The p-value can range from 0.000 to 1.000. This p-value is the probability that the result is due to chance. When calculating inferential statistics, the key statistic is the p statistic. This means that if we collect data from another sample, we are almost guaranteed to find the exact same result. Thus, we conclude that in general, government schools outperform private schools in mathematics. Therefore, the results from our sample - government schools have higher performance in mathematics than private schools - can also be applied to the entire population. On the other hand, after conducting inferential statistics, imagine that we find that the difference in mathematics performance is significant.
If we collected data from another sample of government and private schools, we will likely find the opposite of this small difference. This tiny difference in CRK/IRK performance was simply due to chance. This means that the difference between government and private schools in our sample was too small to conclude that an actual difference exists in the entire population of government and private schools. However, after conducting inferential statistics, we will find that the difference is not significant.
Returning to the WAEC illustration, this research found that there is a difference in CRK/IRK performance in our sample: government schools had a slightly higher mean score than private schools. On the other hand, if the difference between the groups is very small, then the findings are not significant and therefore were simply the result of chance. If the findings are indeed significant, then the conclusions can be applied, or generalized, to the entire population. Inferential statistics must be used to determine whether the difference between the two groups in the sample is large enough to be able to say that the findings are significant. How big must the difference be in order to conclude that there is a meaningful difference in the academic performance between government and private schools? This clearly does not represent a meaningful difference between the two types of schools. On the other hand, the difference between government and private schools on CRK/IRK is less than 1 point.
However, which differences are large enough to be significant? In mathematics, there is a clear difference in the mean scores. In all courses listed in Table 5, there is a difference in the average scores between the government and private schools.
HOW TO CONDUCT INFERENTIAL LIKERT DATA ANALYSIS WITH EXCEL GENERATOR
(Note that the data was created by a random number generator and thus does not reflect actual scores.) Course For example, imagine the following scores on WAEC from students who attended either a government or a private school. There will always be differences in scores between groups in a research study. The purpose of inferential statistics is to determine whether the findings from the sample can generalize - or be applied - to the entire population. Thus, the researcher wants to draw conclusions - or inferences - about the entire population based on the results from the sample. Instead, she wants to say that because her new way of teaching mathematics improved mathematical achievement for the children in her sample, it will also improve mathematical achievement for all children in Primary 1. However, the researcher does not want to limit her conclusions to only the few children who participated in the study. Instead, the researcher chooses a sample of the population to conduct a study. However, it would be impossible to test all children in Primary 1 because of time, resources, and other logistical factors. For example, to the purpose of a research study may be to determine if a new way of teaching mathematics improves mathematical achievement for all children in Primary 1. In educational research, it is never possible to sample all of the people that we want to draw a conclusion about. Inferential Statistics Conducting Educational Research
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