In three situations, a single force acts on a moving particle. Here are the velocities (at that instant) and the forces: (1) v → = (−4 i ^ ) m/s, F → = (6 i ^ − 20 j ^ ) N; (2) v → = (2 i ^ − 3 j ^ ) m/s, F → = (−2 j ^ + 7 k ^ ) N; (3) v → = (−3 i ^ + j) m/s, F → = (2 i ^ + 6 j ^ ) N. Rank the situations according to the rate at which energy is being transferred, greatest transfer to the particle ranked first, greatest transfer from the particle ranked last.
In three situations, a single force acts on a moving particle. Here are the velocities (at that instant) and the forces: (1) v → = (−4 i ^ ) m/s, F → = (6 i ^ − 20 j ^ ) N; (2) v → = (2 i ^ − 3 j ^ ) m/s, F → = (−2 j ^ + 7 k ^ ) N; (3) v → = (−3 i ^ + j) m/s, F → = (2 i ^ + 6 j ^ ) N. Rank the situations according to the rate at which energy is being transferred, greatest transfer to the particle ranked first, greatest transfer from the particle ranked last.
In three situations, a single force acts on a moving particle. Here are the velocities (at that instant) and the forces: (1)
v
→
= (−4
i
^
) m/s,
F
→
= (6
i
^
− 20
j
^
) N; (2)
v
→
= (2
i
^
− 3
j
^
) m/s,
F
→
= (−2
j
^
+ 7
k
^
) N; (3)
v
→
= (−3
i
^
+ j) m/s,
F
→
= (2
i
^
+ 6
j
^
) N. Rank the situations according to the rate at which energy is being transferred, greatest transfer to the particle ranked first, greatest transfer from the particle ranked last.
1. Measurements and Linear Regression
1.1 Introduction
The objective of this lab assignment is to represent measurement data in graphical form in order to
illustrate experimental data and uncertainty visually. It is often convenient to represent experimental
data graphically, not only for reporting results but also to compute or measure several physical
parameters. For example, consider two physical quantities represented by x and y that are linearly
related according to the algebraic relationship,
y=mx+b,
(1.1)
where m is the slope of the line and b is the y-intercept. In order to assess the linearity between y
and x, it is convenient to plot these quantities in a y versus x graph, as shown in Figure 1.1.
Datapoints
Line of
regression
Figure 1.1: Best fit line example.
Once the data points are plotted, it is necessary to draw a "best fit line" or "regression line" that
describes the data. A best fit line is a straight line that is the best approximation of the given set of
data, and…
Please help with Statistical Analysis table. These are trials from a Newton's Laws of Motion lab, please help with standard deviation and margin of error. Thanks!
please solve and answer the question correctly. thank you!!
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