A lumber yard has five different lengths of 2 by 4 boards. Based on cost per linear foot, which is the best deal available on 2
1 answer:
Complete Question:
Here is the complete question:
<em>A lumber yard has five different lengths of 2 by 4 boards. Based on cost per linear foot, which is the best deal available on 2 by 4 boards at this lumber yard?</em>
<em>2 × 4 BOARD PRICES </em>
<em>8 foot board for $2.95 </em>
<em>10 foot board for $3.15 </em>
<em>12 foot board for $4.10 </em>
<em>16 foot board for $5.80 </em>
<em>20 foot board for $6.95</em>
Step-by-step explanation:
- 8 foot board for $2.95
- 10 foot board for $3.15
- 12 foot board for $4.10
- 16 foot board for $5.80
- 20 foot board for $6.95
Therefore, <em>10 foot board for $3.15</em><em> </em>is the best deal available on 2 by 4 boards at this lumber yard. It means you should be able to get 1 board for $0.315 when you buy 10 boards.
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Answer:
96.49% probability that the mean rent is more than $1100
Step-by-step explanation:
To solve this question, we need to understand the normal probability distribution and the central limit theorem.
Normal probability distribution
Problems of normally distributed samples are solved using the z-score formula.
In a set with mean and standard deviation
, the zscore of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.
Central Limit Theorem
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
In this problem, we have that:
What is the probability that the mean rent is more than $1100?
This is 1 subtracted by the pvalue of Z when X = 1100. So
By the Central Limit Theorem
has a pvalue of 0.0351
1 - 0.0351 = 0.9649
96.49% probability that the mean rent is more than $1100
9514 1404 393
Answer:
-3, 7, 8
Step-by-step explanation:
You can fill in the boxes from the table values as shown in the attachment.
The leading coefficient is negative because the parabola opens downward. The value of it is the change in y-value as x changes by 1 unit either side of the vertex.
The vertex is identified by the fact that the y-values are symmetrical either side of the vertex.
