Answer:
Component Form: v = <-1,6>
Magnitude of v: ||v|| = √37
Direction of v: θv = 100° (to the nearest degree)
Step-by-step explanation:
Component Form: v = <(5-6),(3-(-3))> = <-1,6>
Magnitude of v: ||v|| = √[(-1)²+(6)²] = √(1+36) = √37
Direction of v: α = tan⁻¹|6/-1| = tan⁻¹|-6| = tan⁻¹(6) = 80.53° which is your reference angle, but to verify that the angle is in the second quadrant, you'll need to do θv = 180° - 80.53° = 99.47°, therefore your direction angle is θv=100° to the nearest degree.
Answer: Aaron gets paid $19.10 per hour.
When you divide 152.80 by 8, you get 19.1 simplified. But in this case, it is in money so you need to put a 0 at the end.
Answer:
no, it's not.
Step-by-step explanation:
300- 284 = 16
284 - 236 = 48
236 - 156 = 80
156 - 44 = 112
for every one the top line goes up, the bottom line changes too, but it's not at a constant rate. it's not constant, therefore it cannot be linear.
the rate of change formula (or slope formula, they're the same thing) is :
y2- y1/ x2 -x1 and to solve it you plug in the points. x is the same a t and y is h
284-300/ 1-0
-16 /1
-16 (this is the rate of change between the first two points)
236- 284/ 2-1
-48/ 1
-48 (rate of change between the second and third points)
since the rate of change isn't constant, it's not possible for it to be a linear relationship.
Answer: See explanation
Step-by-step explanation:
1. Use the five steps of hypothesis testing.
Step 1: The aim of the research is to conduct the five steps of hypothesis testing.
Step 2:
Null hypothesis: H0 u= 4
Population mean: H1 u = 4
Alternate hypothesis: u ≠ 4
Population mean: u ≠ 4
Step 3 and step 4 are attached.
Step 5: Based on the calculation, the calculated value of t is less than the t critical value, therefore, the null hypothesis will be failed to be rejected.
2. Sketch the distributions involved
This has been attached.
3. Explain the logic of what you did to a person who is familiar with hypothesis testing, but knows nothing about t tests of any kind.
The distribution is "t".
The means is tested by using T-test.
Chi-square is used to test the single variance.
