Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Hypothesis in Research

hypothesis and type of hypothesis is explained with appropriate examples
Hypotheses and type of hypotheses are explained with appropriate examples
Research hypothesis, null hypothesis, directional hypothesis, non-directional hypothesis, simple hypothesis, complex hypothesis etc

  • Login to see the comments

Hypothesis in Research

  1. 1. Hypothesis in Research Muthuvenkatachalam S., D.Pharm, M.Sc (AIIMS), PhD Scholar (RGUHS) Associate Professor, PCNMS, Haldwani
  2. 2. Introduction • A hypothesis is a formal tentative statement of the expected relationship between two or more variables under study. • A clearly stated hypothesis includes the variables to be manipulated or measured, identifies the population to be examined, and indicates the proposed outcome of the study
  3. 3. DEFINITION • Hypothesis is a tentative predication or explanation of the relationship between two variables. • ‘It implies there is a systematic relationship between two variables.’
  4. 4. IMPORTANCES OF HYPOTHESIS • Enables the researcher to investigate objectively • Provides objectivity to research activity • Provides direction to conduct research • Provides clear and specific goals to the researchers • Links theories and practice • Bridge between theories and reality
  5. 5. IMPORTANCES OF HYPOTHESIS • Suggests which type of research is most likely to appropriate • Guides the researcher towards the direction in which research should proceeds • Stimulates the thinking process of the researchers • Serves as a framework for drawing conclusions of a research • Without hypothesis research would be like aimless wandering
  6. 6. Characteristics of good hypothesis A good hypothesis is • based on sound reasoning. • provides explanation for the predicted outcome. • clearly states the relationship between the defined variables. • Defines the variables in easy to measure terms. • Testable in a reasonable amount of time.
  7. 7. Sources • Theoritical or conceptual frameworks • Previous research • Real life experiences • Academic literatures
  8. 8. TYPES • Simple Vs. Complex • Associative Vs. Causal • Directional Vs. Non – Directional • Null Vs. Research
  9. 9. SIMPLE Vs. COMPLEX • The statement which reflects the relationship between two variables is known as simple hypothesis. – E.g. The lower the level of haemoglobin the higher is the risk of infection among postpartum women. • The statement which reflects the relationship beyween more than two variables is known as complex hypothesis. – E.g. Satisfaction is higher among patients who are older and dwelling in rural areas than those who are younger and dwelling in urban areas.
  10. 10. ASSOCIATIVE Vs. CAUSAL • It reflects a relationship between variables that occurs or exists in natural settings without manipulation. – E.g. The lower the blood sugar level, the lesser is the risk of infection among diabetic patients. • It predicts the cause and effect relationship between two or more dependent and independent variables. – E.g. Prevalence of pin site infection is lower in patients who receive pin site care with hydrogen peroxide as compared to patients who receive the pin site care with betadine solution.
  11. 11. DIRECTIONAL Vs. Non - DIRECTIONAL • It specifies not only the existence, but also the expected direction of the relationship between variables. – E.g. There is a positive relationship between years of nursing experience and job satisfaction. • It just predicts the existence of relationship between the variables. – E.g. There is a relationship between year of nursing experiences and job satisfaction among nurses.
  12. 12. NULL AND RESEARCH • Null hypothesis is also known as statistical hypothesis and is used for statistical testing and interpretations. • It states the existence of no relationship between the variables. • Research hypothesis states the existence of relationship between two or more variables.

×