1. Borden Road Music is producing CDs for five (5) artists, Sarah D, Tom Boy, Uber Lyft, Vinny Joe, and Wanda, and X-terra. Borden Road Music makes the following unit profits on each artist’s CD as follows
|
Artist |
Sarah D |
Tom Boy |
Uber Lyft |
Vinny Joe |
Wanda |
|
Profit/CD |
$0.58 |
$0.43 |
$0.25 |
$0.17 |
$0.28 |
Each artist needs recording studio time and mastering studio time. There are 10,000 Minutes of available mastering time and 25,000 minutes of available recording time.
|
Artist |
Sarah D |
Tom Boy |
Uber Lyft |
Vinny Joe |
Wanda |
|
Recording/CD |
52 |
48 |
40 |
60 |
75 |
|
Mastering/CD |
28 |
24 |
18 |
12 |
5 |
Each artists CD must be packaged after production. There is 2,000 minutes of packaging time.
|
Artist |
Sarah D |
Tom Boy |
Uber Lyft |
Vinny Joe |
Wanda |
|
Package/CD |
1.5 |
1.25 |
1.0 |
0.75 |
1.5 |
Each artist will need promotion time. There are only 50,000 minutes of promotional time available.
|
Artist |
Sarah D |
Tom Boy |
Uber Lyft |
Vinny Joe |
Wanda |
|
Time/CD |
25 |
15 |
10 |
5 |
1 |
Marketing has the following consumer behavior information:
i. There are already 200 copies of Uber Lyft CDs pre-ordered.
ii. There are already 100 copies of Vinny Joe CDs pre-ordered.
iii. For every 2 Sarah D CDs sold there is a Tom Boy CD sold.
As a quality control measure Wanda CDs cannot exceed half of the other CDs produced.
a. Formulate the standard form of Borden Road Music’s linear program in the table below.
b. Use excel to solve the linear program and attach the Solution worksheet, the Sensitivity Analysis worksheet.
c. What happens to Borden Road’s profits if they gain 100 minutes of Mastering time?
Profits: .
d. What happens to Borden Road’s profits if they lose 100 minutes of recording time?
Profits: .
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Objective: |
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Constraints: |
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1: |
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2: |
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3: |
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4: |
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5: |
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6: |
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7: |
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8: |
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Non-negativity: |
In: Math
It is thought that prehistoric Indians did not take their best tools, pottery, and household items when they visited higher elevations for their summer camps. It is hypothesized that archaeological sites tend to lose their cultural identity and specific cultural affiliation as the elevation of the site increases. Let x be the elevation (in thousands of feet) for an archaeological site in the southwestern United States. Let y be the percentage of unidentified artifacts (no specific cultural affiliation) at a given elevation. Suppose that the following data were obtained for a collection of archaeological sites in New Mexico: x 5.50 6.25 6.75 7.25 7.50 y 9 38 38 50 72 What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares line?
Select one:
a. 89.9%
b. 10.1%
c. 94.8%
d. 0.3%
e. 1.0%
In: Math
Packer Fan Tours is the official tour company for the Green Bay Packers of the NFL. One of the events in the package is to sponsor a reception the night before a game for fans that is attended by 5 of the players from the team. There are 53 players on the Green Bay Packers' roster of which 22 are starters. Assume that the 6 players attending the reception this week are chosen randomly. Determine the probability of the following occurring: a. None of the players at the reception are starters. b. All of the players at the reception are starters. c. Two of the players at the reception are starters. d. Four of the players at the reception are starters.
In: Math
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. Construct and interpret a 95% prediction interval for the proceeds when the number of issues is
585.
The equation of the regression line is
ModifyingAbove y with caret equals 33.634 x plus 17 comma 224.539y=33.634x+17,224.539.
|
Issues, x |
404 |
453 |
679 |
483 |
479 |
394 |
50 |
73 |
175 |
175 |
|
|---|---|---|---|---|---|---|---|---|---|---|---|
|
Proceeds, y |
19,308 |
29,108 |
43,643 |
31,033 |
35,712 |
35,665 |
21,501 |
10,090 |
31,384 |
27,981 |
Construct and interpret a 95% prediction interval for the proceeds when the number of issues is
585.
Select the correct choice below and fill in the answer boxes to complete your choice.
(Round to the nearest million dollars as needed. Type your answer in standard form where "3.12 million" means 3,120,000.)
A.We can be 95% confident that when there are 585 issues, the proceeds will be between $____ and $____.
B.There is a 95% chance that the predicted proceeds given 585 issues is between $____ and $____.
