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- 1. Concepts, indicators , variables/ Types of measurement scales
- 2. 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.) .
- 3. 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
- 4. 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
- 5. 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
- 6. 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 .
- 7. 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.
- 8. 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.
- 9. • 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 •
- 10. • 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.
- 11. Types of variables A-Independent and dependent variables (i.e., cause and effect)
- 12. 1-independent variable Definition : • 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.
- 13. • 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 ).
- 14. 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.
- 15. • 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.
- 16. • 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.
- 17. • 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.
- 18. 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
- 19. 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 .
- 20. • 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
- 21. 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
- 22. 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:
- 23. • 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.
- 24. 2- Ordinal or ranking scale • Ordered but differences between values are not exactly known • Besides categorizing individuals, or a property into subgroups on the 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.
- 25. • 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.
- 26. 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!)
- 27. 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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