Hypotheses in Machine Learning

Hypotheses are educated guesses about possible differences, relationships, or causes. Hypotheses are statements of expectation about some characteristics of a population. Etymologically, hypothesis are made up of two words, "hypo" (less than) and "thesis" (less certain than thesis). It is the available evidence, which the researcher seeks to prove through his study. 
The hypothesis is a formal affirmative statement predicting a single research outcome, a tentative explanation of the relationship between two or more variables

Simply stated, a hypothesis is an assumption or supposition to be proved or disproved. It is a guiding idea. a tentative explanation or a statement os probabilities which serves to initiate and guide observation, search for relevant data, or considerations to predict results of consequences. Hypotheses are measurable and testable. They are of various types based on the manner in which they are tested.

Hypotheses are of two types-

1. Directional hypothesis 
2. Non-directional hypothesis

1. Directional hypothesis- This hypothesis states a relationship between the variables being studied or differences between experimental treatments that the researcher expects to emerge. The directional hypothesis can also be tested as a statistical hypothesis. However, the statistical hypothesis can also be tested as a statistical hypothesis. However, a statistical hypothesis can be stated in the directional form only when there is a complete certainty that the findings will show a relationship or difference in the expected direction. This is because the directional hypothesis can be tested using the one-tailed test of significance.
2.  Non-directional Hypothesis-If a given hypothesis does not indicate the nature of the relationship between two variables (i.e. whether positive of negative) or it does not indicate the nature/direction of differences between two or more groups on a variable (i.e. which group will perform better) then it is known as the non-directional hypothesis.

In the present study, the null hypothesis is formulated in order to study the information literacy skills of student teachers and the effect of intervention programs.

A null hypothesis is non-directional in nature, as it does not specify the direction of differences between relationships among variables. The null hypothesis is related to a statistical method of interpreting conclusions about population characteristics that are inferred from the variable relationships observed in the sample.

Hypotheses are formed to study the existing conditions. Thus, the null hypothesis is individually tested statistically in order to decide whether it should be accepted of rejected.