In: Math
M12 Q9
What is the optimal time for a scuba diver to be on the bottom of the ocean? That depends on the depth of the dive. The U.S. Navy has done a lot of research on this topic. The Navy defines the "optimal time" to be the time at each depth for the best balance between length of work period and decompression time after surfacing. Let x = depth of dive in meters, and let y = optimal time in hours. A random sample of divers gave the following data.
| x | 16.1 | 26.3 | 31.2 | 38.3 | 51.3 | 20.5 | 22.7 |
| y | 2.68 | 2.18 | 1.48 | 1.03 | 0.75 | 2.38 | 2.20 |
(a) Find Σx, Σy, Σx2, Σy2, Σxy, and r. (Round r to three decimal places.)
| Σx | = |
| Σy | = |
| Σx2 | = |
| Σy2 | = |
| Σxy | = |
| r | = |
(b) Use a 1% level of significance to test the claim that
ρ < 0. (Round your answers to two decimal places.)
| t | = |
| critical t | = |
Conclusion
Fail to reject the null hypothesis. There is insufficient evidence that ρ < 0.
Reject the null hypothesis. There is sufficient evidence that ρ < 0.
Fail to reject the null hypothesis. There is sufficient evidence that ρ < 0.
Reject the null hypothesis. There is insufficient evidence that ρ < 0.
(c) Find Se, a, and b. (Round
your answers to five decimal places.)
| Se | = |
| a | = |
| b | = |
(d) Find the predicted optimal time in hours for a dive depth of
x = 22 meters. (Round your answer to two decimal
places.)
hr
(e) Find an 80% confidence interval for y when x
= 22 meters. (Round your answers to two decimal places.)
| lower limit | hr |
| upper limit | hr |
(f) Use a 1% level of significance to test the claim that
β < 0. (Round your answers to two decimal places.)
| t | = |
| critical t | = |
Conclusion
Fail to reject the null hypothesis. There is insufficient evidence that β < 0.
Reject the null hypothesis. There is sufficient evidence that β < 0.
Reject the null hypothesis. There is insufficient evidence that β < 0.
Fail to reject the null hypothesis. There is sufficient evidence that β < 0.
(g) Find a 90% confidence interval for β and interpret its
meaning. (Round your answers to three decimal places.)
| lower limit | |
| upper limit |
Interpretation
For a 1 meter increase in depth, the optimal time increases by an amount that falls within the confidence interval.
For a 1 meter increase in depth, the optimal time decreases by an amount that falls outside the confidence interval.
For a 1 meter increase in depth, the optimal time decreases by an amount that falls within the confidence interval.
For a 1 meter increase in depth, the optimal time increases by an amount that falls outside the confidence interval.
In: Math
1)With two-way ANOVA, the total sum of squares is portioned in the sum of squares for _______.
2) A _______ represents the number of data values assigned to each cell in a two-way ANOVA table. a)cell b) Block c)replication D)level
3.) True or false: In a two-way ANOVA procedure, the results of the hypothesis test for Factor A and Factor B are only reliable when the hypothesis test for the interaction of Factors A and B is statistically insignificant.
4.)Randomized block ANOVA partitions the total sum of squares into the sum of squares _______. A)between, within B)Between, within, block C)Between, Block, error D)Between,within, error
In: Math
You wish to test the following claim (HaHa) at a significance
level of α=0.005α=0.005. For the context of this problem,
μd=μ2−μ1μd=μ2-μ1 where the first data set represents a pre-test and
the second data set represents a post-test.
Ho:μd=0Ho:μd=0
Ha:μd>0Ha:μd>0
You believe the population of difference scores is normally
distributed, but you do not know the standard deviation. You obtain
pre-test and post-test samples for n=264n=264 subjects. The average
difference (post - pre) is ¯d=3.6d¯=3.6 with a standard deviation
of the differences of sd=20.4sd=20.4.
What is the test statistic for this sample? (Report answer accurate
to three decimal places.)
test statistic =
What is the p-value for this sample? (Report answer accurate to
four decimal places.)
p-value =
The p-value is...
This test statistic leads to a decision to...
As such, the final conclusion is that...
In: Math
The values of Alabama building contracts (in $ millions) for a
12‐month period follow: (19 marks total)
240 350 230 260 280 320 220 310 240 310 240 230
a. Construct a time series plot. What type of pattern exists in the
data?
b. Compare the three‐month moving average approach with the
exponential smoothing forecast using α=0.4. Which
approach provides more accurate forecasts based on MSE?
c. What is the forecast for the next month?
d. Explain how you would find the optimum level of α for this data.
