Data scientists need to understand the fundamental concepts of descriptive statistics and probability theory. Formore information: https://datamites.com/data-science-course-training-chennai/

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2. Baye’s Theorem
Baye’s Theorem is used for determining the conditional
probability. It is based on the methodology that hte probability
of A given B equals the probability of B given A times the
probability of A over the probability of B.
Conditional Probability
Conditional probability states that the probability of the
occurrence of an event is based on an event occurring which
occurred previously.
Probability
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3. Accuracy
Sensitivity
It refers to the ability of a test to detect a
condition, if that condition exists.
True Positive
It detects the condition if the condition
exists.
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4. Accuracy
True Negative
It does not detect the condition if the condition is present.
False Positive
It detects the condition if the condition is absent.
False Negative
It does not detect the condition even if the condition is
present.
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5. Accuracy
Predictive Value Positive
In this case the proportion of the positive corresponds with the
presence of the condition.
Predictive Value Negative
It corresponds to the absence of the condition.
Specificity
It determines the ability of a test to exclude the condition if the
condition is absent.
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