Assuming 5 is the base. I'm going to leave that out for now.
2log(5x^3) + (1/3)log(x^2+6)
power rule
log(5^2 x^3*2) + log((x^2 + 6)^(1/3))
log(25x^6) + log((x^2 + 6)^(1/3))
quotient rule
log(25x^6 / (x^2 + 6)^(1/3))
Answer:
0.497
Step-by-step explanation:
Using the binomial probability formula :
P(x =x) = nCx * p^x * (1 - p)^(n - x)
From the question :
n = 6 ; x = 3 ; p = 0.42
P(x = 3) +... P(x = 6)
P(x = 3) = 6C3 * 0.42^3 * (1 - 0.42)^(6-3)
P(x = 3) = 20 * 0.074088 * 0.195112
P(x = 3) = 0.28910915712
Then find p(x = 4).. + p(x = 6)
Using a calculator :
P(X >= x) = 0.497
The correct answer is this one: "B) More girls than boys prefer Dodge over Ford or Chevrolet." Jamie collected data from her classmates on their favorite make of car. Based on the data collected, if one hundred boys and one hundred girls are given their choice of a car then <span>More girls than boys prefer Dodge over Ford or Chevrolet.</span>
Answer:
Current yield = 5.46%
Step-by-step explanation:
Current yield is calculated by dividing the annual income (coupon) on the bond divided by the current price of the bond
Current yield = Annual coupon / Current price
In this case,
Face value or Par value = $7,600
Price of the bond = $7,373 (shows it is a discount bond since the price < FV)
Coupon rate = 5.30%
Next, calculate the Coupon payment in dollars;
Annual coupon PMT = Coupon rate * Face value
Annual coupon PMT = 0.053 * 7,600 = $402.8
Therefore, Current Yield = 402.8 / 7,373 = 0.05463
Current yield = 5.46%
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:


= 9 per thousand.
<h3>
c)</h3>
The calculation of the sensitivity of this screening is as follows:

where;
- TP = True positive for cancer
- PN₁ = Predicted Negative for true positive cancer
∴

= 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:

where;
- TN = True positive for cancer
- PN₂ = Predicted Negative for true negative cancer
∴

= 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:


= 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:
brainly.com/question/8307968