Please answer this question at α=0.4. I have
submission deadline of 3 hrs. Also if possible please post the
solution typed.
In: Math
The Economic Policy Institute reports that the average entry-level wage for male college graduates is $22.07 per hour and for female college graduates is $19.85 per hour. The standard deviation for male graduates is $3.77 and for female graduates is $3.11. Assume wages are normally distributed. Question 1: If 25 females graduates are chosen, find the probability the sample average entry-level wage is at least $20.60.
In: Math
Data on the gasoline tax per gallon (in cents) as of a certain date for the 50 U.S. states and the District of Columbia are shown below.
| State |
Gasoline Tax per Gallon |
State |
Gasoline Tax per Gallon |
|---|---|---|---|
| Alabama | 20.1 | Missouri | 17.6 |
| Alaska | 8.0 | Montana | 27.9 |
| Arizona | 19.0 | Nebraska | 27.8 |
| Arkansas | 21.9 | Nevada | 33.3 |
| California | 48.4 | New Hampshire | 19.4 |
| Colorado | 22.0 | New Jersey | 14.2 |
| Connecticut | 42.4 | New Mexico | 18.9 |
| Delaware | 23.0 | New York | 44.1 |
|
District of Columbia |
23.2 | North Carolina | 30.5 |
| North Dakota | 23.0 | ||
| Florida | 34.7 | Ohio | 28.0 |
| Georgia | 20.1 | Oklahoma | 17.0 |
| Hawaii | 45.3 | Oregon | 25.0 |
| Idaho | 25.0 | Pennsylvania | 32.6 |
| Illinois | 40.7 | Rhode Island | 33.0 |
| Indiana | 34.9 | South Carolina | 16.9 |
| Iowa | 22.0 | South Dakota | 24.0 |
| Kansas | 25.0 | Tennessee | 21.7 |
| Kentucky | 22.2 | Texas | 20.0 |
| Louisiana | 20.0 | Utah | 24.2 |
| Maine | 31.0 | Vermont | 24.8 |
| Maryland | 23.2 | Virginia | 19.4 |
| Massachusetts | 23.2 | Washington | 37.2 |
| Michigan | 35.9 | West Virginia | 32.5 |
| Minnesota | 27.5 | Wisconsin | 32.1 |
| Mississippi | 18.9 | Wyoming | 14.0 |
How do you know if they are outliers? (Enter your answers to two decimal places.)
To be an outlier, an observation would have to be greater than? or less than?
Comment on the interesting features of the plot. (Round numerical answers to the nearest cent.)
The boxplot shows that a typical gasoline tax is around ___ cents per gallon
In: Math
In order to control costs, a company wishes to study the amount of money its sales force spends entertaining clients. The following is a random sample of six entertainment expenses (dinner costs for four people) from expense reports submitted by members of the sales force
| $ | 365 | $ | 309 | $ | 375 | $ | 379 | $ | 359 | $ | 373 | ||||||||||||
(a) Calculate x¯x¯ , s2, and s for the expense data. (Round "Mean" and "Variances" to 2 decimal places and "Standard Deviation" to 3 decimal places.)
| x¯x¯ | |
| s2 | |
| s | |
(b) Assuming that the distribution of
entertainment expenses is approximately normally distributed,
calculate estimates of tolerance intervals containing 68.26
percent, 95.44 percent, and 99.73 percent of all entertainment
expenses by the sales force. (Round intermediate
calculations and final answers to 2 decimals.)
| [x¯x¯ ± s] | [, ] |
| [x¯x¯ ± 2s] | [, ] |
| [x¯x¯ ± 3s] | [, ] |
(c) If a member of the sales force submits an entertainment expense (dinner cost for four) of $390, should this expense be considered unusually high (and possibly worthy of investigation by the company)? Explain your answer.
| No | |
| Yes |
(d) Compute and interpret the z-score for each of the six entertainment expenses. (Round z-score calculations to 2 decimal places. Negative amounts should be indicated by a minus sign.)
| z365 | |
| z309 | |
| z375 | |
| z379 | |
| z359 | |
| z373 | |
In: Math
Provide an example of how standard deviation is used to measure sports statistics (other than the examples in the book). Feel free to use an example outside of sports. (econ of sports)
In: Math
According to the National Center for Education Statistics, 69% of Texas students are eligible to receive free or reduced-price lunches. Suppose you randomly choose 285 Texas students. Find the probability that no more than 73% of them are eligible to receive free or reduced-price lunches.
