Calculate Statistic False Positives with Our Examples
Recent questions in False Positive
College StatisticsAnswered question
Daphne Haney 2022-04-07The prevalence of breast cancer in women over 40 in country X is estimated to be 0.8% (i.e., 8 in every 1,000 women in that age group).
Mammograms test for the presence of breast cancer. A positive result indicates that the disease is present. A negative result indicates that it is not.
The sensitivity of a mammogram test for breast cancer is estimated to be 90%. This is the probability that the mammogram will give a positive result when the person being tested does have breast cancer.
The false positive rate for the mammogram is 7.5%. This is the probability that the mammogram will give a positive test result when the person being tested does not have breast cancer.
All women who test positive (816) in the mammogram are referred for a further, different examination, which however has the same sensitivity and false positive rates as the first test.
What is the probability that a woman referred for this examination and testing positive again, actually does have breast cancer?
Mammograms test for the presence of breast cancer. A positive result indicates that the disease is present. A negative result indicates that it is not.
The sensitivity of a mammogram test for breast cancer is estimated to be 90%. This is the probability that the mammogram will give a positive result when the person being tested does have breast cancer.
The false positive rate for the mammogram is 7.5%. This is the probability that the mammogram will give a positive test result when the person being tested does not have breast cancer.
All women who test positive (816) in the mammogram are referred for a further, different examination, which however has the same sensitivity and false positive rates as the first test.
What is the probability that a woman referred for this examination and testing positive again, actually does have breast cancer?
College StatisticsAnswered question
Marissa Singh 2022-04-06The occurrence of false positives [in some experiment] is 40%
What does this mean? Does it mean that 40% of positives are false? Or 40% of all tested patients are specifically both false and positive? Or say 40% of those that are false are positive?
What does this mean? Does it mean that 40% of positives are false? Or 40% of all tested patients are specifically both false and positive? Or say 40% of those that are false are positive?
College StatisticsAnswered question
Karissa Sosa 2022-04-06What is the rationale behind ROC curves?
I am not sure how ROC curves work. I see that the X-Axis is the false positive rate while the Y axis is the true positive rate.
1) I don't understand how for a given statistical learning model, you could have the true positive and false positive rate to vary from 0 to
1. Are you changing parameters in the model to make it so?
2) What about true negatives and false negatives? How are these represented in the curve?
I am not sure how ROC curves work. I see that the X-Axis is the false positive rate while the Y axis is the true positive rate.
1) I don't understand how for a given statistical learning model, you could have the true positive and false positive rate to vary from 0 to
1. Are you changing parameters in the model to make it so?
2) What about true negatives and false negatives? How are these represented in the curve?
When you are starting with a careful examination of the college-level statistics, you will encounter an interesting concept known as false positive statistics. Start with the examination of the false positive examples to learn how they work and why probability plays an essential role. The list of answers to the most common questions will help you to approach false positive problems and see how they work in practice and how the measure of accuracy works regardless of what Machine Learning Method you might be using. Remember to study the null hypothesis samples while you examine the false positives task examples.
