At this resolution level of the data, each dot in the above graph represents about 200 Tesla Model S EVs (Electric Vehicles) produced prior to March 2017. Assuming there are 800 dots on the graph for a total of 160,000 produced, about 8 dots appear below 90% Remaining Range level. So the probability of a
Addition Rule of Probability
It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.
Expected Value
When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).
Probability Distributions
Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.
Basic Probability
The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.
 alt="At this resolution level of the data, each dot in
the above graph represents about 200 Tesla
Model S EVs (Electric Vehicles) produced prior
to March 2017. Assuming there are 800 dots
on the graph for a total of 160,000 produced,
about 8 dots appear below 90% Remaining
Range level. So the probability of a
substandard battery is 1%.
Tesla Model S Milenge vs Remaining Range
• Reranng
onginal tange
Tendine
20.00 kn 40000 k .c00 ks se00 im 100.000 kn 2000 m 14 ee m 160.000 km s8.000 km 200000 kn
Mileoge
What is the mean number of failures µ, ?
Sketch and label µ±30:
Hj =.
What is the standard deviation, o, of the
number of cars produced ?
(From Chapter 9) How many future random samples would be needed to make a 99% confidence interval (
Bound = .01) if the substandard rate has jumped to 2% ? Does this meet the minimum number of samples
required meet the basic conditions for a reasonable approximation of p ? If not, how many samples should be
taken ? Show this mean shift in your above sketch.
Justify your response
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
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