In this paper, we investigate a campus wide Wireless Local Area Network (WLAN) over a period of one month with the help of an advanced training system. Traffic characteristics and analysis has been performed based on the users` connectivity and their traffic behavior in a WLAN environment. The obtained results predict the users` traffic intensity in different time slots of the day and different days of the week. Moreover, traffic intensity and available bandwidth of each Access Point (AP) in the WLAN has been investigated.