Answer:
The unit price is the cost per unit of an item or the cost/price for each item.
1) <u>4$</u> per pound. By simplifying the proportion (constant ratio) between the cost, and the pounds of apples. 3 pounds of apples cost 12$ → 3/3 pounds of apples cost 12/3$ → 4 dollars for every pound.
2) <u>2$</u> per pound. By evaluating the rate of change (change in the y over x or dependent variable over independent) in the equation: y = <u>2</u>x. y is the cost in dollars, and x is the pounds of apples. So there are 2 pounds (weight) of apples for every dollar.
3) <u>3$</u> per pound. Given a graph with a y scaled by 3, and an x scaled by 1 with a graph y = x or 1 unit up for every unit right. This must be equivalent to y = 3x. Where y is labeled as the cost in dollars, and x as the weight in pounds. So there are 3 dollars for every pound of apples.
4) Store B. Because 2 is less than 3 which is less than 4.
Answer: approximately 29 feet
Explanation: You need to find a tree so that the angle of elevation from the end of the shadow to top of the tree is 40 degrees.
The length of the shadow is an adjacent side and is 35.
The height of the tree is the opposite side. You could use X.
Tan ratio = opposite/adjacent
tan(40) = x/35
x = 35*tan(40) =29.37
Answer:
x = 
<u><em>or </em></u>x = 
Step-by-step explanation:
5 − 6 2 − 1 3 = 0
− 6 2 − 1 3 + 5 = 0 -6x^2-13x+5=0 −6x2−13x+5=0 − 1
( 6 2 + 1 3 − 5 ) = 0
To solve for w, you would take 9 and subtract that from the 69. after that you end up with 60=5w to find w, divide both sides by 5. 60 divided by 5 is 12, giving you your answer .
Answer:
a. There's a 95% chance that the true proportion is in the confidence interval.
Step-by-step explanation:
When we want to estimate a property of a population (a population's parameter), without surveying the population, we use samples.
Then, with the information of the samples we can calculate the statistics and infere properties about a population. This inferences obviously came with some uncertainty, depending on the properties of the sample and specially the sample size.
When we talk about confidence intervals, we use the statistic of the sample (in this case, the mean) to estimate a range of values it is expected to find the true mean of the population. The width of this interval depends on the sample standard deviation and the sample size.
The value of the confidence interval (95%, 99%, etc) represent the probabilty that the true mean is within this interval.
