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Air Force Essay Example Paper

Words: 1334, Paragraphs: 14, Pages: 5

Paper type: Essay , Subject: Economics

Categories: Economics, Regression Analysis

This sample essay on Air Force Essay Example offers an extensive list of facts and arguments related to it. The essay’s introduction, body paragraphs, and the conclusion are provided below.

An Air Force introductory course in electronics uses a personalized system of instruction whereby each student views a videotaped lecture and then is given a programmed instruction text. The students work with the text until they have completed the training and passed the test. The pace at which the students complete the course varies and the faster students wait until the others complete before the entire group proceeds further. An alternative system, whereby students viewed the same video-taped lecture and then guided by computer-assisted instruction in place of the programmed text, was proposed.

It is the goal of the institute to analyze and compare the efficiencies of both the methods and then to determine the most efficient method of training. Statistical analysis was performed to determine the method that had better pace and consistency of completion. From the analysis, it was concluded that the computer-assisted method enabled more students to complete the course together than before but not sooner on an average. Additional data and a more effective method of testing is required in order to predict more accurately the efficient method that can be used as the training program in the future.

Force Training Institute

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CASE BACKGROUND An Air Force training institute had conducted a study in order to evaluate efficiency of their proposed computer-assisted training method for the introductory course in electronics. To compare the proposed and the current methods of instruction, an entering class of 122 students was assigned randomly to one of the two groups of 61 students each using either of the methods. The completion time in hours was taken for each student in the study.

The objective is to find the difference in the population means of the two training methods; to identify the most effective method of instruction and to make a final decision on the training program to be used in the future. STATISTICAL ANALYSIS As an alternative to the current training method, a new computer-assisted method was proposed. To evaluate the effectiveness of this method, a class of 122 students was assigned randomly to one of the training methods therefore forming two groups of 61 each.

The course completion time taken (in hours) by the students, of both the groups were collected. Descriptive summaries for the completion times of both the methods were obtained using MS Excel tool and the measures of central tendency and variability were hence found so that the data could be understood better. This study involves two populations: a population of students using the current training method and a population of students using the proposed computer-assisted training method.

In terms of time required to complete the training program, the population means are as follows: µ1 = the mean course completion time for students using the current training method µ2 = the mean course completion time for students using the proposed computer-assisted training method The institute hopes to show that the computer-assisted training method will provide a shorter mean course completion time and that the entire group proceeds together with other aspects for the training. Thus, evidence to conclude that µ2 is less than µ1; in this case, the difference between the two population means, µ1 – µ2, will be greater than zero.

The research hypothesis µ1 – µ2 >0 is stated as the alternative hypothesis. Thus, the hypothesis test becomes H0: The computer-assisted training method does not provide smaller population mean course completion time than the current method i. e. , µ1 – µ2 ? 0 H1: The computer-assisted training method provides smaller population mean course completion time than the current method i. e. , µ1 – µ2 > 0 The level of significance is taken as 5%. The test statistic‘t’ was performed for this case using the paired t-test analysis tool in MS Excel, with hypothesized mean difference as zero and assuming equal variances.

The calculated value and critical value, with ? =0. 05, of the test statistic were found and the rejection rule for the right-sided test (reject H0 if zcal > z? ) was used to decide about the validity of the null hypothesis. RESULTS AND FINDINGS The measures of central tendency and variability of the completion time taken by the students who used the two methods were determined. The sample means of course completion time for the current and computer-assisted training method were found to be 75. 066 hours and 75. 426 hours respectively. The sample mean completion time for the proposed method was found to be 21. mins more than that for the current method, which shows that the students on an average have slightly taken more time than earlier. The sample standard deviations for the same were determined as 3. 945 and 2. 506, and the co-efficients of variance were 5. 3% and 3. 3%. The pace of completion is seen to be more consistent and less varying for the entire group using the computer-assisted method. Also, the maximum time taken for this group is lesser than that taken for the current method. According to the rejection rule for the right-sided test, reject H0 if zcal > z?.

From the hypothesis testing, it was found that the critical value of the test statistic was 1. 658 and the calculated value was -0. 603. Therefore the decision taken is: Do not reject H0, as there is no enough evidence the computer-assisted training method provides smaller population mean course completion time. As the null hypothesis cannot be rejected there is a possibility for the two population means to be equal. CONCLUSION The alternative system of computer–assisted instruction was proposed in order to improve the pace of the course completion by all the students of the program.

Using the current programmed instruction text method, the fast students had to wait until the slow students completed the introductory course before the entire group proceeds together with other aspects of training. This gap in the course completion is expected to be rectified by the new computer-assisted method and also to improve the pace of the learning. The hypothesis testing has shown that there is not enough evidence that the computer-assisted training method provides smaller population mean course completion time i. . for the all the students in the program. Therefore, the new method can be helpful for the whole set of students to complete the course more or less together but may not quicken the completion process. More data is required in order to prove that the new method is more efficient in terms of quicker and more consistent pace of completion. The new method may be more effective with the students getting used to the system and hence the test must be performed again after a certain time gap for another course perhaps.

Another considerable fact is that the two samples are independent, and so the performance level and the learning speed of the students in the two groups are different. This may have an effect on the pace of course completion and hence, it can be suggested that the test be done with the same set of students for both the methods. The introductory course test may be conducted in two phases: the first using the text method and the second with the computer-assisted method, so that the syllabus is different for each test.

Additionally, the data of the performance levels and the learning speed of the students may be included and a multiple regression analysis be done in order to determine their influence on the course completion time taken by the students, therefore enabling to analyze the efficiency of the two methods. In this manner, matched samples of same students can be used to identify the most efficient method of training more accurately.

REFERENCES: Ken Black. Business Statistics: Contemporary Decision Making, 3rd ed. Thomson Learning, 2001. Anderson, Sweeny and Williams. Statistics for Business and Economics, 9e. Cengage Learning, 2010.

Air Force Essay Example

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This sample is done by Scarlett with a major in Economics at Northwestern University. All the content of this paper reflects her knowledge and her perspective on Air Force Essay Example and should not be considered as the only possible point of view or way of presenting the arguments.

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