UNDERSTANDING THE LEVEL OF SIGNIFICANCE DURING DATA ANALYSIS

Most project works has the chapter four which is very important comprising of data presentation, data analysis and interpretation. For a researcher or project student to be able to interpret his/her project work effectively, he/.she must have a good knowledge of the level of significance and its application to a project work. All project topics are designed to test hypothesis consisting of a null and alternative hypothesis. Accepting a null or alternative hypothesis can only be made using the level of significance as a yardstick

What is level of significance?

The level of significance denoted by α is simply the level at which we either reject or accept the null hypothesis based on our t-test or probability value commonly known as p-value. During data analysis and interpretation, decisions cannot be made without the level of significance. For professional data analysis, the level of significance is placed at either 0.05 or 0.01. Simply put the level of significance of any experiment is the level at which the null hypothesis is either accepted or rejected based on the p-value.

Most students during their research or project work tend to ignore this which unfortunately tends to haunt them at the end of the day.

For most project work the level of significance of 0.05 is generally preferable, this is because of its 95 percent  confident limit of generalizations reached at the end of the analysis leaving the remaining 5 percent for error during analysis. 5 percent margin for error is generally believed to be on point as it gives enough room for error during the analysis of the chapter four of your project work.

Most research or project supervisor looks out for the level of significance used for a project work. This is because the level of significance goes a long way in telling your project supervisor if you made the right decisions in the analysis and interpretation of your project work.

The level of significance normally comes up in the chapter fur of a standard chapter four of any undergraduate research. It appears below the hypothesis of a study just above the decision rule of the study. Conclusions are made my comparing the p-value with the level of significance which is normally at 0.05 or 0.01 as said earlier.

Below is a professional appearance of the level of significance and how it can be used for decision making in most project works.

Test of hypothesis

H0: there is no significant relation between A and B  

H0: there is a significant relation between A and B   

Level of significance: 0.05

Decision rule: reject H0 if the p-value is less than the level of significance (0.05) but accept H0 if the p-value is greater than the level of significance (0.05)

The p-value is usually a value between 0 and 1 inclusive which is usually a value gotten after the data (whether primary or secondary) must have been analysed used a statistical tool.