How do Hypotheses state an expected causal relationship between two(or more) variable?
How do Hypotheses state an expected causal relationship between two
(or more) variable?
VARIABLES AND HYPOTHESES
Research ideas come from curiosity; experience; need for deciding or acting; job; school; building on or contesting existing theory; available funding; etc. A preliminary research proposal, in one or two pages,
a. states the research question
b. states the purpose of the research
c. sketched the initial model
d. discusses the initial model
e. identifies pertinent background literature (bibliography)
A model shows how different elements are linked by relationships. The elements for a model can be drawn from personal experience, consulting with key players, published literature, asking experts, existing data sets, and pilot studies. Generally a model is fixed at the beginning of the research; it may be altered as a result of the data analysis.
A model is a visual representation of how something works; it both describes and explains some phenomenon.Elements of the model are variables. Variables are measurable characteristics or properties of people or things that can take on different values. In contrast, characteristics that do not vary are constants.
A hypothesis states a presumed relationship between two variables in a way that can be tested with empirical data. It may take the form of a cause-effect statement, or an "if x,...then y" statement.
The cause is called the independent variable; and the effect is called the dependent variable.
Relationships can be of several forms: linear, or non-linear. Linear relationships can be either direct (positive) or inverse (negative).
In a direct or positive relationship, the values of both variables increase together or decrease together. That is, if one increases in value, so does the other; if one decreases in value, so does the other.
In an inverse or negative relationship, the values of the variables change in opposite directions. That is, if the independent variable increases in value, the dependent variable decreases; if the independent variable decreases in value, the dependent variable increases.
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