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Quantitative Paradigm: Causal Comparative & Correlational Studies

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Presentation on theme: "Quantitative Paradigm: Causal Comparative & Correlational Studies"— Presentation transcript:

1 Quantitative Paradigm: Causal Comparative & Correlational Studies
Nawwar Zada

2 * Qualitative and Quantitative Defined
- The simplest way to distinguish between qualitative and quantitative may be to say that qualitative methods involve a researcher describing kinds of characteristics of people and events without comparing events in terms of measurements or amounts. - Quantitative methods, on the other hand, focus attention on measurements and amounts (more and less, larger and smaller, often and seldom, similar and different) of the characteristics displayed by the people and events that the researcher studies.

3 Characterization of Qualitative by Set of Writers :

4 1- Qualitative research is multi-method in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret phenomena in terms of the meanings people bring to them. - Qualitative research involves the studied use and collection of a variety of empirical materials-case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts that describe routine and problematic moments and meanings in people's lives. (Denzin & Lincoln, 1994, p.2)

5 2- Qualitative researchers seek to make sense of personal stories and the ways in which they interact. Qualitative inquiry is an umbrella term for various philosophical orientations to interpretive research. For example, qualitative researchers might call their work ethnography, case study, phenomenology, educational criticism, human ethnology, ecological psychology, holistic ethnography, cognitive anthropology, ethnography of communication, symbolic interactionism, micro-ethnography, ethnomethodology, and postmodern ethnography (or) partid-patory research. (Glesne & Peshkin, 1992, pp. 1)

6 While Quantitative is Characterized by Two Sets of Writers as Following:

7 1. Quantitative research uses numbers and statistical methods
1. Quantitative research uses numbers and statistical methods. It tends to be based on numerical measurements of specific aspects of phenomena; it abstracts from particular instances to seek general description or to test causal hypotheses; it seeks measurements and analyses that are easily replicable by other researchers. (King, Keohane, & Verba, pp. 3-4)

8 2. Quantitative researchers seek explanations and predictions that will generalize to other persons and places. Careful sampling strategies and experimental designs are aspects of quantitative methods aimed at produce generalizable results. In quantitative research, the researcher's role is to observe and measure, and care is taken to keep the researchers from “contaminating" the data through personal involvement with the research subjects. Researchers "objectivity" is of utmost concern. (Glesne & Peshikin, 1992, p. 6)

9 * Types of Quantitative Researches: 1- Survey research 2- Causal-comparative research 3- Correlational research 4- Experimental research

10 * Data Collection: Data collection is the process by which the researcher collects the information needed to answer the research problem. * Data Collection Tools: Questionnaire Checklist Distribution Interview Observation Records Experimental Approach Survey Approach

11 CAUSAL-COMPARATIVE METHOD
OR EX POST FACTO RESEARCH

12 - Causal-comparative research looks to uncover a cause and effect relationship. This research is not conducted between the two groups on each other. Rather than look solely for a statistical relationship between two variables it tries to identify, specifically, how the different groups are affected by the same circumstance. Causal-comparative research involves ‘comparison’. - In causal-comparative research the study of two or more groups is done without focusing on their relationship. As always the use of statistical analysis is engaged to synthesize the data in a clear method for presentation.

13 * Definition: Ex post facto means "from after the fact" (Gay, 1976). In simple terms, in ex post facto research, the researcher investigates a problem by studying the variables in retrospect. It is research in which the dependent variable is immediately observable and now your main concern is to find out the antecedents that gave rise to this consequence.

14 * Definition: Kerlinger (1973) defines ex post facto as "systematic empirical inquiry in which the scientist does not have direct control of independent variables because their manifestations have already occurred or because they are inherently not manipulable. Inferences about relations among variables are made, without direct, intervention from concomitant variation of independent and dependent variables."

15 * Definition: Gay (1976) says that it is that research in which the researcher attempts to determine the cause, or reason, for existing differences in the behavior or status of groups of individuals. In a sense, the researcher observes that groups are different on some variable and then he attempts to identify the major factor or factors which have caused this difference.

16 * Definition: - In other words, Causal comparative study is a form of study that tries to identify and determine the cause and effect of relationship between two or more groups. - Causal comparative study is a study in which the researcher attempts to determine the cause, or reason, for pre-existing differences in groups of individuals.

17 * Differences between Dependent and Independent Variable:
- When it comes to experiments and data analysis, there are two main types of variables: dependent variables and independent variables.  It’s easy to get these mixed up, but the difference between dependent and independent variables is simple.  Here is a quick and easy definition of each one, along with some examples.

18 * Differences between Dependent and Independent Variable:
Dependent Variable:  This is the output variable you are really interested in monitoring to see if it was affected or not.  It can also be called the “measured variable,” the “responding variable,” the “explained variable,” etc.  I think it is easy to remember this one because it is dependent on the other variables.

19 Example 1: Golf Balls Suppose you want to test golf ball flight distances, so you set up a simple experiment in which various golf balls are placed into a mechanical chute and fired into the air. The variable you really care about, the “output” or dependent variable is golf ball distance. Independent variables are the variables you are going to test to see how they affect distance.  In this case, they are going to be things like air temperature, golf ball brand, and color of the golf ball. In the end, if you do a fancy regression analysis on all your data, you are going to end up with a formula that looks something like this: golf ball distance = 50 feet + air temperature factor + golf ball brand factor + golf ball color factor.  See how all the independent variables (air temp, brand, color) have an effect on the dependent variable (distance)?

