Tiêu đề 13. NULL HYPOTHESIS, LEVEL OF SIGNIFICANCE.pdf ✅

PHARMD GURU Page 1 INTRODUCTION TO RESEARCH HYPOTHESIS:  The second important step in the formulation of a research problem is the construction of hypothesis. The hypothesis is a tentative solution of a problem. It is a specific, testable prediction about research study. It is very essential to a scientist to understand the meaning and nature of hypothesis. Hypothesis need to be clear, precise and capable of being tested. Hypothesis is a tentative statement about the solution of the problem.  The term hypothesis has been defined in several ways. A hypothesis is a provisional formulation or possible solution or tentative explanation or suggested answer to the problem being faced by the researcher.  Hypothesis is an important part of scientific research. The importance of hypothesis is generally recognised more in the studies which aim to make predictions about some outcome.  In experimental research, the scientists are interested in making predictions about the outcome of the experiment and hence, the role of hypothesis is most important. In the historical or descriptive research, the researcher is investigating the history of nation or a village and thus may not have a basis for making a prediction of results. Therefore, a hypothesis may not be required in such fact-finding studies.  If a researcher is tracing the history of an university or making a study about the results of a coming Loksabha elections, the facts or data he gathers will prove useful only if he is able to draw generalizations from them. Hypothesis is recommended for all major studies to explain observed facts, conditions or behaviour and to serve as a guide in the research studies.  Working hypothesis or a tentative hypothesis is described as the best guess or statement derivable from known or available evidence. The amount of evidence and quality, of it, determine other forms of hypothesis. NULL HYPOTHESIS, LEVEL OF SIGNIFICANCE

PHARMD GURU Page 3 Statistical hypotheses are tested using a four-step process:  The first step is for the analyst to state the two hypotheses so that only one can be right.  The next step is to formulate an analysis plan, which outlines how the data will be evaluated.  The third step is to carry out the plan and physically analyze the sample data.  The fourth step is to analyze the results and either reject the null hypothesis, or claim that the observed differences are explainable by chance alone. The principle of the null hypothesis is collecting the data and determining the chances of the collected data in the study of a random sample, proving that the null hypothesis is true. In situations or studies where the collected data doesn't complete the expectation of the null hypothesis, it is concluded that the data doesn't provide sufficient or reliable pieces of evidence to support the null hypothesis and thus, it is rejected.
PHARMD GURU Page 4 ALTERNATIVE HYPOTHESIS: Alternative hypothesis defines there is a statistically important relationship between two variables. The alternative or experimental hypothesis reflects that there will be an observed effect for our experiment. It is contradictory to the null hypothesis and denoted by Ha or H1. In many cases, the alternate hypothesis will just be the opposite of the null hypothesis. For example, the null hypothesis might be "There was no change in the water level this spring," and the alternative hypothesis would be "There was a change in the water level this spring". The alternative hypothesis is the hypothesis that is to be proved that indicates that the results of a study are significant and that the sample observation is not results just from chance but from some non-random cause. It is a hypothesis that the researcher tries to prove. Basically, there are three types of the alternative hypothesis. a) Left-Tailed: Here, it is expected that the sample proportion (μ1 ) is less than a specified value which is denoted by μ2 such that: H1 : μ1 < μ2 b) Right-Tailed: It represents that the sample proportion (π) is greater than some value, denoted by π0 . H1 : μ1 > μ2 c) Two-Tailed: According to this hypothesis, the sample proportion (denoted by π) is not equal to a specific value which is represented by π0 . H1 : μ1 ≠ μ2 The null hypothesis for all the three alternative hypotheses would be H1 : μ1 = μ2 . If the null hypothesis is rejected, then we accept the alternative hypothesis. If the null hypothesis is not rejected, then we do not accept the alternative hypothesis. An alternative hypothesis provides the researchers with some specific restatements and clarifications of the research problem. The alternative hypothesis is important as they prove that a relationship exists between two variables selected and that the results of the study conducted are relevant and significant.