Online Rating of Professors - Statistics Project Example

?Introduction Online rating has grown popularity with the site RateMy com. In the website, are able to rate their professors in terms of the overall quality by which they are able to deliver their lessons, from the categories easiness, helpfulness, clarity, and prior interest in the subject. Professors are also given a chili-pepper icon when the reviewer thinks that the professor is “hot” in terms of physical looks. Some controversy has risen from the website as students and even professors devour the results as if it were an official ranking method. Some students even go to the extent of basing the schools and classes that they will take on the reviews made at the website. To make the ranking process “fair” to the professors, these members of the academe are allowed to respond to the feedbacks given to them through the “Professors Strike Back” portion of the website. Understandably, heated exchanges can occur as both students and professors defend themselves and their views. Some professors tend to be sensitive about the issues hurled against them while others choose to dismiss the ranking site entirely. All these aside, this paper wants to investigate if there are underlying factors affecting the overall quality rating of professors at Rate My Professor. As such, this study poses the following research question: RQ: Do differences in underlying factors affect the overall quality rating of professors? RQ: Which factors significantly affect the overall quality rating of professors? Methods In order to answer the proposed research question, this study used a quantitative research methodology using data taken from the Rate My Professor website. The data were first subjected to descriptive statistics in order to take an initial picture of the data. Then, the dependent and independent variables were subjected to correlation and regression analysis to find out if there is an underlying relationship between them. In addition, t tests and Analysis of Variance were also used to see if there are factors affecting differences in overall quality ratings of professors. There were a total of 730 data points for this study. Results Descriptive Statistics The descriptive statistics of important variables were taken in order to find out the initial behavior of the data. A summary of these descriptive statistics are given in Table 1. Box plots reflecting the behavior of the data are also provided in Figures 1 to 5. Table 1. Summary of Descriptive Statistics. Descriptive Statistics Dept Division num easiness overall count 730 730 730 730 730 mean 46.24 2.2 34.27 3.327 3.712 sample variance 598.07 0.96 683.18 0.541 0.693 sample standard deviation 24.46 0.98 26.14 0.735 0.832 minimum 2 1 10 1.2 1.4 maximum 96 4 168 5 5 range 94 3 158 3.8 3.6 Figure 1 shows that most of the data from the graph is concentrated in the second quarter. Then to the third quarter, then evenly spread to the first quarter, and the fourth quarter. There does not seem to be any outlier in the graph. Figure 1. Box plot for the variable “Department” Based on Figure 2, there is no first quarter data from the graph. Either that it is insufficient to generate a first quarter, or the first quarter is so concentraated that the data could not show. It is most likely that the data is insufficient to generate a first quarter. Figure 2. Box plot for the variable “Division” Figure 3 shows that most of the data is concentrated on the first quarter. Then on the second quarter, then the third, then the fourth. The one thing that makes this graph interesting is the high amount of outliers in the graph, which is not seen from the other graphs. Figure 3. Box plot for the variable “Num” Figure 4 shows that most data are concentrated on the third quarter, followed by the last and third, and a really spreaded first quarter. There is a possibility that there is an outlier in the first quarter. Figure 4. Box plot for the variable “Overall” Figure 5 shows that data are mostly concentrated in the second quarter. And then the third. The rest of the data are evenly speaded on the first and and last quarter. Figure 5. Box plot for the variable “Easiness” Effect of Hotness on Overall Quality Ho: There is no difference in overall quality when professors are grouped according to hotness. Ha: There is a significant difference in overall quality when professors are grouped according to hotness. alpha = .05 Table. Results of t test.   nothotOverall HotOverall Mean 3.38 4.28 Variance 0.67 0.22 Observations 461 269 Hypothesized Mean Difference 0 df 728 t Stat -18.89 P(T Read More