What is a Law? Scientific laws are similar to scientific theories in that they are principles that can be used to predict the behavior of the natural world. Both scientific laws and scientific theories are typically well-supported by observations and/or experimental evidence.

A hypothesis is a limited explanation of a phenomenon; a scientific theory is an in-depth explanation of the observed phenomenon. A law is a statement about an observed phenomenon or a unifying concept, according to Kennesaw State University.

Hypothesis and prediction are both a type of guess. That’s why many people get the two confused. However, the hypothesis is an educated, testable guess in science. A prediction uses observable phenomena to make a future projection.

However, there are some important things to consider when building a compelling hypothesis.

1. State the problem that you are trying to solve. Make sure that the hypothesis clearly defines the topic and the focus of the experiment.
2. Try to write the hypothesis as an if-then statement.
3. Define the variables.

An hypothesis is a specific statement of prediction. It describes in concrete (rather than theoretical) terms what you expect will happen in your study. Not all studies have hypotheses. Sometimes a study is designed to be exploratory (see inductive research).

A hypothesis is used in an experiment to define the relationship between two variables. The purpose of a hypothesis is to find the answer to a question. A formalized hypothesis will force us to think about what results we should look for in an experiment. The first variable is called the independent variable.

There are four evaluation criteria that a hypothesis must meet. First, it must state an expected relationship between variables. Second, it must be testable and falsifiable; researchers must be able to test whether a hypothesis is truth or false. Third, it should be consistent with the existing body of knowledge.

Importance of Hypothesis: It helps to provide link to the underlying theory and specific research question. It helps in data analysis and measure the validity and reliability of the research. It provides a basis or evidence to prove the validity of the research.

Often called a research question, a hypothesis is basically an idea that must be put to the test. Research questions should lead to clear, testable predictions. The more specific these predictions are, the easier it is to reduce the number of ways in which the results could be explained.

Fourthly, the hypothesis provides guidance by way of providing the direction, pointing to enquiry, enabling to select pertinent facts and helping to draw specific conclusions. It saves the researcher from the botheration of ‘trial and error’ which causes loss of money, energy and time.

According to the San Jose State University Statistics Department, hypothesis testing is one of the most important concepts in statistics because it is how you decide if something really happened, or if certain treatments have positive effects, or if groups differ from each other or if one variable predicts another.

test statistic

Hypothesis testing incorporates estimates of the sampling error to help you make the correct decision. For example, if you are studying the proportion of defects produced by two manufacturing methods, any difference you observe between the two sample proportions might be sample error rather than a true difference.

• Step 1: Specify the Null Hypothesis.
• Step 2: Specify the Alternative Hypothesis.
• Step 3: Set the Significance Level (a)
• Step 4: Calculate the Test Statistic and Corresponding P-Value.
• Step 5: Drawing a Conclusion.