Answer:
y = 5x + 20
Step-by-step explanation:
Here, we want to find the slope intercept form equation of the trend line
The general form is:
y =
mx + b
b is slope and m
is the y-intercept
b = 20
To get the slope, we select any two points and use the slope formula
we have the points;
(10,70) and (5,45)
The slope formula is;
m = (y2-y1)/(x2-x1) = (45-70)/(5-10) = -25/-5 = 5
The equation of the line is thus;
y = 5x + 20
Answer:
x = -3.25
Step-by-step explanation:
2/5 = 0.4
0.4x - 0.2 = -2(3/4)
-2(3/4) = -2/1 * 3/4 = -6/4
0.4x - 0.2 = -6/4
Convert to fraction
2/5x - 1/5 = -6/4
Add 1/5 to both sides
-6/4 + 1/5 = -30/20 + 4/20 = -26/20
2/5x = -26/20
Convert to decimal
0.4x = -1.3
-1.3/0.4 = -3.25
x = -3.25
Option B
The number of light years in
miles is 11508 light years
<em><u>Solution:</u></em>
Given that,
One light-year equals 5.9 x 10^12 miles
Therefore,

To find: Number of light years in
miles
Let "x" be the number of light years in
miles
Then number of light years in
miles can be found by dividing
miles by miles in 1 light year

Thus number of light years in
miles is 11508 light years
Answer: Horizontal
Step-by-step explanation: The equation <em>y = -2</em> can be thought of as y = 0x - 2. So our line has a slope of 0 and a y-intercept of -2.
To graph it, we start with the y-intercept, down 2 units on the y-axis. Now, if the slope of a line is 0, then the line must be flat or horizontal.
So we just draw a horizontal line through the y-intercept of -2.
In fact, when the equation of any line reads y = a number, it's graph will always be a horizontal line. For example, y = 3, y = -10, y = -8 and so on.
Image provided below.
Answer:
As the sample size increases, the variability decreases.
Step-by-step explanation:
Variability is the measure of actual entries from mean. The less the deviations the less would be the variance.
For a sample of size n, we have by central limit theorem the mean of sample follows a normal distribution for random samples of large size.
X bar will have std deviation as 
where s is the square root of variance of sample
Thus we find the variability denoted by std deviation is inversely proportion of square root of sample size.
Hence as sample size increases, std error decreases.
As the sample size increases, the variability decreases.