Basic statistics are an essential part of any organization. In fact, a successful organization couldn’t possibly go through a week without the use of basic statistics. The analysis of different situations by using statistical tests within an organization can be a useful tool in planning the future for the organization. The statistical data or information that is collected for analysis can assist an organization, so that it will remain successful in the future Analyzing Descriptive Statistics Data analysis can be split up into two different phases.
Both of these phases are critical to the final analysis or the conclusion that will be determined after the tests. The first phase in the analysis would be the preliminary descriptive phase. In this initial stage the organization will study the data or information to become more familiar with it in order to come to a conclusion. During the preliminary phase the data or information is applied and a formal inferential analysis is used.
This will assist in making the determination as to whether any patterns that occurred during the descriptive analysis could have happened just by chance (Blackwell Handbook of Research Methods in Clinical Psychology, 2003). The key focus during the preliminary descriptive analysis should be to understand the meaning of the data or information. This is essential to the organization’s conclusion of the analysis. During this phase graphs, charts, or plots are made in order to determine the means, modes, medians, or percentiles for the organization (Blackwell Handbook of Research Methods in Clinical Psychology, 2003).
The investigator conducting these tests for the organization should pay close attention to any unexpected or important patterns that may appear. Analyzing Inferential Statistics Once the patterns have been discovered, the analysis of the inferential statistics can be determined by using a variety of different tests. For example, a correlation analysis can be done; another example would be t-tests. So how does an organization analyze the information or data with inferential statistics? By using these two different tests, a conclusion of the information or data can be established.
Correlation Analysis A correlation analysis is simply to measure the relationship between two or more variables. According to Statsoft (2010), “Correlation coefficients can range from -1. 00 to +1. 00. The value of -1. 00 represents a perfect negative correlation while a value of +1. 00 represents a perfect positive correlation. A value of 0. 00 represents a lack of correlation” (Correlations, para. 1-19). In a correlation analysis the goal is to determine whether or not the two variables have a “true” relationship.
If a relation of the two variables show a high correlation, it is highly possible that this result is due to how the groups were arranged while testing. When a high correlation is shown the two groups can be run separately in each subset to get a different observation or result. According to Statsoft (2010), the significance of a correlation is; “The significance level calculated for each correlation is a primary source of information about the reliability of the correlation. As explained before the significance of a correlation coefficient of a particular magnitude will change depending on the size of the sample from which it was computed. (Correlations, para. 1-19).
T-Test Analysis The t-test analysis is used to determine or evaluate the variations or differences in the means between two groups. This is the most common test to make this determination or evaluation. According to Statsoft (2010), an example would be, “the t-test can be used to test for a difference in test scores between a group of patients who were given a drug and a control group who received a placebo” (Correlations, para. 1-19). Unlike the correlation analysis, the t-test can be evaluated on either large or small groups to make the analysis.
The purpose of the t-test is in the case of an error on other tests, the t-test is able to identify the error and eliminate the error in order to obtain a more accurate evaluation. In conclusion, it is critical to the outcome of the statistical tests that are being administered by the organization, to complete the preliminary descriptive phase. This will ensure that the individual doing the investigation has an overall knowledge of the data or information that is being analyzed. Furthermore, this will assist in the second and final phase which is to complete the inferential statistics analysis.