Answer:
27/36
Step-by-step explanation:
Count the white region (which is 36), and then count the shaded region (which is 27). And write the shaded region on the upper part (numerator), and the white part on the lower portion (denominator).
(-∞,∞)
[0,∞)
(-∞,0]
-2, 2
Answer:
(-∞,∞)
Step-by-step explanation:
The domainisthepossiblex values,sofor this functionx^2,the possiblex valuesare all thevalues
(-infinity ,infinity)
$1,675 and variable costs per plant are $3.65. What is the maximum profit Rebecca Clarke's
will make if it sells all the plants at the discounted price?
Answer:
$1,540.70
Step-by-step explanation:
1675/335 = 5
3.65 * 335 = 1222.75
Cost of $8.65 per plant, or $2,897.75 for every plant.
12.99 - 8.65 = 4.34
Profit of $4.34 per plant, or $1,540.70 total.
Answer:
3/4 sq. ft.
Step-by-step explanation:
The question is using feet and inches. So, you'd have to convert the 6 inches to feet. How many inches in one foot? 6. So 6=1/2 feet so you do 1 1/2*1/2=3/4
Answer:
1,000,000
Step-by-step explanation:
1mm=1e-6km
10mm=1e-5km
100mm=1e-4km
1000mm=000.1km
10000mm=0.01km
100000mm=0.1km
500000mm=0.5km
1000000mm=1km
slope:
What does the numerical value of the slope tell you?
The slope of the line is 0.993. A positive slope indicates a positive linear relationship between city mpg and highway mpg.
The slope of a regression line represents the change in the dependent variable (in this case, highway mpg) for a one-unit increase in the independent variable (city mpg).
In this equation, the slope is given by 0.993. This means that for every one-unit increase in city mpg, the highway mpg is expected to increase by 0.993 units.
The positive numerical value of the slope indicates that there is a positive linear relationship between city mpg and highway mpg. This means that as the city mpg increases, the highway mpg also tends to increase.
#SPJ12
Answer:
(a) 0.0178 <= p <= 0.0622
(b) p <= 0.0586
Step-by-step explanation:
We have that the sample proportion is:
p = 12/300 = 0.04
(to)
For 95% confidence interval alpha = 0.05, so critical value of z will be 1.96
Therefore, we have that the interval would be:
p + - z * (p * (1-p) / n) ^ (1/2)
replacing we have:
0.04 + - 1.96 * (0.04 * (1-0.04) / 300) ^ (1/2)
0.04 + - 0.022
Therefore the interval would be:
0.04 - 0.022 <= p <= 0.04 + 0.022
0.0178 <= p <= 0.0622
(b)
For upper bounf z-critical value for 95% confidence interval is 1.645, so upper bound is:
p + z * (p * (1-p) / n) ^ (1/2)
replacing:
0.04 + 1.645 * (0.04 * (1-0.04) / 300) ^ (1/2)
0.04 + 0.0186 = 0.0586
p <= 0.0586