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Setler [38]
3 years ago
14

MVUT =175, mVUJ=17x-3, and mJUT=17x+8. Find x

Mathematics
1 answer:
kotykmax [81]3 years ago
5 0
The diagram of the three angles is shown below with point U as the point where all three lines meet.

Angles property: Angles around a point add up to 360°

We set up an equation

175+17x-3+17x+8=360
180+34x=360
34x=360-180
34x=180
x= \frac{180}{34}= \frac{90}{17}
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Divide 3 by 900 then multiply by 2
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Suppose that 100,000 men were screened for prostate cancer for the first time. Of these, 4,000 men had a positive result on the
Virty [35]

An actual two-by-two table is a tabular representation containing two rows and two columns.

  • The columns consist of the tested True positive for prostate cancer and tested True Negative for prostate cancer
  • The rows consist of the predicted positive screening and predicted negative values

<h3>a)</h3>

Mathematically, the set-up of the two-by-two table for this data can be computed as:

Tested                  True Positive for cancer   True Negative    Total

Predicted Positive         800                            3200                 4000

Predicted Negative        100                            95900              96000

Total                                900                            99100              100000  

<h3>b)</h3>

The prevalence rate of prostate cancer in this population is:

\mathbf{ =\dfrac{900}{100000}}

\mathbf{ =\dfrac{9}{1000}}

= 9 per thousand.

<h3>c)</h3>

The calculation of the sensitivity of this screening is as follows:

\mathbf{=\dfrac{TP}{TP+PN_1}}

where;

  • TP = True positive for cancer
  • PN₁ = Predicted Negative for true positive cancer

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\mathbf{=\dfrac{800}{800+100}}

= 0.889

= 88.9%

The interpretation shows that 88.9% are correctly identified to be actual positive for prostate cancer.

<h3>d)</h3>

The calculation of the specificity  of this screening is as follows:

\mathbf{=\dfrac{PN_2}{PN_2+TN}}

where;

  • TN = True positive for cancer
  • PN₂ = Predicted Negative for true negative cancer

∴

\mathbf{=\dfrac{95900}{95900+3200}}

= 0.9677

= 96.77%

The interpretation shows that 96.7% of an actual negative is correctly identified as such.

<h3>e)</h3>

The positive predicted value of the screening test is computed as:

\mathbf{= \dfrac{TP}{TP + TN}}

\mathbf{= \dfrac{800}{800 + 3200}}

= 0.2

= 20%

The interpretation of the positive predicted value of this screening shows that 20% that are subjected to the diagnosis of positive prostate cancer truly have the disease.

Learn more about tabular representation here:

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