The objective of this study is to compare three forecasting methods on three agricultural products consisting of fresh whole chicken (include bone no entrails) red meat pork hip section and Jasmine rice. These methods are Simple Exponential Smoothing method Holt’s method and Winter’s method. Data are colleced for a period of 60 months from January 2007 to December 2011. The most suitable forecasting method are the one that shows no residual autocorrelation and gives the lowest MSE MAPE. The results show that Simple Exponential Smoothing method is the most suitable method on three agricultural products due to this method reveals no residual autocorrelation and displays the lowest MSE MAPE.

The purpose of this study is to compare four forecasting methods on SET Index SET 50 Index and SET 100 index. These methods are Simple Exponential Smoothing Holt’s Method Box-Jenkins Method and Regression Analysis. Two sets of Index data were used in this study. The first one used as a training set was collected at the end of each day from January 2 2008 to September 30 2011. The other one used as a testing set was collected at the end of each day from October 3 2011 to October 14 2011. The diagnostic check was used to test each method. The MAE MSE and MAPE from each method shows that Box-Jenkins is more appropriate to the forecasting of SET Index SET 50 Index and SET 100 Index because its MAE MSE and MAPE are fairly low and have no autocorrelations. This leads to the conclusion that the appropriate models for forecasting of SET Index SET 50 Index and SET 100 Index are ARIMA (212) ARIMA (213) and ARIMA (213) respectively. The most stock market indices are correlated to SET Index SET 50 Index and SET 100 Index is Composite Index of Indonesia

The purpose of this research is to study and compare several factors which can influence how first year students make their decisions to study in Rajamangala University of Technology Phra Nakhon. The samples were about 370 students which were collected by Quota Sampling. Questionnaires were used as a research tool to collect data. The data were analyzed by percentage arithmetic mean standard deviation t-test F-test and LSD. This research found that 1. Most of students are female and have graduated from high school with GPA of 3.09. They study in the faculty of business administration. Their hometown is in Bangkok and perimeter. Their parents are business owner and have average income about 21950.88 bath per month. They spend money about 148.66 bath per day. 2. Mostly the students have decided to study in Rajamangala University of Technology Phra Nakhon by themselves and have chosen not to apply in other universities. In addition they have known about admission from the internet. 3. The universitys reputation is a main factor that students use to consider in order to study in Rajamangala University of Technology Phra Nakhon. Other factors that have less influence are curriculum students requirement lecturer universitys administration financial support transportation location and environment respectively. Almost all of factors have high average score; however locational and environmental factors have moderate average score. 4. This research comparatively concludes that different factors have influenced students to enroll in Rajamangala University of Technology Phra Nakhon in many different levels with statistical significance at 0.05 level. 5. The students with different genders GPA education backgrounds howntowns parents income and daily expense have various levels of factor that affects students decision making for enrollment with no statistical significance at 0.05 level. 6. The students with different faculties and alternatives to apply in other universities have different levels of factor that affects their decision to enroll in Rajamangala University of Technology Phra Nakhon with statistical significance at 0.05 level.