The vertex of the two functions is in the same place, so there is no translation involved. Point (0, 4) on f(x) is point (0, 12) on g(x).
The appropriate choice seems to be ...
<span>It is stretched vertically by a factor of 3.</span>
<span>(square root) -28
=</span><span>(square root) 4*-7
=2</span><span>(square root)-7
hope this helps</span>
Answer:
The regression line is not a good model because there is a pattern in the residual plot.
Step-by-step explanation:
Given is a residual plot for a data set
The residual plot shows scatter plot of x and y
The plotting of points show that there is not likely to be a linear trend of relation between the two variables. It is more likely to be parabolic or exponential.
Hence the regression line cannot be a good model as they do not approach 0.
Also there is not a pattern of linear trend.
D) The regression line is not a good model because there is a pattern in the residual plot.
Factor each
4k=2*2*k
18k⁴=2*3*3*k*k*k*k
12=2*2*3
GCF=2
the greatest common factor is 2
Answer:
"A Type I error in the context of this problem is to conclude that the true mean wind speed at the site is higher than 15 mph when it actually is not higher than 15 mph."
Step-by-step explanation:
A Type I error happens when a true null hypothesis is rejected.
In this case, as the claim that want to be tested is that the average wind speed is significantly higher than 15 mph, the null hypothesis has to state the opposite: the average wind speed is equal or less than 15 mph.
Then, with this null hypothesis, the Type I error implies a rejection of the hypothesis that the average wind speed is equal or less than 15 mph. This is equivalent to say that there is evidence that the average speed is significantly higher than 15 mph.
"A Type I error in the context of this problem is to conclude that the true mean wind speed at the site is higher than 15 mph when it actually is not higher than 15 mph."
