RESEARCH PROBLEM , HYPOTHESES AND VARIABLES

1. INTRODUCTION

The research problem is often argued as the heart of the research process, without

which no research process can take place. In formulating the problem the variables

must be eminent and easily identifiable while a hypothesis should accompany each

research problem. Once a research problem is clearly defined, it should be translated

into a research hypothesis that states; a relationship between two or more variables in

one (or more) population(s).Thus the assignment will reflect on the linkage of the

research problem, research hypothesis and the existing variables.

Firstly, the research problem will be explored, its importance, sources of the research

problem, considerations as well as steps to be followed when formulating a research

problem. Secondly, identification of variables will be discussed using the three common

types of variables and the four prominent scales of measurement.Lastly,the

definition ,functions,characteristics,types and errors in testing hypothesis will be

discussed.

2. THE RESEARCH PROBLEM

A research problem is the first step and the most important requirement in the research

process. It serves as the foundation of a research study thus if well formulated, you

expect a good study to follow. According the Kerlinger; in order for one to solve a

problem, one must know what the problem is. The large part of the problem is knowing

what one is trying to do. A research problem and the way you formulate it determines

almost every step that follows in the research study. Formulation of the problem is like

the input into the study and the output is the quality of the contents of the research

report. A research problem is often accompanied by research question(s). A Research

Question is a statement that identifies the phenomenon to be studied. For example,

“What resources are helpful to new and minority drug abuse researchers?”

(www.theresearchassistant.com).

Bless et al (2006:29) write that, in some cases research problems or questions are

defined too vaguely and too generally. An important point to keep in mind when defining

or formulating a research problem is that it should be specific rather than general. When

a problem or question is specific and focused, it becomes amore answerable research

question than if it remained general and unfocused. A well formulated problem is

already a half-solved problem .A research problem is expressed as a general question

about the relationship between two or more variables. The formulation of a problem

introduces the necessity of defining clearly all concepts used and of determining the

variables and their relationships. If you know a lot about the topic, you can develop a

research question based on your own knowledge. If you feel you don't know much

about the topic, think again (www.esc.edu/esconline).

2.1THE IMPORTANCE OF FORMULATING THE RESEARCH PROBLEM

According to Kumar (2005:40) research formulation is like the identification of a

destination before undertaking journey. As in the absence of a destination, it is

impossible to identify the shortest-or indeed any –route in the absence of a clear

research problem, a clear economical plan is impossible. A research problem is like the

foundation of a building. The type and design of a building is dependant upon the

foundation of a building.

2.2 SOURCES OF RESEARCH PROBLEMS

Kumar (2005:41) writes that most research in the humanities revolves around four Ps

thus People, Problems, Programs, and Phenomena

2.3 CONSIDERATIONS IN SELECTING A RESEARCH PROBLEM

According to Kumar (2005:43) there are a number of considerations to keep in mind

when selecting a research problem/topic. These considerations are; interest,

magnitude, measurement of concepts, level of expertise, relevance, availability of data

and ethical issues. Bailey (1982:19) is of the contention that there are six factors

affecting problem selection. These factors are; the sociological paradigm, the

researcher’s values, the degree of reactivity inherent in a particular method deemed

appropriate for gathering data, the researcher’s methodology, the unit of analysis

chosen (small or big) and time factor thus, whether the study deals with a cross section

of the population at cone point in time or is a longitudinal study conducted over time.

Thus it can be deduced that a handful of considerations and factors should be

considered when selecting a research problem.

2.4 STEPS IN THE FORMULATION OF THE RESEARCH PROBLEM

According to http://wiki.answers.com,the following are Steps involved in formulating a

research problem:

1. Identify a broad area of interest in your academic /professional field.

2. Dissect the broad area into sub-areas by having a brain storming session with your

colleagues.

3. Select the sub-area in which you would like to conduct your research through the

process of elimination.

4. Reverse the research questions that you would like to answer through your study.

This can be after formulation of the objectives of can lead you to the formulation of the

objective.

5. Assess these objectives to ascertain the feasibility of attaining them in the light of

time and other issues like finances and human resource expertise.

3. IDENTIFYNG VARIABLES

The following working definitions of variable can be outlined;

An entity that varies from one observation to the next, an empirical property that

is capable of taking two or more values(Bless et al 2006;30)

A property that takes on different values(Kumar 2005:56)

Thus from the above definitions it can be deduced that a variable is a measurable factor

that can assume more than one value, hence age,income,gender,pay,job satisfaction

can be classified as values.

Considering the statement below as an example;

The impact of remuneration on the rate of turnover in South African local

Municipalities: The case of Buffalo City Municipality.

