Usability Engineering Quantitative Analysis - Assignment Example

Introduction This exercise involves the analyses of data that has been taken from a 3 day diary study and another set of data collected from students. The objective of this study is to understand the reading experience of students in the class. From the spreadsheets provided, the data will be cleaned and encoded for analysis on excel sheets. The report below presents the quantitative analysis of this data as determined. Data analysis In order to clean up and encode the data, the data was scrutinized in order to identify the most important fields that were weighty in regard to their contribution to the decisions to be made. The fields that were selected were: What did you read? , what was the reading medium? , what was the reason for reading? , what was your native language? , How old are you? And do you know any other languages? The data on gender in regard to whether one was male or female was deemed to be unsuitable for analysis since the number of males exceeds that of females by a far large margin. The missing data was filled using the results from the frequency distribution tables for the selected data and the redundancy that existed in the dataset was removed. Some fields such as the use of lectures notes was merged with paperwork and the use of slides was merged with the use of lecture slides. Data about websites was combined under the umbrella of websites. The descriptive statistics for the selected fields were computed as shown in the table below Table 1: Descriptive statistics for different fields Field Mean no. of respondents Mode (most satisfying) Standard deviation (variation from the average no. of respondents) What did you read? 7.0 128 (email) 23.35 What was the reading medium? 66 380 (laptop) 112.07 What was the reason for reading? 168 330 (for enjoyment) 151.52 What was your native language? 3 72 (English) 5.41 How old are you? 43.5 48 ( 25 or younger) 6.36 Do you know any other languages? 4.0 47 10.00 Through analysis of the statistics obtained in the table above, it emerged that the question of what was most read by the respondents was obtained through the mode. 128 people were determined to have read their emails. The laptop was found to be the most commonly used medium. A total of 380 respondents indicated that they had used their laptops to read. Most of the respondents indicated that English was their native language. The number of persons who were determined to have indicated that English was their native language was 72. The highest number of respondents also indicated that they were 25 years of age or younger as compared to those who were over 25 years old. The highest number of the respondents also indicated that they had knowledge of more than one language compared to those who were unilingual. In regard to the type of media used, the average number of those who used e readers was 11 and those who used papers were 107 in number. Figure 1: Graph showing the distribution of the type of media used This narrows down to 1.29 % using e readers while 12.56 % used papers as a media. These results from the sample population indicate that the people prefer to use the traditional medium of communication as compared to the modern media. A further analysis of the data on the media used for communication is tabulated below. The table below shows the confidence intervals used for the two media used for communication. Table 2: confidence intervals distribution table Field Standard deviation Standard error Margin error e-readers 1.45 0.402 0.332 Papers 14.08 3.91 3.23 An analysis on the level of satisfaction with reference to the type of media that was used, it emerged that most of the respondents were satisfied with the websites as the sources of information. This amounts to 57.5 % of the total level of satisfaction expressed by the respondents. The respondents also indicated that class tests, instagram apps, lecture notes, lecture materials, PDF, paper works, recipes and wheels were the least satisfying to the respondents. They had a satisfaction of 0.11 % of the total level of satisfaction expressed by the respondents. Figure 2: Distribution of the level of satisfaction of the respondents to various types of media If we try to relate different datasets from the two separate spreadsheets, it is expected that age will be closely related to the reason for reason. People who are below the age of 25 are likely to spend more time reading for study, enjoyment while people who are over the age of 25 are likely to spend time reading for the purpose of either studies, work or their own personal reasons. Relating this data, we can generate the following chart to demonstrate the level of confidence among the different age groups. Figure 3: Relationship between age and the type Conclusion and recommendations From the statistical analysis carried out above, the data has been cleaned and encoded as required. The redundancy that existed in the data has been removed and the data analyzed under different criteria. In regard to the results obtained from the analysis, the following recommendations can be made: There is need to improve the level of satisfaction of the lecture materials. In this case, this refers to all the materials provided during lectures include tutorials, slides, notes, printouts and the actual oral lectures. There is also need to encourage people who are below the age of 25 to use the websites for other purposes other than enjoyment. The results indicated that the highest percentage of the young people used the websites for enjoyment and very few people within this age bracket used them for other purposes. The traditional methods of learning such as blackboards, walls, posters, posts and billboards show a very low level of confidence among the respondents while laptops and smart phones show the highest level of satisfaction among the respondents. There is need for the modification of the modes of relaying information so that these methods to not become obsolete in the long run. Read More