Understanding Hypotheses in Research Methodology
Unit VI: Theory
It is an assumption that establishes the existence of a relationship between two or more variables expressed as facts, events, or factors, and should be tested to be accepted as valid. Role of Hypotheses: Guide and direct an investigation. The assumptions should be deducted from the problem and aim to study and be consistent with the theoretical framework underpinning the work. Determine the type of study to follow and the design methodology that is planned for testing.
Characteristics of a Hypothesis: A hypothesis must refer to a real situation, with a universe and a well-defined context. The terms of the assumptions should be understandable, accurate, and as specific as possible. The assumptions should be formulated as statements and expressions of value or avoid trial. The relationship between variables suggested by a hypothesis must be clear and logical. The terms of the hypotheses should be observable and measurable in reality. The assumptions should be related to available techniques for testing. The assumptions made must be consistent with confirmed facts.
Types of Assumptions:
Research Hypothesis: Selection or attempts on the possible relationships between two or more variables. Hypotheses descriptive of data or value are forecasted. Not all descriptive research hypotheses are formulated, or these are more general statements.
Correlational Scenario: They specify the relationships between two or more variables. No handles dependent or independent variable; it is indifferent, if not for causality. The relationship of two variables in bivariate correlation, the relationship of more than two variables is multivariate correlation.
Scenarios for the Difference Between Groups: These are made in research designed to compare groups. This usually occurs when the hypothesis is derived from a theory or background studies, or the researcher is quite familiar with the problem being studied.
Hypotheses of Causal Relationships: This type of hypothesis states not only the relationships between two or more variables and how these relationships exist, but also proposes a “sense of understanding” of them. All relationships in these hypotheses establish cause-effect. To talk about hypotheses of causes, we refer to the independent variables and the dependent variables.
Types of Causal Hypotheses:
Bivariate Causal Hypotheses: In these, a relationship is established between an independent variable and a dependent variable.
Multivariate Causal Hypotheses: These establish a relationship between several independent variables and dependent variables, or dependent variables and several independent variables, or several independent variables and several dependent variables. When statistical causal hypotheses are analyzed, the influence of each independent variable (cause) on the dependent variable (effect) and the combined influence of all independent variables on the dependent or dependent variables is evaluated.
Null Hypotheses: Propositions that constitute the relationship between a set of variables; they serve only to refute or deny what the research hypothesis states.
Alternative Hypotheses: These are alternative possibilities to the research hypotheses and provide other explanations other than description or prediction of the research hypotheses.
Statistical Hypotheses: These are hypotheses transformed from the research hypotheses, null and alternative in statistical symbols. They are only made when one can study the data that will be collected and analyzed to prove or disprove the hypotheses, which are quantitative (numbers, percentages, averages).
Types of Statistical Hypotheses:
Statistical Hypotheses of Estimation: Correspond to those that, when speaking, the research hypotheses are called “descriptive hypotheses that predict a fact.” They serve to evaluate the assumption of a researcher regarding any value that shows a characteristic of individuals or objects in a population.
Statistical Hypotheses of Correlation: These translate into statistical terms a correlation between two or more variables.
Statistical Hypotheses of Differences: In these hypotheses, a comparison is made between two or more statistical values between groups.