The terms remuneration and turnover represents variables because both can assume

two or more values while impact is a concept. Concepts are mental images or

perceptions and therefore their meanings vary markedly from individual to individual,

whereas variables are measurable, of course with varying degrees of accuracy.

Measurability is the main difference between a concept and a variable. A concept

cannot be measured whereas a variable can be subjected to measurement by

crude/refined or subjective/objective units of measurement (Kumar 2005:56).

In some cases the researcher might expect a causal relationship to exist between

variables, where a variation in one results in a variation in the other (Bless et al

2006:300).Taking the above example, the amount of remuneration of municipal

employees may result in a variation of the rate at which the employees leave(turnover)

the municipality.Leedy and Ormrod (2001:233) are of the opinion that when we

investigate cause-and-effect relationships, we are, of course, looking at the extent to

which one variable(the cause) influences another variable(the effect).ln an experimental

study, the researcher in some ways changes, or manipulates, one or more variables in

the environment and then measures the effects that such changes have on something

else.ln research in the social sciences and education ,the “something else” being

affected is often some form of human behavior.ln medical research, it might it might be

people’s physical healthy or well-being.

3.1 TYPES OF VARIABLE

Bless et al (2006:30) write that, independent and dependant are two most important

types of variable. Variables may have particular roles in a certain problem. Thus the

common types of variables can now be discussed.

3.1.1 INDEPENDENT VARIABLES

Bless et al (2006:30) define independent variables (indicated by IV) as variables

influencing other variables, thereby determining the values of these affected

variables.Leedy and Ormrod (2001:233) define an independent variable as a variable

that the researcher manipulates. Taking the earlier example, remuneration is the

manipulated value which can influence the behavior of employees.

3.1.2 DEPENDANT VARIABLES

Indicated by DV, are variables whose values are influenced by the value of other values

(Bless et al 2006:30). Leedy and Ormrod (2001:233) define dependent value as a

variable that is potentially influenced by the independent variable, because it is

influenced by, and thus to some extent depends on the independent variable. Also

considering the example, turnover is the dependant variable because it depends on the

other variable (independent) which is remuneration.

3.1.3 EXTRANEOUS VARIABLES

Kumar (2005:60) defines extraneous variable as several other factors operating in a

real-life that may affect changes in the dependant variable. These factors, not measured

in the study may, may increase or decrease the magnitude or strength of the

relationship between independent and dependant variables. Considering the same

example as in above apart from remuneration influencing turnover some factors like

working hours, working environment, career growth may also have an influence even

though they are not being investigated.

3.2 TYPES OF MEASUREMENT SCALE

Measurement is essential to an enquiry especially when it is scientific. Stevens

(1978:52) in Kumar (2005:67) classified the different types of measurement scale into

four categories namely; nominal or classificatory scale, ordinal or ranking scale. Interval

scale and lastly ratio scale.

3.2.1 Nominal Scale

A nominal scale enables the classification of individuals, objects or responses based on

common/shared property or characteristic for example gender can be classified into two

sub-categories; male and female. Similarly citizens in The Republic of South Africa can

be classified into two main sub-categories: the First economy and the second economy.

3.2.2 Ordinal Scale

The ordinal scale has all the properties of a nominal scale plus one of its own. The

simplest ordinal scale is a ranking. When a market researcher asks one to rank 5 types

of beer from most flavourful to least flavourful, he/she is asking one to create an ordinal

scale of preference. There is no objective distance between any two points on your

subjective scale. For you the top beer may be far superior to the second preferred beer

but, to another respondent with the same top and second beer, the distance may be

subjectively small. An ordinal scale only lets you interpret gross order and not the

relative positional distances. Ordinal data would use non-parametric statistics. These

would include: Median and mode

rank order correlation

non-parametric analysis of variance. (http://www.csse.monash.edu.au)

3.2.3 Interval

The standard survey rating scale is an interval scale. When you are asked to rate your

satisfaction with a piece of software on a 7 point scale, from Dissatisfied to Satisfied,

you are using an interval scale. It is an interval scale because it is assumed to have

equidistant points between each of the scale elements. This means that we can

interpret differences in the distance along the scale. We contrast this to an ordinal scale

where we can only talk about differences in order, not differences in the degree of order.

Interval scales are also scales which are defined by metrics such as logarithms. In

these cases, the distances are not equal but they are strictly definable based on the

metric used.

3.2.4 Ratio Scale

A ratio scale is the top level of measurement and is not often available in social

research. The factor which clearly defines a ratio scale is that it has a true zero point.

