<jupyter_start><jupyter_text>Q-QPlot<jupyter_code># Data loading
survtime<-read.table("14_03_dataset.txt", header=FALSE, dec=".")
# Normal Q-Q Plot
qqnorm(survtime[ ,'V1'])
qqline(survtime[ ,'V1'])
# Exponential Q-Q Plot
qqplot(rexp(300, rate=1), survtime[ ,'V1'])<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.19387755102040816, 'fraction_numerical': 0.03741496598639456, 'mean_word_length': 9.172413793103448, 'pattern_counts': {'":': 0, '<': 6, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '657139', 'license': 'MIT', 'n_tokens_mistral': 135, 'n_tokens_neox': 128, 'n_words': 20, 'path': '14_ReliabilityDataAnalysis/14_03_ExploratoryDataAnalysis/14_03_06_QQPlot.ipynb', 'repo_name': 'RausandBarros/ReliabilityBookScripts', 'size': '294'}