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NULL AND ALTERNATIVE HYPOTHESIS.pptx

The document discusses null and alternative hypotheses. The null hypothesis states that there is no relationship or difference between two variables and is what researchers aim to disprove. It is represented by H0 and can be rejected but not accepted. The alternative hypothesis proposes an alternative theory to the null hypothesis by stating a relationship or difference does exist between variables. It is represented by H1 or Ha. If the null hypothesis is rejected based on a low p-value, the alternative hypothesis is supported, meaning the results are statistically significant. Examples of null and alternative hypotheses are provided.

Data & Analytics◦
NULL AND ALTERNATIVE HYPOTHESIS
NULL HYPOTHESIS-  The null hypothesis is a general statement that states that there is no relationship between two phenomenons under consideration or that there is no association between two groups.  A hypothesis, in general, is an assumption that is yet to be proved with sufficient pieces of evidence. A null hypothesis thus is the hypothesis a researcher is trying to disprove.  A null hypothesis is a hypothesis capable of being objectively verified, tested, and even rejected.  If a study is to compare method A with method B about their relationship, and if the study is preceded on the assumption that both methods are equally good, then this assumption is termed as the null hypothesis.  The null hypothesis should always be a specific hypothesis, i.e., it should not state about or approximately a certain value.  The symbol for the null hypothesis is H0, and it is read as H-null, H- zero, or H-naught.  The null hypothesis is usually associated with just ‘equals to’ sign as a null hypothesis can either be accepted or rejected.
PURPOSE OF NULL HYPOTHESIS-  The main purpose of a null hypothesis is to verify/ disprove the proposed statistical assumptions.  Some scientific null hypothesis help to advance a theory.  The null hypothesis is also used to verify the consistent results of multiple experiments. For e.g., the null hypothesis stating that there is no relation between some medication and age of the patients supports the general effectiveness conclusion, and allows recommendations.
ACCEPTANCE / REJECTION -  When the p-value of the data is less than the significant level of the test, the null hypothesis is rejected, indicating the test results are significant.  However, if the p-value is higher than the significant value, the null hypothesis is not rejected, and the results are considered not significant.  The level of significance is an important concept while hypothesis testing as it determines the percentage risk of rejecting the null hypothesis when H0 might happen to be true.  In other words, if we take the level of significance at 5%, it means that the researcher is willing to take as much as a 5 percent risk of rejecting the null hypothesis when it (H0) happens to be true.  The null hypothesis cannot be accepted because the lack of evidence only means that the relationship is not proven. It doesn’t prove that something doesn’t exist, but it just means that there are not enough shreds of evidence and the study might have missed it.
EXAMPLES-  The following are some examples of null hypothesis:  If the hypothesis is that “the consumption of a particular medicine reduces the chances of heart arrest”, the null hypothesis will be “the consumption of the medicine doesn’t reduce the chances of heart arrest.”  If the hypothesis is that, “If random test scores are collected from men and women, does the score of one group differ from the other?” a possible null hypothesis will be that the mean test score of men is the same as that of the women.  H0: µ1= µ2  H0= null hypothesis µ1= mean score of men µ2= mean score of women
ALTERNATIVE HYPOTHESIS  An alternative hypothesis is a statement that describes that there is a relationship between two selected variables in a study.  An alternative hypothesis is usually used to state that a new theory is preferable to the old one (null hypothesis).  This hypothesis can be simply termed as an alternative to the null hypothesis.  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.  If a study is to compare method A with method B about their relationship and we assume that the method A is superior or the method B is inferior, then such a statement is termed as an alternative hypothesis.  Alternative hypotheses should be clearly stated, considering the nature of the research problem.  The symbol of the alternative hypothesis is either H1 or Ha while using less than, greater than or not equal signs.
PURPOSE OF ALTERNATIVE HYPOTHESIS-  An alternative hypothesis provides the researchers with some specific restatements and clarifications of the research problem.  An alternative hypothesis provides a direction to the study, which then can be utilized by the researcher to obtain the desired results.  Since the alternative hypothesis is selected before conducting the study, it allows the test to prove that the study is supported by evidence, separating it from the researchers’ desires and values.  An alternative hypothesis provides a chance of discovering new theories that can disprove an existing one that might not be supported by evidence.  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.
EXAMPLES  The following are some examples of alternative hypothesis:  1. If a researcher is assuming that the bearing capacity of a bridge is more than 10 tons, then the hypothesis under this study will be:  Null hypothesis H0: µ= 10 tons Alternative hypothesis Ha: µ>10 tons  2. Under another study that is trying to test whether there is a significant difference between the effectiveness of medicine against heart arrest, the alternative hypothesis will be that there is a relationship between the medicine and chances of heart arrest.
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