Presentation is loading. Please wait.

Presentation is loading. Please wait.

BASIC TERMS IN RESEARCH: LECTURE 2 CONCEPTS VARIABLES HYPOTHESIS THEORY 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 1.

Similar presentations


Presentation on theme: "BASIC TERMS IN RESEARCH: LECTURE 2 CONCEPTS VARIABLES HYPOTHESIS THEORY 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 1."— Presentation transcript:

1 BASIC TERMS IN RESEARCH: LECTURE 2 CONCEPTS VARIABLES HYPOTHESIS THEORY 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 1

2 BASIC TERMS IN RESEARCH CONCEPTS – DEFINE AND EXPLAIN – DISTINGUISH BETWEEN ABSTRACT AND CONCRETE CONCEPTS 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 2

3 BASIC TERMS VARIABLES – DEFINE AND EXPLAIN – CLASSIFY VARIABLES NATURE OF VARIATION THE ROLE THEY PLAY IN RESEARCH THEORY – DEFINE AND EXPLAIN – RELATIONSHIP BETWEEN THEORY, CONCEPTS VARIABLES AND HYPOTHESIS 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 3

4 WHAT ARE CONCEPTS IN RESEARCH? DEFINING AND EXPLAINING CONCEPTS. A concept is a term that abstractly describes and names an object or phenomenon by providing it with a separate identity or meaning. (Burn and Grove, 1993.) They are words that label, name, classify or define objects, experiences, events, phenomenon or relationships (Sarantakos, 2000) 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 4

5 WHAT ARE CONCEPTS IN RESEARCH? DEFINING AND EXPLAINING CONCEPTS. A concept can be An idea Word Phrase 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 5

6 WHAT ARE CONCEPTS IN RESEARCH? SOME EXAMPLES Man Age Income Height Weight Gender Level of Education SOME EXAMPLES Leadership, Honesty, Competence Productivity, openness Morale Motivation Inflation Happiness Authority Bureaucracy Power Self-esteem 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 6

7 WHAT ARE CONCEPTS IN RESEARCH? A concept can be: 1.Concrete Eg. Income; Weight; Height; Age 2.Abstract Eg. Adolescent; Youth; Green; Authority Concepts are the building blocks of Theory 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 7

8 WHAT IS A VARIABLE DEFINING AND EXPLAINING VARIABLES A variable is: A concept that varies. It can take on two or more values. A variable is a concept that takes on different values. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 8

9 WHAT ARE VARIABLES? Variable Gender Income Educational Attainment Attitude Age Temperature Religion Height Weight Political Affiliation Values Male; Female High; Middle; Low High; Average; Low Strongly agree; Agree; Old; Young; Child; Adult Hot; Cold Christian; Moslem; Tall; Short Heavy; Light ABC; DSP; BBA; PCC 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 9

10 CLASSIFYING VARIABLES BY THE NATURE OF VARIATION 1.CATEGORICAL AND QUANTITATIVE / CONTINUOUS VARIABLES When the variations of the variable are associated with specific categories, we refer to them as categorical variables So variables are CATEGORICAL if they can be classified into distinct categories) according to some characteristics, attribute or property. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 10

11 CLASSIFYING VARIABLES BY THE NATURE OF VARIATION The variation represent different kinds of categories. Such variables do not fall along any continuum of measurement. The variation is simply identifying a property as having two or more distinct categories 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 11

12 SOME EXAMPLES: VARIABLE GENDER EYE COLOUR AGE TEMPERATURE VALUES / CATEGORIES MALE; FEMALE BLUE; BROWN; GREEN YOUNG; OLD HOT; COLD 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 12

13 CLASSIFYING VARIABLES BY THE NATURE OF VARIATION Variables are continuous or quantitative if they can be measured in the numerical sense. The values can be divided into fractions Can take on infinite number of values Can take on values within a certain range In some cases values cannot be into divided fractions 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 13

14 SOME EXAMPLES The values can be divided into fractions Can take on infinite number of values Can take on values within a certain range In some cases values cannot be divided into fractions Height of all level 300 RM class (6ft. 1inch; 5ft. 8inch, Ages of students ( 21, 19, 18, 30, 35 ect) Income of Bankers (Ghc 4000-9000 /Month Football scores; Number of correct answers in a test. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 14

15 CLASSIFYING VARIABLES BY THE NATURE OF VARIATION 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 15

16 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PEFORM IN RESEARCH 1.DEPENDENT VARIABLE 2.INDEPENDENT VARIABLE 3.MODERATING VARIABLE 4.INTERVENING VARIABLE 5.EXTRANEOUS VARIABLE 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 16

17 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH 1.INDEPENDENT VARIABLE This is the presumed causal variable in a relationship. Manipulation or variation of this variable is assumed to be the cause of change in other variables. Independent Variable is the CAUSE VARIABLE. It causes a change to occur in the DEPENDENT VARIABLE 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 17

