The correct answer is A: 2.
The slope compares the vertical change (the rise) to the horizontal change (the run) when moving from one fixed point to another along the line.
If you look at your graph, it takes 2 units up and 1 unit to the right in order to get to the next point on the line.
Therefore, the slope of the line is 2/1, or simply 2. It has a positive value because the line is sloping upward.
Answer:
Graph 1: Consistent Dependent
Graph 2: Consistent Independent
Graph 3: Consistent Dependent
Graph 4: Inconsistent
Step-by-step explanation:
Consistent means they have at least one solution. So lines that intersect once or lines that intersect infinitely many times are both consistent systems.
If they are the system that has one solution they are considered independent.
If they are the system that has infinitely many solutions then are considered dependent.
Inconsistent means they won't intersect at all.
First graph shows the same line graphed onto itself. That means they have infinitely many solutions and is therefore a consistent dependent system.
Second graph shows the lines intersecting once. That means they have one solution and therefore is a consistent independent system.
Third graph shows the same description of graph one and is therefore a consistent dependent system.
The last graph shows parallel lines. Parallel lines do not intersect and therefore do not have a solution. So this system is inconsistent.
Answer:
677
Step-by-step explanation:
There could be a strong correlation between the proximity of the holiday season and the number of people who buy in the shopping centers.
It is known that when there are vacations people tend to frequent shopping centers more often than when they are busy with work or school.
Therefore, the proximity in the holiday season is related to the increase in the number of people who buy in the shopping centers.
This means that there is a strong correlation between both variables, since when one increases the other also does. This type of correlation is called positive. When, on the contrary, the increase of one variable causes the decrease of another variable, it is said that there is a negative correlation.
There are several coefficients that measure the degree of correlation (strong or weak), adapted to the nature of the data. The best known is the 'r' coefficient of Pearson correlation
A correlation is strong when the change in a variable x produces a significant change in a variable 'y'. In this case, the correlation coefficient r approaches | 1 |.
When the correlation between two variables is weak, the change of one causes a very slight and difficult to perceive change in the other variable. In this case, the correlation coefficient approaches zero
We know that the load is 8713 lbs.
The total weight (truck + load) is 17200 lb.
Then, we can calculate the weight of the empty truck as:
Answer: the empty truck's weight is 8487 lb.
T: empty truck's weight
W: total weight (loaded truck's weight)
L: Load
The equation is:
T = W - L
