Hypothesis Assumptions
Question 1. Define Hypothesis
Answer:
- The word hypothesis (plural is hypotheses) is derived from the Greek word ‘hypothenar’ meaning ’to put under‘ or ’to suppose’ For a hypothesis to be put forward as a scientific hypothesis, the scientific method requires that one can test it.
Hypothesis Definition:
- According to Lundberg, “A hypothesis is a tentative generalization, the validity of which remains to be tested. In its most elementary stage, the hypothesis may be any hunch, guess, or imaginative idea, which becomes the basis for action or investigation.
- A hypothesis is a tentative assumption drawn from knowledge and theory which is used as a guide in the investigation of other facts and theories that are yet unknown.
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Question 2. Types of Hypothesis
Answer:
- According to Lundberg, “A hypothesis is a tentative generalization, the validity of which remains to be tested. In its most elementary stage, the hypothesis may be any hunch, guess, or imaginative idea, which becomes the basis for action or investigation.
Types Of Hypotheses
- Hypotheses are classified in several ways. With reference to their function.
Hypotheses are of two types:
- Descriptive hypotheses and
- Relational hypotheses.
Another approach is to classify them into:
- Working hypotheses,
- Null hypotheses and
- Statistical hypotheses.
- The third approach is to divide them on the basis of the level of abstraction.
Three broad levels may be distinguished:
- Simple Description
- Logical Derivation
- Abstraction.
Accordingly, there are three types of hypotheses:
- Common-Sense Hypotheses,
- Complex Hypotheses And
- Analytical hypotheses.
Descriptive hypotheses:
- These are propositions that describe the characteristics (such as size, and form of distribution) of a variable. The variable may be an object, person, organization, situation, or event.
Some examples are:
- “Patients who attend pre-operative education classes have less post-operative emotional stress than patients who do not.”
- “The rate of unemployment among Nursing graduates is lesser than that of medical graduates.”
- Relational hypotheses: These are propositions, which describe the relationship between two variables. The relationship suggested may be a positive or negative correlation or causal relationship.
Some examples are:
- “Families with higher incomes spend more for recreation.”
- “Upper-class people have fewer children than lower-class people.”
- “Labour productivity decreases as the working duration increases.”
Causal hypotheses:
- State that the existence of, or a change in, one variable causes or leads to an effect on another variable.
- The first variable is called the independent variable, and the latter is the dependent variable. When dealing with causal relationships between variables the researcher must consider the direction in which such relationships flow, i.e. which is cause and which is effect e.g., smoking causes lung cancer.
Working hypotheses:
- While planning the study of a problem, hypotheses the formed.
- Initially, they may not be very specific. In such cases, they are referred to as “Working Hypotheses” which are subject to modification as the investigation proceeds.
Null hypotheses:
These are hypothetical statements denying what is explicitly indicated in working hypotheses.
- They do not, nor were ever intended to exist in reality. They state that no difference exists between the parameter and the statistic being compared to it.
- For example, even though there is a relationship between a family’s income and expenditure on recreation
A null hypothesis may state:
- “There is no relationship between families’ income level and expenditure on recreation.”
- Null hypotheses are formulated for testing statistical significance, since, this form is a convenient approach to statistical analysis. As the test would nullify the null hypotheses, they are so-called.
Statistical hypotheses:
- These are statements about a statistical population. These are derived from a sample.
- These are quantitative in nature in that they are numerically measurable, e.g., “Group A is older than Group B.”
Common sense hypotheses:
- These represent common sense ideas. They state the existence of empirical uniformities perceived through day-to-day observations.
- Many empirical uniformities may be observed in business establishments, the social background of workers, and the behavior patterns of specific groups like students e.g., “shop assistants in small shops lack motivation.”
- “Soldiers from upper class are less adjusted in the army than lower class men”; “fresh students conform to the conventions set up by seniors.”
Complex hypotheses:
- These aim to test the existence of logically derived relationships between empirical uniformities.
- For example, in the early stage, Human ecology described empirical uniformities in the distribution of land values, industrial concentrations, types of business, and other phenomena.
- Further study and logical analysis of these and other related findings led to the formulation of complex hypotheses such as “The concentric growth circles characterize a city,”
- “Members of minority groups suffer from oppression psychosis,” etc.
- Such hypotheses are purposeful distortions of empirical exactness. Analytical Hypotheses: These are concerned with the relationship of analytic variables.
- These hypotheses occur at the highest level of abstraction. These specify the relationship between changes in one property and changes in another.
- For example, the study of human fertility might show empirical regularities by wealth, education, region, and religion.
- If these were raised to the level of ideal type formulation, one result might be the hypothesis: “There are two high-fertility population segments in India viz., low-income urban Muslims and low-income rural low-caste Hindus.”
- At a still higher level of abstraction, the effects of region, education, and religion or fertility might be held constant.
- This would allow a better measurement of the relationship between the variables of wealth and fertility.
Question 3. Importance of Hypothesis
Answer:
According to Lundberg, “A hypothesis is a tentative generalization, the validity of which remains to be tested.
In its most elementary stage, the hypothesis may be any hunch, guess, or imaginative idea, which becomes the basis for action or investigation.
It is A researcher’s eye,
- It focuses a research.
- It formulates clear and specific goals
- It links related facts
- It prevents blind research
- It works as a beacon light
- Hypotheses facilitate the extension of knowledge in an area.
