Hypothesis Theory: Types, Characteristics, and Formulation
Hypothesis Theory
A hypothesis is an assumption that establishes a relationship between two or more variables, expressed as facts, events, or factors. It must be tested to be accepted as valid.
Role of a Hypothesis
- Guides and directs an investigation.
- Assumptions should be deduced from the problem and aims of the study.
- Must be consistent with the theoretical framework.
- Determines the type of study and design methodology.
Characteristics of a Hypothesis
- Must refer to a real situation with a defined context.
- Terms should be understandable, accurate, and specific.
- Formulated as statements, avoiding value judgments.
- Relationship between variables must be clear and logical.
- Terms should be observable and measurable.
- Related to available testing techniques.
- Consistent with confirmed facts.
Types of Hypotheses
Research Hypothesis
Explores possible relationships between two or more variables. Can be descriptive of data or forecast a value. Not all descriptive research hypotheses are formulated, or they may be general statements.
Correlational Scenario
Specifies relationships between two or more variables. Does not handle dependent or independent variables, focusing on causality. Bivariate correlation involves two variables; multivariate involves more than two.
Scenarios for the Difference Between Groups
Used in research designed to compare groups, often derived from theory, background studies, or when the researcher is familiar with the problem.
Hypothesis Establishing Relations of Causality
States the relationship between variables and how these relationships occur, proposing a “sense of understanding.” Independent variables are the alleged causes, and dependent variables are the effects.
Causal Hypothesis Types
- Bivariate Causal Hypothesis: Relationship between one independent and one dependent variable.
- Multivariate Causal Hypothesis: Connection between several independent variables and one dependent, one independent and several dependent, or multiple independent and dependent variables.
Statistical analysis evaluates the influence of each independent variable on the dependent and the combined influence of all independent variables.
Null Hypotheses
Propositions about the relationship between variables, used to refute or deny research hypotheses.
Alternative Scenarios
Alternative possibilities to research and null hypotheses, providing different descriptions or explanations. They are additional research hypotheses to the original.
Statistical Assumptions
Transformations of research, null, and alternative hypotheses into statistical symbols. Can be formulated when survey data is quantitative.
Types of Statistical Hypothesis
- Scenario Statistics Estimate: Evaluates a researcher’s assumption about the value of a property in a sample or population.
- Hypothesis Correlation Statistics: Translates a correlation between two or more variables statistically.
- Hypothesis Statistics Mean Difference: Compares a statistic between two or more groups.