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What is the difference between a false positive and a false negative?

Short Answer

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A false positive is an error that shows up when results are interpreted as positive (e.g. something is present when it's actually not, something is detected as above the limit when it's actually below the limit), while a false negative says the other way around (e.g. Something is identified as being below the limit when it is actually above the limit, and something is recognised as being absent when it is truly present).

Step by step solution

01

Definition of false positive and false negative.

False positive:

In analytical Chemistry, False positive is an assumption that the concentration of analyte goes above a certain limit, in fact the concentration is below the limit.

False negative:

In analytical Chemistry, False negative is an assumption that the concentration of analyte is lower than a certain limit. In fact, the concentration is above the limit.

02

Difference between false positive and false negative

When you get a positive test result when you should have gotten a negative result, it's known as a false positive. It's also known as a "false positive error" or "false alarm." It's most commonly employed in the medical area, but it can be applied to other fields as well (like software testing).

Examples:

  • A pregnancy test indicates that you are pregnant when you are not.
  • You have a positive cancer screening test, but you don't have the disease.
  • A prenatal test for Down's Syndrome comes up positive even though your foetus does not have the disorder.
  • Your computer's virus software wrongly classifies a safe programme as harmful.

When a negative test result is incorrect, it is referred to as a false negative.To put it another way, you get a negative test result when you should have had a positive one. For instance, suppose you take a pregnancy test and it comes back negative (not pregnant). You are, however, expecting a child. It's possible that you got a false negative on a pregnancy test because you took it too soon, used diluted urine, or checked the findings too quickly. A false negative is a possibility with almost every diagnostic test. A cancer test, for example, could come back negative when you truly have the condition.

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Most popular questions from this chapter

A solution containing3.47mMX(analyte) and1.72mMS(standard) gave peak areas of3473and 10222,respectively, in a chromatographic analysis. Then1.00mLof 8.47mMSwas added to5.00mLof unknownX,and the mixture was diluted to10.00mL. This solution gave peak areas of5428and4431forXandS, respectively.

(a) Calculate the response factor for the analyte.

(b) Find the concentration of S(mM)inthe10.0-mLmixture.

(c) Find the concentration of X(mM)inthe10.0-mLmixture.

(d) Find the concentration ofXintheorignalunknown.

Consider a sample that contains analyte at the detection limit defined in Figure. Explain the following statements: There is approximately a 1%chance of falsely concluding that a sample containing no analyte contains analyte above the detection limit. There is a50%chance of concluding that a sample that really contains analyte at the detection limit does not contain analyte above the detection limit.

What is the difference between repeatability and reproducibility? Define the following terms: instrument precision, intra-assay precision, intermediate precision, and interlaboratory precision. Which type of precision is a synonym for reproducibility?

Standard addition graph. Students performed an experiment like that in Figure 5-7 in which each flask contained 25.00mLof serum, varying additions of 2.640MNaCIstandard, and a total volume of 50.00mL.


(a) Prepare a standard addition graph and find [Na+]in the serum.

(b) Find the standard deviation and 95%confidence interval for [Na+].

State when standard additions and internal standards, instead of a calibration curve, are desirable, and why.

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