A Hypothesis is an assumption or a statement which may be true or not true. The testing of the hypothesis takes place on the basis of the information that has been obtained from a sample. The use of Hypothesis testing is widely prevalent in the business industry as it assists in decision making. There is some important terminology in hypothesis that needs to be known so as to completely understand the concept.

Null Hypothesis: Those hypotheses that have been proposed with the intention of receiving a rejection are called the null hypothesis. It means that the researcher hypotheses the opposite of what is desired to be proved.

Alternative Hypothesis:  When the null hypothesis is rejected, the alternate hypothesis has to be accepted. The rejection of the null hypothesis means that there is a relationship between the variables. The alternate hypotheses cover a large range of values.

One tailed test:  Any test can be either one tailed or two tailed. A test is put in the category of a one tailed test when the null hypothesis gets rejected and the value of the test statistic comes into a specified tail of the distribution. The test is called a two tailed test when the null hypothesis gets rejected and the statistics of the test fall in either of the two tails of the sampling distribution. There  are often the chances of errors in hypothesis testing which need to be corrected at the right time so as to avoid any major flaws in the analysis and interpretation of the data. There are usually Type I and Type II errors

The knowledge of different types of variable and also the way they can be measured plays a significant role in research. Variables become important in resulting into specificity and clarity to the conceptualisation of a research problem, leading to establishing hypotheses, leading to construction of research instrument. Variables affect the way data could be analysed, statistical tools that could be applied to the data, interpretations that could be made, the way data could be presented and finally what conclusions could be drawn. The way a variable could be measured at the data collection stage determines to a larger extent whether a study would be majorly ‘qualitative’ or ‘quantitative’ in nature.

For a beginner it becomes important to understand the various ways by which a variable could be measured and implications arising from it for the study. There are three perspectives that mutually not exclusive through which a variable could be classified:

• Causal relationship
  
• Design of the study
  
• Unit of measurement
  

Any concept that could be measured on scales like nominal, ordinal, interval and ratio is called a variable. Measurement scales leads to subjective responses, and also responses that could be measured with great precision for purposes of categorisation. The choice that a researcher could have on measuring a variable on a scale used for measurement depends upon the objective of the study and also the way the researchers want to convey their findings to the readers.

It is juvenile to even question what role medical research plays in society – rather if one were to see its breadth of usefulness, one would ask – is there anything at all that medical research cannot do? 

From research and development to newer scientific explorations – the outcome of medical research has far reaching effects on society. Whether it is exploration of a new gene, an evolving disease or virus, a breakthrough in treatment or therapy for fatal illnesses or evolution of advanced medical instruments – these assessments into the unknown alleys of medicine, environment and the human body is producing tremendous results for the betterment of society.

While most endeavours in medical science have been applauded, a number of methods in testing and research have raised pertinent doubts as well. Funding for example, for long-drawn research initiatives - whether they are from the government or through charitable donations - have often been questioned, more specifically due to the pressing question about the outcome or effect of the research. 

The problem with medical research is that there is no formula to evaluate impact – success is gauged through trial and error, and which is usually time-consuming. For governments and society at large the success of a research is however exclusively based on its impact on mortality and morbidity. For instance, some recent forays into study of cardiovascular-related medical interventions show the time gap between original, key research and tangible results on health was at least 17 years.

Despite these hiccups, the exceptional value that medical research has had on society cannot be doubted. Discoveries made in the domain of medicine have made lives simpler, and it has cleared the complex web of several unknown diseases. From the discovery of x-ray machines, to in-vitro fertilization and further into gene therapies and technological aids in medicine – the ever new and ever unknown frontiers of medicine are yet to be explored. 

Moral and humanitarian questions have however often been raised from several quarters, including governments and humanitarian agencies, on various forms of research – vis-à-vis use of animals for testing; gauging the efficacy of new and yet-unpatented drugs on the underprivileged in underdeveloped countries and the complex issue of patents for traditional and new discoveries. 

Apart from the social, cultural and scientific impact of medical research, it has a huge bearing on economy as well. In the research chain are involved several key players, including governments, firms and the research organisation themselves. While the goal of any innovation initiative should be on health, medical learning and additional benefits to society – often these are guided by purely profit and business motives; and that’s where medical research begins to tread a rather fragile ground.    

Well before settling down for undertaking a research work, it is very important to decide upon the methodology to be used for the same. Today, most of the scholars use the qualitative method of conducting a research. As per this method, the scholars collect only a limited amount of information about a large number of cases pertaining to the research topic.

One of the best strategies to be followed while using the qualitative research method is using a questionnaire survey. As per this questionnaire survey, you can ask a series of already-framed questions related to the subject on which you are conducting your research. You can choose to ask the questions as per two methods. As per the first method, the questions can be pre-coded i.e. your respondent can choose among a range of responses for a particular question and as per the second method i.e. open-ended, you can allow your responder to give an answer in his/her own words and this answer can further be coded or analyzed.

Another means of using the qualitative research method is utilizing the sampling techniques in order to get a representative sample, such as using a random sample or a quota sample. Once you are done with your survey, the data collected from each question on the survey can be combined to provide numerical data for that question. This data can then be analyzed through various quantitative methods such as comparing the percentages of answers to different questions based on the unique traits of the respondents, obtaining an average or median for rating or ranking data or doing a correlation or regression analysis. Nowadays, research scholars also use the e-mail survey method as per which they send a questionnaire to the people and ask them to answer the same. This helps these scholars in gathering a good amount of data for research purposes. Qualitative research method is considered to be the best method for collecting large chunks of data and presenting the same in a compact and easy-to-understand manner.