Answer:
To find the x-intercept, make y equal to zero, and solve for x. To find the y-intercept, make x equal to zero, and solve for y.
Explanation:
<span>y=4x−2</span>
<span>
</span>
X-Intercept
<span>0=4x−2</span>
<span>
</span>
Add 2 to both sides of the equation.
<span>2=4x</span>
<span>
</span>
Divide both sides by 4.
<span><span>2/4</span>=x</span>
<span>
</span>
Simplify.
<span><span>1/2</span>=x</span>
<span>
</span>
Switch sides.
<span>x=<span>1/2</span></span>
<span><span>
</span></span>
Y-Intercept
<span>y=4<span>(0)</span>−2</span>
<span>y=−2</span>
Answer: a. 1.981 < μ < 2.18
b. Yes.
Step-by-step explanation:
A. For this sample, we will use t-distribution because we're estimating the standard deviation, i.e., we are calculating the standard deviation, and the sample is small, n = 12.
First, we calculate mean of the sample:


2.08
Now, we estimate standard deviation:


s = 0.1564
For t-score, we need to determine degree of freedom and
:
df = 12 - 1
df = 11
= 1 - 0.95
α = 0.05
0.025
Then, t-score is
= 2.201
The interval will be
± 
2.08 ± 
2.08 ± 0.099
The 95% two-sided CI on the mean is 1.981 < μ < 2.18.
B. We are 95% confident that the true population mean for this clinic is between 1.981 and 2.18. Since the mean number performed by all clinics has been 1.95, and this mean is less than the interval, there is evidence that this particular clinic performs more scans than the overall system average.
Answer:
do 24 points i know it very well
The final answer that i got from this was -x-13
Answer:
(2, 1.5)
Step-by-step explanation:
Outlier Definition: An outlier is defined as a data point that emanates from a different model than do the rest of the data.
The only one that stands out is (2, 1.5)
Answer: (2, 1.5)