Hypothesis Testing in Research
Hypothesis testing in research can be referred to as the act of testing an assumption related to a population. Researchers test this assumed truth by examining data collected from members within that population and determining whether or not there is enough evidence in favor for it being true – meaning, if the results show significant proof that supports what was originally hypothesized then it becomes accepted as fact; otherwise, any assumptions are dismissed until more information comes along to support them.
Hypothesis testing is basically a formal process that includes the investigation of ideas about the real world by utilizing statistics. Testing of a hypothesis is mainly done by scientists for examining their predictions known as a hypothesis that originates from theories.
How to Test a hypothesis in research?
The 4 steps of the testing hypothesis in research are:
Step 1: Defining the null and alternative hypotheses
Before testing the hypothesis you need to create a hypothesis (it means that develop predictions on which you want to perform an investigation. It is very much important for you to write null (H0) and the alternative hypothesis (H1) so that they could be tested using mathematical formulas.
An alternative hypothesis is considered to be an initial hypothesis that helps you in predictions of the relationship between variables.
For example: If you intend to perform for the investigation to test whether there is a relationship between height and gender. On the basis of your knowledge about human physiology you can design a hypothesis that men are taller than women. You for testing the hypothesis need to restate it in the following manner such as:
H0, Men on average are taller than women.
H1: Men are on average are taller than women.
Step 2: Information gathering for hypothesis testing
You for making statistical hypothesis testing research to be valid, it is very crucial for you to execute the sapling and collection of information in a manner that is formulated to test the hypothesis. If the information is not representative, then you cannot make statistical inferences about the population in which you are interested.
Example: If you intend to test an average difference between the height of girls and boys, then you should select such a sample which consists of an equal proportion of girls and boys.
While making a selection of samples you should cover all socio-economic classes. At the time of selecting a sample you should consider other variables that might influence average height.
Step 3: Execution of statistical test
There are a number of statistical tests available which you can utilize for testing hypotheses. The entire statistical tests are designed for making a comparison between groups of variance. If there is a large difference between groups then the value will represent that variation. There are only a few cases when the difference between groups takes place by chance.
If in case there is great variance in a group and lower between different group variance, then the statistical test will represent a high P-value. It means that any difference you measure between groups is due to chance.
At the time of making the selection of statistical tests, you need to consider the type of information you intend to gather. On the basis of the information which you have gathered, you can perform a T-test in order to find whether the height of boys is taller than girls or not. T-Test enables you to get:
- Assume the difference between the height of boys and girls.
- It is a P-value that will help you in demonstrating the way which helps in demonstrating the way to test the hypothesis.
- A t-Test is deciding whether the null hypothesis is supported or refused
On the basis of outcomes of statistical tests, you need to determine whether the null hypothesis which you design will be accepted or rejected. There are a few circumstances where you can utilize the p-value which you have generated by performing the statistical test for guiding your decision. In some situations, the chances of rejecting the null hypothesis would be 0.05. In simple words, if the null hypothesis is true, it means that there are less than 5 percent of the chances of seeing the research outcomes.
For example: In an investigation performed for analyzing the difference between the height of boys and girls. The outcome of research findings reveals that there is an average difference between the height of boys and girls.
P-value which has been generated through statistical test is 0.002 which is below maximum which is 0.05. If your hypothesis s less than 0.05 then you can make a decision related to the rejection of the hypothesis.
Step 4: Presenting the results and facilitating discussion
You need to present the outcomes of hypothesis testing in the outcomes and discussion sections of the research paper. In the result chapter of the research paper, you should provide a detailed summary of information.
You should summarise the outcomes of the statistical test. In the discussion chapter, you should facilitate debate on whether the primary hypothesis should be accepted or rejected.
Example of stating outcome in statistics assignment: By making the comparison been the average height of boys and girls. It has been found from the investigation that the average difference between the height of boys and girls is 14.3 cm and the p-value is 0.002.
Therefore, you can refuse the null hypothesis that is boys are not as tall as compared to girls. It can be concluded by analyzing the outcome of an investigation that there is a little difference between the height of boys and girls.
At the time of presenting the research outcomes UN research paper, you need to review your alternative hypothesis. After that, you need to write that whether the outcome of the test is consistent or inconsistent in relation to the alternative hypothesis.
Example: It has been concluded from an assignment that the difference between the mean height of both girls and boys is 14.3 cm and the p-value is 0.002.
Maintaining the consistency in hypothesis there is variation in the height of girls and boys. Such variation is considered to be superficial which means that these difference have some meaning.
It has been concluded from the above that hypothesis testing helps you in testing your assumptions. Another thing that has been summarised from the above article is that by can utilize hypothesis testing for analyzing the relationship between different variables.