20 * Differences between Dependent and Independent Variable:
Independent Variables: These are the individual variables that you believe may have an effect on the dependent variable.  They are sometimes called “explanatory variables,” “manipulated variables,” or “controlled variables.”

21 Example 2: Ice Cubes Here’s another simple example:  Imagine that you have a bunch of ice cubes and you want to test how long it takes them to melt in various situations.  You have an experiment with 1,000 equally shaped ice cubes.  Some of them are made of frozen cranberry juice and some of them are frozen lemonade.  You are going to set some of them on a metal sheet and others are going to be placed on a wooden plank.  Air temperature, wind, and every other condition you can think of will remain constant. So, in this case, your dependent variable is ice cube melting time.  Your two independent variables are: juice type (cranberry or lemonade) and melting surface (metal or wood).  

22 * Differences and similarities between causal comparative and correlational studies:
Causal comparative study looks at differences between groups while correlational study looks for relationships of variables within a single group. Causal comparative and correlational studies are similar in that both used to examine relationships among variables. Causal comparative includes categorical independent and or dependent variable but correlational study only includes quantitative variables.

23 * Differences and similarities between causal comparative and correlational studies:
Causal comparative research provides better evidence of cause and effect relationships than correlational research. Like correlational research, causal comparative research is sometimes treated as a type of descriptive research since it too describes conditions that already exist.

24 * Differences and similarities between causal comparative and correlational studies:
Causal comparative research attempts to establish cause-effect relationships while correlational research attempts to determine whether, and to what degree, a relationship exists between two or more quantifiable variables. Causal comparative and correlational studies are non-experimental methods.

25 * Types of causal comparative research (Ex Post Facto):
Retrospective causal comparative and prospective causal comparative research. Retrospective causal comparative research requires that researcher begins investigating a particular question when the effects have already occurred and the research attempts to determine whether one variable may have influenced another variable. Prospective causal comparative research occurs when a researcher initiates a study beginning with the causes and is determined to investigate the effects of a condition.

26 * Application of Ex Post Facto Research:
Let us think of correlational studies. Some studies identify dependent and independent variables. Some researchers who employ the correlational approach are merely interested in the relational aspect of two variables without necessarily assuming that one is a function of the other; e.g. relationship between teacher behavior and pupil behavior or between work attitude and job satisfaction. This type of correlational studies does not attempt to identify cause-effect relationships.

27 * Application of Ex Post Facto Research:
- Therefore, where hypotheses are stated in cause-effect relationship and where variables being correlated are ex post facto, that is, their manifestations have already occurred. The research is actually ex post facto. - Correlational and causal-comparative or ex post facto researches are confused because of the lack of manipulation common to both. There are definite differences, however. Ex post facto studies attempt to identify cause-effect relationships, correlational studies do not.

28 * Limitations: - There are three major weaknesses of ex post facto research. These are: First, the inability of the researcher to manipulate the independent variables purposively; and second, the researcher's lack of power to assign subjects randomly to the group levels of the variables under study. Put simply, ex post facto research lacks control which actually is the best for a third major weakness that of the risk of improper interpretation.

29 * Limitations: - Wiersma (1975) points out that "the interpretation of the results of an ex post facto study should be supported by a thorough knowledge of the independent variables in the context of the dependent variables. Such knowledge will tend to guard against profuse and improper interpretations. Any conjectures should be categorized as just that. The researcher should recognize the empirical results of the study and should limit the discussion on these results in preference to pursuing conjectures for which there is little or no basis." - This means that a third variable might have caused both the identified cause and the effect. Thus in an ex post facto study, the cause-effect relationships are at beat tenuous and tentative.

30 * The Value of Ex Post Facto Research:
Many of the variables in social, psychological and educational setting are certainly important areas of study but which can impossibly be investigated through true experimentation. Although direct control is impossible, controlled inquiry can be done in ex post facto and extraneous variable control is certainly possible. These make the research sensible and valid. For this reason, findings, interpretations and conclusions made in ex post facto research, when done properly, will always be valuable to the scientist and to the layman.

31 * References: Dependent vs. Independent Variables: What’s the Difference?. (2012). Retrieved from Johnson, B. & Christensen, L. Educational Research: Quantitative, Qualitative, and Mixed Approaches. California, SAG Publications, Inc. Klazema, April. (2014). Types of Quantitative Research for Students and Researchers. Retrieved from https://www.udemy.com/blog/types-of-quantitative-research/ Nalzaro, Ludi Mae. (2012). METHODS OF DATA COLLECTION. Retrieved from collection?related=2

32 * References: Sevilla, C. G., Ochave, J. A., Punsalan, T. G., Regala, B. P., & Uriarte, G. G. Research Method. Quezon, Rex Printing Company, INC. Stejskal, Stella-Maria. (2007). Quantitative and Qualitative Research Methods Are not and Should not Be Mutually Exclusive. Retrieved from Thomas, R. Murray. Blending Qualitative and Quantitative Research Methods in Theses and Dissertations. California, Corwin Press, Inc.


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