- Hypotheses provide the researcher with rational statements,
- Hypotheses provide direction to the research.
- Hypotheses provide the basis for reporting the conclusions of the study.
- The hypothesis has a very important place in research although it occupies a very small place in the body of a thesis.
Question 4. Assumptions
Answer:
- Assumptions are things that are accepted as true, or at least plausible, by researchers and peers who will read your dissertation or thesis.
- In other words, any scholar reading your paper will assume that certain aspects of your study are true given your population, statistical test, research design, or other delimitations.
- An assumption is a belief that forms one of the bases for the research. This belief is not to be tested or supported with empirical data. Very often belief is not stated in a research proposal.
Definition:
- According to Charles: An assumption is a proposition that is taken for granted, as if it were true based upon presupposition without preponderance of the facts.
- According to Chris Jordan: An assumption is an accepted cause-and-effect relationship or estimate of the existence of a fact from the known existence of another fact (s).
- According to Frederick: An assumption is an ascertain about some characteristic of the future that underlies the current operations or plans of an organization.
Need of assumptions:
- This is important because both assumptions and limitations affect the inferences you can draw from your study.
- One of the more common assumptions made in survey research is the assumption of honesty and truthful responses.
- However, for certain sensitive questions, this assumption may be more difficult to accept, in which case it would be described as a limitation of the study
- For example, asking people to report they are criminal behavior in a survey may not be as reliable as asking people to report their eating habits.
Types of assumptions:
1. Explicit assumptions:
- Explicit assumptions are assumptions of which the intention is fully revealed and expressed without vagueness, implication, or ambiguity.
2. Implicit assumption:
- Implicit assumptions are assumptions that are not expressed and may go undetected. If implicit assumptions prove to be wrong, this can damage projects.
3. Primary assumption:
- Primary assumptions are assumptions about which the respondent identifies what they want, how dense the customer population is, what they need, and what the customer sees as the alternative to your project, The primary assumptions define the foundation of an organization.
4. Derivative assumptions:
- Derivative assumptions come from the primary assumptions. The numbers in a sales forecast are based on assumptions about customer demand, the number of clients; a salesperson can visit in a week, and the availability of the project.
Steps involved in assumption-based planning:
- Identify assumptions: Collect all assumptions implicit, explicit, and primary and derivatives, out of the plan.
- Determine criticality: Try to quantify the assumptions as much as possible in order to determine which assumptions have the greatest impact.
- Design tests: Design a test for every critical assumption.
- Schedule test: Every critical assumption needs to be tested, but not all assumptions can be tested in the present, so future assumptions tests are scheduled in a test schedule,
Some possible reasons to schedule a test in the future are a lack of information in the present or dependency on the test outcomes of other tests. - Test assumptions: When an assumption is tested this results in a test outcome, which proves the assumption right or wrong.
- Reassess venture plan: Based on the test outcomes and the test schedule one might decide to reassess the venture plan and update the plan with the new insights gathered into the assumption-based planning process.
- Plan retesting of assumption: The assumptions need to be re-tested regularly if not constantly. There should be a retest scheduled for every critical assumption.
- Create or update the assumption plan: The assumption plan holds all data gathered during the assumption planning process.
Question 5. Types of Error.
Answer:
In the context of testing the hypothesis, there are two types of errors. They are type-1 and type-2 errors.
- Type-1: We may reject H0 when HO is true and it is known as a type-1 error.
- Type-2: We may accept H0, when in fact HO is not true and it is known as a type-2 error.
- Types-1 error is also known as alpha error and type-ll error is also known as beta error.
Question 6. Characteristics of A Hypothesis
Answer:
Characteristics Of A Good Hypothesis:
An acceptable hypothesis should fulfill the conditions given below:
- Conceptual clarity:
- A hypothesis should be conceptually clear. It should consist of clearly defined and understandable concepts. Clarity is obtained by means of defining operationally the concepts in the hypothesis.
- Specificity:
- A hypothesis should be specific and explain the expected relations between variables and the conditions under which these relations will hold e.g., “when there is dissatisfaction and no care is taken, deprivation will engender violence.”
- Testability:
- A hypothesis should be testable and should not be a moral judgment. It should be possible to collect empirical evidence to test the hypothesis.
- Statements like “Bad partners produce bad children” are commonplace generalizations and cannot be tested, as they merely express sentiments and their concepts are vague.
- Availability of techniques:
- Hypotheses should be related to available techniques. Otherwise, they will not be researchable; therefore, the researcher must make sure that methods are available for testing his proposed hypotheses.
- Theoretical relevance:
- A hypothesis should be related to a body of theory. A science can be cumulative only by building on an existing body of facts and theory. It cannot develop if each study is an isolated investigation.
- When research is systematically based upon a body of existing theory, a genuine contribution to knowledge is more likely to result. Therefore, a hypothesis should possess theoretical relevance.
- Consistency:
- Hypotheses should be logically consistent. Two or more propositions logically derived from the same theory must not be mutually contradictory.
- Objectivity:
- Scientific hypotheses should be free from value – judgment. In principle, the researcher’s system of values has no place in the scientific method.
- However, as social phenomena are affected by the milieu in which they take place, the researcher must be aware of his values and state them explicitly.
- Simplicity:
- A hypothesis should be a simple one requiring fewer conditions or assumptions. But simple does not mean obvious. Simplicity demands insight. The more insight the researcher has into a problem, the simpler will be his hypothesis about it.
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