18 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH 2.THE DEPENDENT VARIABLE The variable that the independent variable is presumed to affect is called the dependent (or outcome) variable. The nature of the dependent variable "depends on" what the independent variable does to it, how it affects it. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 18

19 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH AN EXAMPLE An experiment seeks to examine the relationship between sunlight and the growth of plants. Independent Variable: SUNLIGHT Dependent Variable: GROWTH OF PLANTS 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 19

20 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH ANOTHER EXAMPLE Students of different ages were given the same jigsaw puzzle to put together. They were timed to see how long it took to finish the puzzle. Identify the variables in this investigation. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 20

21 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH What was the independent variable? Ages of the students – Different ages were tested by the scientist What was the dependent variable? The time it took to put the puzzle together – The time was observed and measured by the scientist 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 21

22 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH ONE MORE EXAMPLE The higher the temperature of water, the faster an egg will boil. Independent variable – temperature of water Dependent variable – time to cook an egg 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 22

23 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH THE LAST EXAMPLE Research studies indicate that successful new product development has an influence on the stock market price of a company. Independent Variable Success of new product Dependent Variable Stock market price 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 23

24 GRAPHICAL REPRESETATION OF INDEPENDENT AND DEPENDENT VARIABLES In statistical analysis a variable is identified by the symbol (X) for the independent variable and by (Y) for the dependent variable. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 24

25 LABELS ASSOCIATED WITH INDEPENDENT AND DEPENDENT VARIABLES Independent Variable Presumed cause Stimulus Predicted from Antecedent Manipulated Predictor Dependent Variable Presumed effect Response Predicted to Consequence Measured Outcome Criterion 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 25

26 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH 3. MODERATING VARIABLE A moderating variable is one that has a strong contingent effect on the independent variable- dependent variable relationship. That is, the presence of the moderating variable modifies the original relationship between the independent and the dependent variable. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 26

27 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH EXAMPLE: A strong relationship has been observed between the quality of library facilities (X) and the performance of the students (Y). Although this relationship is supposed to be true generally, it is nevertheless contingent on the interest and inclination of the students. It means that only those students who have the interest and inclination to use the library will show improved performance in their studies. In this relationship interest and inclination is moderating variable i.e. which moderates the strength of the association between X and Y variables. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 27

28 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH 4. INTERVENING / MEDIATING VARIABLE It comes between the independent and dependent variables and shows the link or mechanism between them. It explains the relationship between the independent and dependent variables; it does not change the relation, it only explains it. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 28

29 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH EXAMPLE A theory of suicide states that married people are less likely to commit suicide than single people. The assumption is that married people have greater social integration (e.g. feelings of belonging to a group or family). Hence a major cause of one type of suicide was that people lacked a sense of belonging to group (family). 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 29

30 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH Restatement of the theory Marital status (independent variable) causes the degree of social integration (intervening variable), which affects suicide (dependent variable). 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 30

31 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH ANOTHER EXAMPLE Five-day work-week results in higher productivity. What exactly is that factor which theoretically affects the observed phenomenon but cannot be seen? Its effects must be inferred from the effects of independent variable on the dependent variable. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 31

32 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH In this work-week hypothesis, one might view the intervening variable to be the job satisfaction. Rephrase the statement: The introduction of five-day work week (IV) will increase job satisfaction (IVV), which will lead to higher productivity (DV). 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 32

33 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH 5.EXTRANEOUS VARIABLES These are undesirable variables that influence the relationship between the variables under investigation. They influence the outcome of a study, though they are not the variables that are actually of interest. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 33

34 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH EXAMPLE The relationship between background music and task performance amongst employees at a packing facility Independent variable: Background music Dependent variable: Task performance 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 34

35 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH Extraneous variables that can affect the Independent variable: ▪Type of background music (e.g., rap music, dance music, easy listening, classical music, etc.) ▪Loudness of background music (e.g., low, medium, high volumes, etc.) ▪Time of day when the background music was played (e.g., morning, afternoon, night, etc.) 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 35

36 CLASSIFYING VARIABLES BY THE FUNCTIONS THEY PERFORM IN RESEARCH Extraneous variables that could also affect the dependent variable: Employee tiredness Employee motivation Job satisfaction 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 36

37 HYPOTHESIS DEFINING AND EXPLANING HYPOTHESIS A proposition to be tested or a tentative statement of a relationship between two or more variables (Neuman, 2003) A testable proposition, one in which the relationship underlying the concepts are operationally defined 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 37

38 HYPOTHESIS Some examples 1.Officers in my organization have higher than average level of commitment 2.Level of job commitment of the officers is associated with their level of efficiency 3.Level of job commitment of the officers is positively associated with their level of efficiency 4.The higher the level of job commitment of the officers the lower the level of their absenteeism 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 38

