Answer:
Step-by-step explanation:
See attachment.
If both cyclists travel for the same time and speed, they will have travelled the same distance. Since one is headed north and the other east, we can see that the distance between them in one hour is the hypotenuse of a right triangle. Each leg has distance x. We can say x^2 + x^2 = (3)^2
2x^2 =1 8
x^2 = 9
x = 3
They both rode 3 miles.
the overhead, fixed costs, is $1000.
the variable cost is $200, so if she sells "x" tiles, then her costs is 200*x or 200x.
total costs then will just be C(x) = 200x + 1000.
namely both costs added together.
Revenue is just how much it's been taken in from the sales, since each tile is selling for $240, then the revenue is simply 240*x or just R(x) = 240x.
break even point is when those two guys equal each other
what if the cost for each tile were $220, 20 bucks more?
well, if the cost for each tile is $200, her break-even point is at 25 units, namely once she has sold 25 tiles, she's has lost nothing, has won nothing either, but hasn't lost anything.
if the cost is however $220 instead, her break-even point comes much later, at 50 units, so she'll have to sell more tiles in order to not have any losses, so she's worse off if the cost is more or course.
Answer:
Step-by-step explanation:
Hello!
a.
Using the data sets you have to analyze them as if they are two independent samples.
The hypotheses are:
H₀: μ₁=μ₂
H₁: μ₁≠μ₂
α: 0.05
Assuming that both data sets are from a normal distribution and both population variances, although unknown, are equal, the statistic to use is:
Sa= 2.12
The p-value for the two-tailed test is:
P(≤-0.875) + P(
≥0.875)= P(
≤-0.875) + (1 - P(
≤0.875))= 0.1965 + ( 1 - 0.8035)= 0.393
Since there is no significant level I determined it at 5%, comparing it to the p-value, the hypothesis test is not significant. Meaning that the difference between the population means of both groups is equal to zero.
b.
Considering the given data as a paired sample, you have to determine the variable difference to conduct the test:
Xd: the difference between X₁ and X₂
Before the sample mean and sample standard deviation you have to calculate the difference between the observations of group 1 and group 2. (2nd attachment)
Mean X[bar]d= -0.83
Standard deviation Sd= 1.28
The hypotheses for the paired sample test are:
H₀: μd=0
H₁: μd≠0
α: 0.05
The p-value for the two-tailed test is:
P(≤-2.05) + P(
≥2.05)= P(
≤-2.05) + (1 - P(
≤2.05))= 0.0353 + (1 - 0.9647)= 0.0706
Comparing the p-value with the significance level, the hypothesis test is not significant. Meaning that the population mean of the difference between group 1 and group 2 is equal to cero. There is no difference between the two groups.
c.
The value of the statistic in "a" is greater than the value of the statistic obtained in "b". Since there are two samples used an "a" the degrees of freedom of the test are the double as the ones used in "b". The p-value obtained in "b" is around half of the p-value of "a".
The main difference is that in "a" you compared two different samples but in "b" you compared two dependent samples when analyzing paired data the "effect of the individual" is removed from the equation.
I hope this helps!
