Answer:
The perimeter of triangle PQR is 17 ft
Step-by-step explanation:
Consider the triangles PQR and STU
1. PQ ≅ ST = 4 ft (Given)
2. ∠PQR ≅ ∠STU (Given)
3. QR ≅ TU = 6 ft (Given)
Therefore, the two triangles are congruent by SAS postulate.
Now, from CPCTE, PR = SU. Therefore,
Now, side PR is given by plugging in 3 for 'y'.
PR = 3(3) - 2 = 9 - 2 = 7 ft
Now, perimeter of a triangle PQR is the sum of all of its sides.
Therefore, Perimeter = PQ + QR + PR
= (4 + 6 + 7) ft
= 17 ft
Hence, the perimeter of triangle PQR is 17 ft.
It can help you by showing you what you do more simplified. For example 3(x+5) is 3 time x + 3 times 5
The Correct option is 36.60
Step-by-step explanation:
The key to solving this question lies
around measurement
conversion,specifically converting
grams into its equivalence in
kilograms.
1000 grams equal one kilogram
9 grams=9/1000 kg
9 grams=0.009 kg
70 grams=70/1000 kg 1000 grams equal one kilogram
9 grams=9/1000 kg
9 grams=0.009 kg
70 grams=70/1000 kg
70 grams=0.07 kg
Julie pays=$600*0.009=$5.4
Jacques pays=$600*0.07=$42
Jacques pays $36.60 more ($42-
$5.4) than Julie paid
Option is wrong because that was Jacques pays=$600*0.07=$42
Jacques pays $36.60 more ($42-
$5.4) than Julie paid
Option is wrong because that was
what Julie paid
Option D is wrong because that was
what Jacques paid
Option B is obviously wrong
Answer:
NO
Step-by-step explanation:
The changeability of a sampling distribution is measured by its variance or its standard deviation. The changeability of a sampling distribution depends on three factors:
- N: The number of observations in the population.
- n: The number of observations in the sample.
- The way that the random sample is chosen.
We know the following about the sampling distribution of the mean. The mean of the sampling distribution (μ_x) is equal to the mean of the population (μ). And the standard error of the sampling distribution (σ_x) is determined by the standard deviation of the population (σ), the population size (N), and the sample size (n). That is
μ_x=p
σ_x== [ σ / sqrt(n) ] * sqrt[ (N - n ) / (N - 1) ]
In the standard error formula, the factor sqrt[ (N - n ) / (N - 1) ] is called the finite population correction. When the population size is very large relative to the sample size, the finite population correction is approximately equal to one; and the standard error formula can be approximated by:
σ_x = σ / sqrt(n).
Answer:
n^2 - n - 12 = (n+3)(n-4)
Step-by-step explanation:
3 times - 4 = -12 ( two numbers when multiplied = -12, when added=-1)
3 + -4 = -1