39 TYPES OF HYPOTHESIS 1.DESCRIPTIVE HYPOTHESIS Contains only one variable (Univariate Hypothesis). Descriptive hypotheses typically state the existence, size, form, or distribution of some variable. Example: Officers in my organization have higher than average level of commitment (variable). This contains only one variable. It only shows the distribution of the level of commitment among the officers of the organization which is higher than average. Such a hypothesis is an example of a Descriptive Hypothesis. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 39

40 TYPES OF HYPOTHESIS 2. RELATIONAL HYPOTHESIS These are the propositions that describe a relationship between two variables. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 40

41 TYPES OF HYPOTHESIS TYPES OF RELATIONAL HYPOTHESIS Non-directional Directional (Positive/Negative) Causal Correlational. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 41

42 TYPES OF HYPOTHESIS 3.CORRELATIONAL HYPOTHESIS State merely that the variables occur together in some specified manner without implying that one causes the other. FOR EXAMPLE: Level of job commitment of the officers is positively associated with their level of efficiency. Here we do not make any claim that one variable causes the other to change. That will be possible only if we have control on all other factors that could influence our dependent variable. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 42

43 TYPES OF HYPOTHESIS 4.EXPLANATORY (CAUSAL HYPOTHESIS) Imply the existence of, or a change in, one variable causes or leads to a change in the other variable. This brings in the notions of independent and the dependent variables. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 43

44 DIFFERENT WAYS TO STATE HYPOTHESIS High motivation causes high efficiency. High motivation leads to high efficiency. High motivation is related to high efficiency. High motivation influences high efficiency. High motivation is associated with high efficiency. High motivation produces high efficiency. High motivation results in high efficiency. If high motivation then high efficiency. The higher the motivation, the higher the efficiency 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 44

45 ROLE OF HYPOTHESIS IN RESEARCH It guides the direction of the study It identifies facts that are relevant and those that are not It suggests which form of research design is likely to be the most appropriate It provides a framework for organizing the conclusions of the findings 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 45

46 NULL AND ALTERNATE HYPOTHESIS NULL HYPOTHSIS It is used for testing the hypothesis formulated by the researcher. The null hypothesis simply states that there is no relationship between the variables or the relationship between the variables is “zero.” That is how symbolically null hypothesis is denoted as “H0”. For example: H0 = There is no relationship between the level of job commitment and the level of efficiency. Or H0 = The relationship between level of job commitment and the level of efficiency is zero. Or The two variables are independent of each other. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 46

47 NULL AND ALTERNATE HYPOTHESIS ALTERNATE HYPOTHESIS The alternative (to the null) hypothesis simply states that there is a relationship between the variables under study. In our example it could be: there is a relationship between the level of job commitment and the level of efficiency 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 47

48 NULL AND ALTERNATE HYPOTHESIS The relationship is perfect which is indicated by the number “1”. Thereby the alternative hypothesis is symbolically denoted as “H1”. It can be written like this: H1: There is a relationship between the level of job commitment of the officers and their level of efficiency. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 48

49 THEORY WHAT IS THEORY A set of interrelated concepts, definitions and propositions that presents a systematic view of phenomena by specifying relations among variables, with the purpose of explaining and predicting the phenomenon. (Cohen and Manion, 1994). 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 49

50 THEORY A theory is a systematic attempt to explain something like: Why do people commit crimes? How do the media affect us? Why do people believe in God? Why do people get married? Why do kids play truant from school? 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 50

51 THEORY The key element in the definitions of theory is a PROPOSITION This is a statement concerned with the logical relationships among concepts. EXAMPLE An expansion in a bar of metal occurs when it is heated. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 51

52 THEORY To have a theory … There must be concepts There must be a proposition Proposition must state the relationship between the concepts 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 52

53 THEORY An expansion in a bar of metal occurs when it is heated. The statement (proposition) above can be explained as follows: Metals are made up of atoms The structure of an atom is changed by heat Heat causes atoms to expand 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 53

54 THEORY The proposition contains a number of concepts: Heat Atoms Metals Expansion 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 54

55 THEORY Theory explains the relationship between these concepts in the proposition Theory: a set of propositions Propositions: are made up of concepts Without concepts we have no theory Hence : Concepts are the building blocks of theories. 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 55

56 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 56 REMEMBER SUCCESS COMES BEFORE WORK ONLY IN THE DICTIONARY. Attributed to Vince Lombardi


Download ppt "BASIC TERMS IN RESEARCH: LECTURE 2 CONCEPTS VARIABLES HYPOTHESIS THEORY 3/10/2014 INFS 323: DEPARTMENT OF INFORMATION STUDIES; DR. E. ADJEI 1."

Similar presentations


Ads by Google