Business Research

Hypothesis:

To statistically evaluate questions, we need to put forward a hypothesis, which is an unproven testable proposition or supposition that tentatively explains certain facts or phenomena. It is a statement of assumptions we have about the nature of populations or relationships. So, Hypothesis is an educated guess based on the material that one has read.

Hypothesis testing involves the careful construction of two statements: the null hypothesis and the alternative hypothesis. To statistically evaluate the truthfulness of a question, one has to develop a null hypothesis (or statistical hypothesis), which will be used to test the proposition or supposition. The null hypothesis reflects that there will be no observed effect for our experiment. The null hypothesis is denoted by H0. The null hypothesis always states that the population parameter is equal to the claimed value. All null hypotheses include an equal sign in them.

The hypothesis that we seek to test is set up so that it will not be rejected (nullified) purely as a result of random error and is usually expressed in the negative: For example, there is no difference between a and b, or a and b are the same (a = b). Rejecting this statement means that there is some difference between a and b— that is, they are not equal. In addition to a null hypothesis, we also develop an alternate hypothesis, which is the opposite of the null hypothesis. The alternative or experimental hypothesis reflects that there will be an observed effect for our experiment. In a mathematical formulation of the alternative hypothesis there will typically be an inequality, or not equal to symbol. This hypothesis is denoted by H1. Thus, if we reject the null hypothesis, we accept the alternative hypothesis.

To overcome this and to decide whether we have enough evidence to reject the null hypothesis is by considering what is called the P-value. This is a probability and its lies between 0 and 1. An event cannot occur if P=0...