Mandalorian iron, also known by its Mando'a name of beskar, was an extremely durable iron ore whose only known source was the Outer Rim world of Mandalore and its moon, Concordia.
The battle at The Sarlacc Pit in The Return of the Jedi offers us a rare opportunity to study the composition of the rare and coveted mandalorian armor worn by Boba Fett. In this battle Boba Fett fell into the gaping maw of The Sarlacc, where he would be slowly digested over the course a thousand years. If the molarity of the HCl in The Sarlacc stomach is 0.15M, upon which, over the course of a thousand years, four tons (4000 Liters) is produced, we can then titrate the stomach acid after a thousand years and treat the iron content of the mandalorian armor as an antacid tablet containing a diprotic base, since:
Fe + 2 HCl(aq) -> Fe2+(aq) + 2 Cl-(aq) + H2(g)
If after 1000 years, it took 21.85 mL of 0.1337 M NaOH to neutralize a 25.00 mL sample of The Sarlacc’s stomach acid, what was the mass % of Iron in Boba Fett’s mandalorian armor.
The last known Imperial medical record reports Boba Fett’s mass as 78.12 kg. The last known sensor scan from Boba Fett’s ship, Slave I, reports 93.36 kg for Boba Fett with his armor on.
You may assume The Sarlaac eats only once a millenia since Jabba the Hutt’s death.
(Please assume that while Boba Fett escaped the Sarlacc Pit, his armor did not.)
In: Chemistry
"Durable press" cotton fabrics are treated to improve their recovery from wrinkles after washing. Unfortunately, the treatment also reduces the strength of the fabric. The breaking strength of untreated fabric is normally distributed with mean 52 pounds and standard deviation 1.8 pounds. The same type of fabric after treatment has normally distributed breaking strength with mean 24.1 pounds and standard deviation 1.8 pounds. A clothing manufacturer tests 3 specimens of each fabric. All 6 strength measurements are independent. (Round your answers to four decimal places.) (a) What is the probability that the mean breaking strength of the 3 untreated specimens exceeds 50 pounds? (b) What is the probability that the mean breaking strength of the 3 untreated specimens is at least 25 pounds greater than the mean strength of the 3 treated specimens?
In: Statistics and Probability
"Durable press" cotton fabrics are treated to improve their recovery from wrinkles after washing. Unfortunately, the treatment also reduces the strength of the fabric. The breaking strength of untreated fabric is normally distributed with mean 52.5 pounds and standard deviation 2.4 pounds. The same type of fabric after treatment has normally distributed breaking strength with mean 29.9 pounds and standard deviation 1.6 pounds. A clothing manufacturer tests 5 specimens of each fabric. All 10 strength measurements are independent. (Round your answers to four decimal places.) (a) What is the probability that the mean breaking strength of the 5 untreated specimens exceeds 50 pounds? (b) What is the probability that the mean breaking strength of the 5 untreated specimens is at least 25 pounds greater than the mean strength of the 5 treated specimens?
In: Math
9. We find the following information on NPNG (No-Pain-No-Gain) Inc. (18 marks total)
These numbers are projected to increase at the following supernormal rates for the next three years, and 5% after the third year for the foreseeable future:
The firm’s tax rate is 35%, and it has 1,000,000 outstanding shares and $6,000,000 in debt. We have estimated the WACC to be 15%.
b. Calculate the CFA* for each of the next four years, using the following formula:
d. Calculate the present value of growing perpetuity at
Year 3.
