The slope is the change in Y over the change in X
Slope = (-5 - -10) / (-2 - -9) = (-5+10) / (-2+9)
Slope = 5 / 7
Answer:
(2,9)
Step-by-step explanation:
To do this you have to solve one of the equations for a variable.
-x+y=7
2x+3y=31
Because the first equation doesn't have any numbers attached to the variables I decided to solve for the y in that equation.
-x+y=7
y=x+7
With this now one would have to plug this into the second equations:
2x+3(x+7)=31
Use the distributive property.
2x+3x+21=31
simplify.
5x+21=31
Isolate the x.
-21 -21
5x=10
solve for the x.
x=2
Plug the x into one of the equations and solve for y.
-x+y=7
-2+y=7
isolate the y.
+2 +2
y=9
This is the point of solution.
Answer:
<u>Photo Lab:</u>
<u>=3.20x +8</u>
<u>Specialty Photos:</u>
<u>=2.60x + 10</u>
Step-by-step explanation:
At the Photo Lab, the cost is $3.20 per roll plus 8 per print.
Therefore, the cost of developing a roll of film is:
<u>=3.20x +8</u>
At Specialty Photos the cost is $2.60 per roll plus 10 per print.
Therefore, the cost of developing a roll of film is:
<u>=2.60x + 10</u>
The picture of how the graph looks like is shown in the picture.
Part A. The correlation coefficient, R², is the quantitative evaluation of how the data points are well-fitted to a model. The closer it is to 1, the better. But a R²=1 is very ideal and rare. This can be only true if the points coincides exactly with the given model. Since we can see in the graph that the points are exaclty passed through by the linear model, the correlation coefficient is 1.
Part B. The slope of the graph is measured between two points as Δy/Δx. So, between 1 to 4 hours, the slope is: (85-100)/(4-1) = -5. The slope represents the instantaneous rate of change of surface area with time. It is called instantaneous because the change was only between than interval, not the whole set of data. Also, the negative sign signifies that the trend is decreasing.
Part C. The data represents causation if the time was the cause of the change of the pond's surface area. However, this is not technically true because there might be other factors to be considered like environmental conditions. But, definitely, these data are in correlation because together they show an observable trend.
Answer:
The data provide strong evidence that young men weigh more on average than old men in the U.S
Step-by-step explanation:
Given :
The null hypothesis ; H0 : μ1 = μ2
The alternative hypothesis ; H1 : μ1 > μ2
T score = 5.3 ; Pvalue = < 0.0001
The decision region :
If Pvalue < α ; We reject the Null
If Pvalue > α ; We fail to reject the Null
When the α - level isn't stated, we usually assume a α - level of 5%
However, even at lower alpha level of 1% = 0.01 ;
The Pvalue < α
Hence, we can conclude that there is significant evidence that there is difference in the mean weight of young men and old men in the U.S