Answer:
m:
Step-by-step explanation:
Pick two points (0,5) and (3,4)
use the formula to find slope: 
Insert values: 
m:
:-)
Answer:
The augmented matrix for the system of equations is
.
Step-by-step explanation:
This system consists in three equations with three variables (
,
,
).The augmented matrix of a system of equations is formed by the coefficients and constants of the system of linear equations. In this case, we conclude that the system of equations has the following matrix:
![\left[\begin{array}{cccc}0&2&-3&1\\7&0&5&8\\4&1&-3&6\end{array}\right]](https://tex.z-dn.net/?f=%5Cleft%5B%5Cbegin%7Barray%7D%7Bcccc%7D0%262%26-3%261%5C%5C7%260%265%268%5C%5C4%261%26-3%266%5Cend%7Barray%7D%5Cright%5D)
The augmented matrix for the system of equations is
.
Answer:
Daily points, you have made my day!!!!!!!!!!!!!!!!!!!!!!!!!!!
Step-by-step explanation:
Answer:
0.1151 = 11.51% probability of completing the project over 20 days.
Step-by-step explanation:
Normal Probability Distribution
Problems of normal distributions can be solved using the z-score formula.
In a set with mean
and standard deviation
, the z-score 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 p-value, we get the probability that the value of the measure is greater than X.
Expected completion time of the project = 22 days.
Variance of project completion time = 2.77
This means that 
What is the probability of completing the project over 20 days?
This is the p-value of Z when X = 20, so:



has a p-value of 0.1151.
0.1151 = 11.51% probability of completing the project over 20 days.
Answer:
The price of the homes in the Pittsburgh sample typically vary by about $267,210 from the mean home price of $500,000.
Step-by-step explanation:
The dotplots reveal that the variability of home prices in the Pittsburgh sample is greater than the variability of home prices in the Philadelphia sample. Therefore, the standard deviation of the home prices for the Pittsburgh sample is $267,210 rather than $100,740. The correct interpretation of this statistic is that the price of homes in Pittsburgh typically vary by about $267,210 from the mean home price of $500,000.