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Concepts, indicators , variables/ Types of measurement scales

Definitions of a variable:

• 1-A characteristic, number or quality that that increases or decreases over time, or takes different values in different situations.

• 2-An image, perception or concept that can be measured – hence capable of taking on Different values.

• 3-a label or name that represents a concept or characteristic of the subjects that varies (e.g., gender, weight, achievement, etc.) .

Other definitions of variables :-

a-Conceptual definition: uses concepts to define a variable :• 1-Achievement: what one has learned from formal

instruction • 2-Aptitude: one's capability for performing a particular

skill b-Operational definition: is an indication of the meaning of a

variable through the specification of the manner by which it is measured:

• 1-Weschler IQ score • 2-Income levels below and above 45,000 pounds per year

Concepts:• They are terms which people create for the

purpose of communication and efficiency • Concepts are mental images or perceptions

and therefore their meaning varies markedly from individual to individual.

• E.g. : • personal impression about an object?• Vary in meaning & cannot be measured

directly

Identifying Variables from concepts:

• In a research , it is important that the concepts used should be operationalised in

measurable terms( so that variations in respondents’ answers are reduced ,if not eliminated).

• Techniques about how to operationalise concepts, play an important role in reducing this variability

The 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.

• It is therefore important for the concept to be converted into variables .

INDICATOR:

• Is a computed or collated collective characteristics of the persons under study.

• Is a set of criteria reflected from the concept. Indicator can then be converted into variables.

• Indicators are used to show whether or not the objectives have been achieved.

Concepts, indicators and variables:• When using a concept in the study, researcher

need to develop indicators from the concept, • that is, developing from these indicators,

measurable variable. • this is what is called operationalization , • operationalization is thus a process of

quantifying variables for the purpose of measuring their: occurrence, strength and frequency.

• For example, to determine this concept ?• the level of knowledge , concerning a specific

issue • The variable :poor knowledge, will assist in

determining factors influencing the problem under study

•

• Some times the research team in a particular case decide that one indicator is not enough, more are needed to fully measure or quantify the concept.

• E.g. Psychologists have built entire questionnaires to measure complex concepts such as depression, where a range of questions on mood and emotion are then scored

• Then a persons depression level or ‘score’ is established.

Types of variables

A-Independent and dependent variables (i.e., cause and effect)

1-independent variableDefinition :• is a factor that can be varied or manipulated in

an experiment under the control of the experimenter (e.g. time, temperature, etc).

• It is usually what will affect the dependent variable

• Independent variables act as the "cause" in that they precede, influence, and predict the dependent variable.

• There are two types of independent variable, which are often treated differently in analyses:

• 1- quantitative variables that differ in amounts or scale and can be ordered (e.g. weight, temperature, time).

• 2- qualitative variables which differ in "types" and can not be ordered (e.g. gender, method of treatments ).

2- DEPENDENT VARIABLE

• Is the variable that is used to describe or measure the problem under study.

• They describe or measure the factors that are assumed to cause or at least influence the problem.

• It can take different values in response to an independent variable.

• Dependent Variable is something that might be affected by the change in the independent variable.

• Whether a variable is dependent or independent, is determined by the statement of the problem and the objectives of the study.

• It is therefore important when designing an analytical study to clearly state which variable is the dependent and which variable are the independent.

• For example, in a study of the relationship between smoking and lung cancer,

• 'suffering from lung cancer' ,would be the dependent variable and

• 'smoking' (varying from not smoking to smoking more than three packets a day) the independent variable.

• Note that if a researcher investigates why people smoke, ?

• 'smoking' is the dependent variable, and• 'pressure from peers to smoke' could be an independent

variable. • While In the lung cancer study ' smoking' was the

independent variable.

• For example, to test a hypothesis that eating carrots improves vision?

• eating carrots is the independent variable. Each subject’s vision would be tested to see if carrot eating had any effect.

• vision is the dependent variable. • The subjects assigned to eat carrots are in the

experimental group, whereas subjects not eating carrots are in the control group.

3- confounding / or Interfering variables

• Confounding variables are those that vary systematically with the independent variable and exert influence of the dependent variable . Confounding variables are not the principal interest in the study. They distorts the result of the study

• For example, not using counselors with similar levels of experience in a study & then comparing the effectiveness of two counseling approaches

4 -Controlled Variable• a variable that is not changed, is also called constants• For Example: Students of different ages were given the

same problem to solve. They were timed to see how long it took them to finish the exercise.

• in this investigation the independent variable? • Ages of the students( Different ages were tested by the

scientist), • the controlled variable? • same problem to solve • It would not have been a fair test if some had an easy

problem to solve and some had a harder problem to solve .

• Example:• The temperature of water was measured at

different depths of a pond.• Independent variable – depth of the water• Dependent variable – temperature• Controlled variable – thermometer

5-Quantitative variables &Qualitative

• 1- Qualitative variables(categorical) : are measured and assigned to groups on the basis of specific characteristics .Not expressed numerically. E.g. Sex, ethnic group, Socio-economic status, and outcome of disease

• 2- Quantitative variables(Continuous) : Expressed numerically. E.g. Age, height, weight blood pressure, Continuous variables are measured on a scale that theoretically can take on an infinite number of values

Scales of Measurement

• Measurement is the foundation of any scientific investigation

• Data comes in various sizes and shapes and it is important to know about these so that the proper analysis can be used on the data.

• There are usually four scales of measurement that must be considered:

• 1-Nominal or classificatory scale• classification data, e.g. m/f • no ordering, e.g. it makes no sense to state that M > F • enables the classification of individuals, objects or

responses into subgroups based on a common/shared property or characteristic.

• A variable measured on a nominal scale may have one, two or more subcategories depending upon the extent of variation.

• For example, ’water’ have only one subgroup, whereas the variable “gender” are classified into two sub-categories: male and female.

• The sequence in which subgroups are listed makes no difference as there is no relationship among subgroups.

2- Ordinal or ranking scale• Ordered but differences between values are not exactly

known• Besides categorizing individuals, or a property into subgroups

onthe basis of common characteristic, it ranks the subgroups in a

certain order.• They are arranged either in ascending or descending order

according to the extent a• subcategory reflects the magnitude of variation in the

variable.

• For example, ‘income’ can be measured either quantitatively or qualitatively using subcategories:

• ‘above average’, ‘average’ and ‘below average’. • The ‘distance’ between these subcategories are

not equal as there is no quantitative unit of measurement.

• ‘Socioeconomic status’ and ‘attitude’ are other variables that can be measured on

• ordinal scale.

3-Interval scale

• An interval scale has all the characteristics of an ordinal scale. In addition, it uses a unit of measurement with an arbitrary starting and terminating points.

• For example,• Celsius scale: 0°C to 100°C• Fahrenheit scale: 32°F to 212°F• The variables are ordered, constant scale are used , but

there is no natural zero(no true zero) • Here differences make sense, but ratios do not (e.g.,

30°-20°=20°-10°, but 20°/10° is not twice as hot!)

4-Ratio scale• The ratio scale is a measurement scale where the interval

between successive points can be measured using a defined numerical scale and

• where the zero point means absence of the characteristic being measured.

• A ratio scale has all the properties of nominal, ordinal and interval scales plus its own property: the zero point of a ratio scale is fixed, which means?

• This scale it has a fixed starting point. • The measurement of variables like income, age, height and

weight are examples of this scale. • A person who is 40 year old is twice as old as one who is 20

year old.• Other e.g., height, weight, age, length

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