The simplest example of a ratio scale is the measurement of length (disregarding any

philosophical points about defining how we can identify zero length). The best way to

contrast interval and ratio scales is to look at temperature. The Centigrade scale has a

zero point but it is an arbitrary one. The Fahrenheit scale has its equivalent point at -

32o. (Physicists would probably argue that Absolute Zero is the zero point for

temperature but this is a theoretical concept.) So, even though temperature looks as if it

would be a ratio scale it is an interval scale. Currently, we cannot talk about no

temperature - and this would be needed if it were a ration scale.

(http://www.csse.monash.edu.au)

4. HYPOTHESES FORMULATION

Hypotheses, though important, are not essential for a study. A perfectly valid study can

be conducted without constructing a single hypothesis. There are however many

definitions of a hypothesis but for the purpose of this assignment the following

definitions can be given;

… a conjectural statement of the relationship between two or more variables

(Kerlin 1986:17).

… a tentative assumption or preliminary statement about the relationship

between two or more things that needs to be examined(Welman et al 2005:12

… tentative statement about something, the validity of which is usually unknown

(Black and Champion 1976:126).

… a proposition that is stated in a testable form and that predicts a particular

relationship between two (or more) variables.ln other words, if we think that a

relationship exists, we first state it as a hypothesis and then test the hypothesis in

the field (Bailey 1978:35).

Thus from the given definitions it can be deduced that a hypothesis is a premade

statement of the results of an investigation indicating the relationship between two or

more variables that awaits verification.

4.1 FUNCTIONS OF A HYPOTHESIS

Hypotheses are important for bringing clarity, specifity and focus to a research study

(Kumar 2005:79).Hypotheses does so by exposing ;the specific aspects of a research

problem, important data to a study, focus and finally may enable the researcher to add

to the formulation of theory. Hypotheses may only add to the formulation of theory after

they have been proven to be true.

4.2 CHARACTERISTICS OF A HYPOTHESIS

Kumar (2005:75) outlines four major aspects of a hypothesis. Firstly a hypothesis

should be simple, specific and conceptually clear.Secondly,it should be capable of

verification.Thirdly,it should be related to the existing body of knowledge and lastly it

should be operationalisable thus expressible in terms that can be measured.

4.3 TYPES OF HYPOTHESIS

Broadly, there are two categories of hypothesis namely, the research hypothesis and

the alternate hypothesis. The research hypothesis is the basis of an investigation and is

usually indicated by H1.The alternate hypothesis there to explicitly specify the

relationship that will be considered true if in case the research hypothesis proves to be

wrong.

4.4 ERRORS IN TESTING A HYPOTHESIS

Incorrect conclusions about the validity of a hypothesis can be reached if; the study

design selected is faulty, the sampling procedure adopted is faulty, the method of data

collection is inaccurate, analysis is wrong, statistical procedures applied are

inappropriate and conclusions drawn are incorrect .There are two common errors when

testing a hypothesis. The first error involves rejection of a null hypothesis when it is true

and this is called Type 1 error. The second error involves acceptance of a null

hypothesis when it is false and this is called Type 11 error(Kumar 2005:79) .Thus when

testing a hypothesis especially when more numerical figures are involved, it is essential

that every step should be approached with utmost discreetness or else Type 1 or 11

errors may occur.

5. CONCLUSION

The research problem is the heart of the research process hence can not be selected in

a vacuum thus some considerations and factors have to be considered. Sources of

research problems revolve around the four P’s, People, Problems, Programs, and

Phenomena. Formulation of a research problem is a process thus involves following

steps. Variables are measurable factors that can assume more than one value and

three types of important variables can distinguished; independent, dependant and

extraneous variables. Nominal scale, ordinal scale, interval scale and ratio scale are the

different types of measurement scale which we use to classify variables. A hypothesis is

a tentative statement of the results of an investigation indicating the relationship

between two or more variables that awaits verification. Hypotheses enable the

researcher to add the formulation of theory if proved to be true. The research

hypothesis and the alternate hypothesis are the most important when carrying out or

analyzing research process. However errors my occur when testing hypothesis, Type 1

and Type 2 errors are the common errors. Conclusively a research problem is vital to

the research process, and each problem will always variables whose relationship is

expressed in the research hypothesis, thus there is a close relationship between the

research problem, the variables and the hypothesis.

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Kerlinger, Fred N. (1973) Foundations of Behavioral Research. 2nd edition. Holt,

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Kumar, R. (2005).Research Methodology: A Step by Step Guide for Beginners. London,

Thousand Oaks, New Delhi: Sage Publications.

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