Adaptive streaming is a popular technique that allows quality adaption for videos based on the current playback conditions. The purpose of this thesis is to investigate how chunks in video files downloaded from YouTube correlate to each other. We investigate how the chunk size characteristics depend on the category and encoding of the video. The main focus is to analyze the chunk sizes of the video, focusing on distinctness between 360$^\circ$ and 2D videos. This is performed using the YouTube API. The videos are downloaded and analysed using youtube-dl and mkv-info. The results show that chunk sizes for adjacent qualities have higher correlation and that videos having a similarity between scenes have higher correlation. In addition, 360$^\circ$ videos differ primarily from regular 2D videos by the amount of qualities used and a generally higher correlation for all qualities.