Skip to main content
Sign In

Aims and Hypothesis

At the start of the study process, there are general questions, goals, and study aims that set the context for an idea. Often the questions seem clear but are not formulated in enough detail to perform analysis. Questions often range throughout research. Some examples are looking for results from groups with different profiles, assessing the effectiveness of a drug, or looking for a response pattern over time.

Supporting information is required to help move from the study aim to a hypothesis. A hypothesis is more detailed than a study aim. It is a testable, statistics-driven statement that will have evidence for or against, or no evidence at all.


  • What is known and unknown about Drug X?
  • What is known and unknown about Disease W?
  • What are all, if any, long term implications of any precipitating results?

Formulation of a Hypothesis

Null Hypothesis

  • Accepted statistical practice for formulating a hypothesis is to start with a scenario of status-quo
  • Often declares that the study will have no effect

Alternative Hypothesis

  • Is the compliment of the null hypothesis
  • Often declares that the study will have an effect
  • Characterizes how this effect will be manifested


  • Null: Drug X is no more effective for treating Disease W than Drug Y.
  • Alternative: Drug X is more effective for treating Disease W than Drug Y.

It is critical to establish the null and alternative hypotheses before the study begins so that the appropriate measurements and controls can be put in place to ensure that the study is as unbiased as possible. Determining these hypotheses after the fact is a bit like ‘leading the witness’.

The primary goal of the study is to accept or reject the null hypothesis. It is through the rejection of the null hypothesis that there is enough evidence to support the possibility that the alternative hypothesis may be true.

"There are two possible outcomes: if the result confirms the hypothesis then you've made a measurement. If the result is contrary to the hypothesis, then you've made a discovery." Enrico Fermi

Criteria for a Hypothesis

A good hypothesis should have the following characteristics:

Characteristic Examples

Be measureable: Define your independent and dependent variables, how you plan to measure them, and determine ways to examine the relationship between them.

Survival rates after treatment: 1,2,3 years

Decrease in systolic blood pressure of a minimum of 5 mm Hg after 6 months

References a well-defined population: Describe in detail the members of the population   or contrast various population groupings.

Males age 55+ with family history of heart disease

Pregnant women with elevated hormone levels

Ethnicity - Existing conditions, comorbidity

Proposes cause-effect or association between variables: If not true cause and effect, then make a statement about the relationship or association between variables of interest, including potential predictor variables thought to have an impact on study outcomes.



Genetic characteristics

Vital measurements (potentially at different times during the study)

History of smoking/tobacco use

Has a “biological” basis – or at least it’s plausible: Your hypothesis needs to be plausible and you need to have done your homework in the literature to propose it.

Examination of hereditary traits in an ethnic population

Levels of serum beta-carotene distinguished in groups receiving 4 different treatments

Is clear, focused, and in the form of a statement: Refer back to the discussion of the null and alternative hypotheses to make a clear distinction between the two.

Treatment of Stage IV pancreatic cancer with drug X will result in a reduction of tumor size in treated mice compared to mice that were not treated.

Can answer at least part of your research question!: Sometimes a study might not have a specific hypothesis but will have an objective, perhaps just to provide descriptive statistics or to be exploratory. The study might just provide direction for follow-on work.

Describe the characteristics of Veterans Affairs patients who participated in open heart surgery for the last 6 months at hospitals in Colorado.

Colorado Biostatistics Consortium

13001 17th Place | Mail Stop B119 | Room W3129, Building 500 | Aurora, CO 80045
303-724-4370 |

Biostatistics Consulting | Grant Collaboration | Department of Biostatistics and Informatics | BERD | BBSR | ColoradoSPH

© The Regents of the University of Colorado, a body corporate. All rights reserved.

Accredited by the Higher Learning Commission. All trademarks are registered property of the University. Used by permission only.