(1 mark)
e. Calculate the firm’s value at time 0 using the WACC of the firm as the discount rate. (Note that the first CFA* to be discounted is the cash flow from one year into the future.)
f. Calculate the firm’s equity value at time 0. (1 mark)
g. Calculate the firm’s share price at time 0. (1 mark)
In: Finance
Ponzi Products produced 80 chain-letter kits this quarter, resulting in a total cash outlay of $12 per unit. It will sell 40 of the kits next quarter at a price of $13, and the other 40 kits in the third quarter at a price of $14. It takes a full quarter for Ponzi to collect its bills from its customers. (Ignore possible sales in earlier or later quarters.) (Negative amount should be indicated by a minus sign.)
a. What is the net income for Ponzi next quarter?
b. What are the cash flows for the company this quarter?
c. What are the cash flows for the company in the third quarter?
d. What is Ponzi’s net working capital in the next quarter?
In: Finance
Consider the following time series.
| Quarter | Year 1 | Year 2 | Year 3 |
|---|---|---|---|
| 1 | 70 | 67 | 61 |
| 2 | 48 | 40 | 50 |
| 3 | 58 | 60 | 53 |
| 4 | 79 | 82 | 73 |
(b)Use the following dummy variables to develop an estimated regression equation to account for seasonal effects in the data:
x1 = 1 if quarter 1, 0 otherwise; x2 = 1 if quarter 2, 0 otherwise; x3 = 1 if quarter 3, 0 otherwise.
=
(c)Compute the quarterly forecasts for next year.
quarter 1 forecast___
quarter 2 forecast___
quarter 3 forecast___
quarter 4 forecast___
In: Statistics and Probability
Ponzi Products produced 88 chain-letter kits this quarter, resulting in a total cash outlay of $11 per unit. It will sell 44 of the kits next quarter at a price of $12, and the other 44 kits in the third quarter at a price of $13. It takes a full quarter for Ponzi to collect its bills from its customers. (Ignore possible sales in earlier or later quarters.) (Negative amount should be indicated by a minus sign.)
a. What is the net income for Ponzi next quarter?
b. What are the cash flows for the company this quarter?
c. What are the cash flows for the company in the third quarter?
d. What is Ponzi’s net working capital in the next quarter?
In: Finance
A statistical program is recommended.
Consider the following time series.
| Quarter | Year 1 | Year 2 | Year 3 |
|---|---|---|---|
| 1 | 72 | 69 | 63 |
| 2 | 49 | 41 | 51 |
| 3 | 59 | 61 | 54 |
| 4 | 77 | 80 | 71 |
Use the following dummy variables to develop an estimated regression equation to account for seasonal effects in the data:
x1 = 1 if quarter 1, 0 otherwise; x2 = 1 if quarter 2, 0 otherwise; x3 = 1 if quarter 3, 0 otherwise.
=
(c) Compute the quarterly forecasts for next year.
quarter 1 forecast
quarter 2 forecast
quarter 3 forecast
quarter 4 forecast
In: Statistics and Probability
In: Economics
You are conducting a study to determine if there is a relationship between annual household income and a high school student’s GPA. The school district you are studying is diverse and lower income. a) Before you conduct the study, do you expect there to be an association between these two variables? Why or why not? Which should be the explanatory variable? b) You collect data from a random sample of 15 students. The first row of the table is household income of a particular student (in thousands of dollars) and the second row is the GPA of that particular student. 42 30 82 19 29 44 90 55 17 62 51 30 9 39 42 3.1 2.6 3.8 2.7 2.3 3.5 3.8 3.2 2.4 3.3 3.1 2.8 1.6 3.4 3.2 c) Does the data have a scatterplot that shows a linear association? What is the correlation coefficient? What does it tell you about the association between these two variables? d) Use the above data to make a linear (regression) model. e) Use the model to predict the GPA of a high-schooler that comes from a family that has a household income of $48,000. f) How accurate is the model’s prediction of GPA for the family that makes $44,000? g) If a family’s income increases by $10,000, what is the amount of change in a student’s GPA, as predicted by the model? h) Statisticians often state “correlation is not necessarily causation.” Would it be correct to conclude that household income is “causing” GPA? Is it possible that there are other variables that are “lurking,” causing GPA and household income to be correlated? What might these variables be?
In: Statistics and Probability