Do EVs Catch Fire More Than Gas Cars in 2023?

Do EVs Catch Fire More Than Gas Cars in 2023? Data Scientist expert analysis answer. What are the Statistics on Tesla Fires in 2023? 🔥 What Percentage of Teslas Catch Fire in 2023? 🔥 #----------------------------------------------------------------------------------------# Teslas autos are 48 times more likely to combust than a combustion engine! #----------------------------------------------------------------------------------------# 14.5% of Tesla Fatalities involve 🔥 🔥 🔥 🔥 🔥 🔥 🔥 🔥 🔥 🔥 🔥 🔥 #-----------------------------------------------------------------------------------------# That means out of 1000 fatalities, 145 will involve fire. #------------------------------------------------------------------------------------------# Because 7.7 million rows of Big Data from Cornell University covering the years 2016 - 2023 suggests: The national average is 0.3% #------------------------------------------------------------------------------------------# That means for every 10,000 deaths only 30 result in fire. #-------------------------------------------------------------------------------------------# Now image if the entire country was scaled to all EVs. #----------------------------------# The Data is overwhelming; The video description gives you links to the datasets, study, and access to the code so you can replicate the findings yourself. #------------------------------------------------------------------------------------------# Just by liking this video, you are helping spread the word! If You Share this video, you might save a life or at least inform at Tesla driver!u If you think Im wrong, then prove it to me in the comments below. Hello world my name is data mining Mike I’m a data scientist and machine learning researcher. As defensive drivers and informed consumers, lets mine into the data! The following study compares two datasets: Countrywide ’descriptions’ of fatal accidents vs. Tesla Death ’descriptions’. The Cornell University Countrywide Big Data study (7.7 million rows or instances) was originally compiled to predict the severity of car accidents with several exogenous factors. The big data study also comes with an accident ’description’ column, containing words to be tallied; The column is compiled of the individual documented ‘descriptions’ of the accidents. The words to be searched are: “fire”, “bursts“, “ignites“, “ignited“, “combusts“, “flames“, “burns“, “fiery“, and “erupt“. The Tesla automobile fatalities dataset (Tesla Deaths) will be compared to the big-data-baseline. It’s important to included the synonyms of fire to detect the avoidance of people stating the word FIRE! The Tesla Deaths dataset has a ’description’ column that can be exploited for the same keywords. The results where that 14.5% of Tesla deaths involve ‘fire’ or synonyms; In contrast the countrywide average is only 0.3%. The two statistical tests used, led to the rejection of the null hypothesis. No, 14.5% and 0.3% are not in the same range or proportion within a sample population. Importantly, 14.5% represents roughly 145 out of every 1000 occurrences of death will contain ’fire’ or its synonyms. However, the national baseline is 0.3% equivalent to in decimal form. This represents a much smaller proportion, indicating only 30 occurrences out of every 10,000 instances. Lets explore the data! Based on the analysis of the data and the results of the Shapiro-Wilk test Man-Whitney U test, and Kruskal-Wallis test, we reject the null hypothesis(s) in favor of the alternative hypothesis(s). This means that there is evidence to suggest a significant difference between the percentage of Tesla fatalities involving ’fire’ or related synonyms (14%) and the percentage of deaths in the U.S. population baseline of fire-related incidents (0.3%). Given the non-parametric behavior of both datasets, the tests where appropriate, yielding p-values less than an alpha level of . The conclusion aligns with the statistical findings, indicating that there is a notable difference between the two populations in terms of fatalities related to ’fire’ or similar terms. This highlights the importance of further investigation and attention to safety in the context of Tesla and similar electric vehicles. Based off these findings, the implications of replacing all combustion engines with electric vehicles, would scale the number of vehicles fires up exponentially. More data needs to be compiled to monitor this trend. Lastly, this finding can now be used for a vanguard for consumer awareness.