units. For example, achievement will differ between pupils and schools, gender will differ between pupils, and so on. If there are no differences at all between the units we want to study, we probably aren’t going to be able to do any interesting research (for example, studying whether pupils are human would not yield interesting findings).