Could someone answer these questions (In Steps) Please
3. Remember that a phase difference of 2π radians/360° is equal to a path difference of one wavelength, λ. Therefore a phase difference of 90° (π/2) radians is equal to a path difference of λ/4.
5. R = ρL/A
Therefore R α 1/A (that is, resistance is inversely proportional to the cross-sectional area) provided that the length and resistivity of the wire remain constant.
Area of a wire = πr2 or A = πd2/4.
Therefore, if the diameter of the wire is doubled the area will increase by a factor of 4. Since R α 1/A, and area is 4 times greater, resistance must decrease by a factor of 4. Hence Rnew = 0.25R. Therefore the answer is A.
6. You have to find the total resistance of the resistors in series first.
Remember, for resistors in series Rtotal = R1 + R2 + ... + Rn
So to find the resistance of the two 4Ω resistors in parallel you just simply add the individual resistance of each resistor.
Rtotal = 4Ω + 4Ω = 8Ω
Now, you can think of the circuit as two 8Ω resistors in parallel. Remember, for resistors in parallel 1/Rtotal = 1/R1 + 1/R2 + ... + 1/Rn
So to find the resistance of the two 8Ω resistors in parallel you have to use the formula
1/Rtotal = 1/8 + 1/8 1/Rtotal = 2/8 = 1/4
So to find Rtotal you just take the reciprocal of both sides, so Rtotal = 4Ω.
Resistance is proportional to both length and area. R=ρAL
If the length increases the resistance also increases.
If the area increases, the resistance falls.
Because the cross sectional area of the wire is a square function of the diameter, if the diameter doubles, the c.s.a. increases by a factor of 4.
Hence for the same length, the resistance must fall by a factor of 4.
I don't understand your own definition of proportional. When the correlation is positive, we other say it is directly proportional, or we just say it is proportional. And when the correlation is negative, we categorically state that it is Inversely-proportional.
Be that as it may, the correct formulae speaks for itself and I'm sure the author of the incorrect formulae got my message square and clear.
And FYI, "rookie" mistakes are for a category of people.
And when did correcting critical mistakes become "criticism"?
Since the time of making the impression of being knowledgeable but ignoring to explain the question and yet waiting for correcting other's answers.
If you had the "courage" to scan through, you would have seen my earlier contribution. But of course, you decided to only attack as usual.
Contribution? I'm sure what you did was nothing more than looking at a mark scheme to which the original poster can/had access. But yeah, you can call it an attack as a sophistical excuse to undermine my point.
I don't understand your own definition of proportional. When the correlation is positive, we other say it is directly proportional, or we just say it is proportional. And when the correlation is negative, we categorically state that it is Inversely-proportional.
Be that as it may, the correct formulae speaks for itself and I'm sure the author of the incorrect formulae got my message square and clear.
And FYI, "rookie" mistakes are for a category of people.
Hello buddy. You were the one who stated proportional. I merely reflected your statement to make it easier for you to understand.
I don't understand your own definition of proportional. When the correlation is positive, we other say it is directly proportional, or we just say it is proportional. And when the correlation is negative, we categorically state that it is Inversely-proportional.
Be that as it may, the correct formulae speaks for itself and I'm sure the author of the incorrect formulae got my message square and clear.
And FYI, "rookie" mistakes are for a category of people.
Just going to float by and state that your terminology is wrong - the word correlation is almost meaningless here. 'Proportional to' typically means is "Is equal to some constant times". This would probably include whatever you mean by a negative correlation (which I'm assuming you mean a negative slope).
Inversely proportional would usually mean ∝A1. That's a hyperbola/reciprical relationship and is rarely what anyone means by "negative correlation".
As any good rookie knows, the more aloof your answer, the more likely it is to contain a mistkae
Just going to float by and state that your terminology is wrong - the word correlation is almost meaningless here. 'Proportional to' typically means is "Is equal to some constant times". This would probably include whatever you mean by a negative correlation (which I'm assuming you mean a negative slope).
Inversely proportional would usually mean ∝A1. That's a hyperbola/reciprical relationship and is rarely what anyone means by "negative correlation".
As any good rookie knows, the more aloof your answer, the more likely it is to contain a mistkae
"A negative correlation means that there is an inverse relationship between two variables - when one variable decreases, the other increases. The vice versa is a negative correlation too, in which one variable increases and the other decreases. These correlations are studied in statistics as a means of determining the relationship between two variables."
Y = -mx +c has a negative correlation relationship. Just as y = k/X does. Just as in statistics, it's not about how straight the line is but the scattered plot of any points drawn.
"A negative correlation means that there is an inverse relationship between two variables - when one variable decreases, the other increases. The vice versa is a negative correlation too, in which one variable increases and the other decreases. These correlations are studied in statistics as a means of determining the relationship between two variables."
Y = -mx +c has a negative correlation relationship. Just as y = k/X does. Just as in statistics, it's not about how straight the line is but the scattered plot of any points drawn.
Happy?
Well I'm somewhat happy that you proved my point. Y = -mx would be described as proportional, yet has a 'negative correlation', whilst Y = 1/x is inversely proportional and does not fit the nice pattern.
Moreover, nobody uses the term correlation if you're talking about a simple theoretical relationship - correlations are for experimental (statistical) data. Proportionality is a different concept, and trying to explain one in terms of the other won't work very well.