In: Math
Based on historical data, your manager believes that 34% of the
company's orders come from first-time customers. A random sample of
122 orders will be used to estimate the proportion of
first-time-customers. What is the probability that the sample
proportion is greater than than 0.21?
Note: You should carefully round any z-values you calculate to 4
decimal places to match wamap's approach and calculations.
Answer = (Enter your answer as a number accurate to 4 decimal
places.)
Based on historical data, your manager believes that 32% of the
company's orders come from first-time customers. A random sample of
138 orders will be used to estimate the proportion of
first-time-customers. What is the probability that the sample
proportion is between 0.21 and 0.35?
Note: You should carefully round any z-values you calculate to 4
decimal places to match wamap's approach and calculations.
Answer = (Enter your answer as a number accurate to 4 decimal
places.)
In: Math
An investment advisor claimed that BIT return is 2%. Do you agree? Justify your reasoning using a two-tailed hypothesis test approach at the significance level of 5% in Excel.
| Date | Weekly Return BIT |
| 11/3/13 | 3.41913 |
| 18/3/13 | 85.71694 |
| 25/3/13 | 39.24392 |
| 1/4/13 | -18.7891 |
| 8/4/13 | 9.60467 |
| 15/4/13 | 14.06439 |
| 22/4/13 | -10.5122 |
| 29/4/13 | -4.83004 |
| 6/5/13 | 4.244539 |
| 13/5/13 | 13.56176 |
| 20/5/13 | -3.25568 |
| 27/5/13 | -16.1155 |
| 3/6/13 | 4.599688 |
| 10/6/13 | 3.554303 |
| 17/6/13 | -10.6242 |
| 24/6/13 | -12.8874 |
| 1/7/13 | 17.84908 |
| 8/7/13 | -16.0505 |
| 15/7/13 | -4.66321 |
| 22/7/13 | 8.641301 |
| 29/7/13 | 25.55278 |
| 5/8/13 | -17.0452 |
| 12/8/13 | 5.216139 |
| 19/8/13 | 44.93746 |
| 26/8/13 | -14.2551 |
| 2/9/13 | 8.63209 |
| 9/9/13 | -3.23257 |
| 16/9/13 | -0.70585 |
| 23/9/13 | -1.29504 |
| 30/9/13 | 8.221619 |
| 7/10/13 | 27.50873 |
| 14/10/13 | 10.52604 |
| 21/10/13 | 9.168265 |
| 28/10/13 | 41.7773 |
| 4/11/13 | 65.25601 |
| 11/11/13 | 78.13665 |
| 18/11/13 | 22.31184 |
| 25/11/13 | -14.7417 |
| 2/12/13 | 1.136502 |
| 9/12/13 | -23.938 |
| 16/12/13 | 13.72892 |
| 23/12/13 | 12.35955 |
| 30/12/13 | 3.8959 |
| 6/1/14 | -5.8598 |
| 13/1/14 | 2.343673 |
| 20/1/14 | -7.101 |
| 27/1/14 | -8.50278 |
| 3/2/14 | -12.9412 |
| 10/2/14 | -1.57162 |
| 17/2/14 | -10.7596 |
| 24/2/14 | 3.804612 |
| 3/3/14 | -0.77067 |
| 10/3/14 | -3.39044 |
| 17/3/14 | -13.4239 |
| 24/3/14 | -7.44464 |
| 31/3/14 | -8.356 |
| 7/4/14 | 19.4821 |
| 14/4/14 | -17.3626 |
| 21/4/14 | 7.070363 |
| 28/4/14 | -9.19229 |
| 5/5/14 | 12.03947 |
| 12/5/14 | 26.96418 |
| 19/5/14 | 16.04077 |
| 26/5/14 | -0.36004 |
| 2/6/14 | -10.4387 |
| 9/6/14 | 2.722898 |
| 16/6/14 | -3.62319 |
| 23/6/14 | -0.57143 |
| 30/6/14 | 4.679371 |
| 7/7/14 | -11.2723 |
| 14/7/14 | -2.16244 |
| 21/7/14 | 10.83316 |
| 28/7/14 | 3.278125 |
| 4/8/14 | -14.9456 |
| 11/8/14 | -7.17472 |
| 18/8/14 | -5.97974 |
| 25/8/14 | 5.36501 |
| 1/9/14 | 4.556442 |
| 8/9/14 | -24.5346 |
| 15/9/14 | 8.413437 |
| 22/9/14 | -23.2077 |
| 29/9/14 | 36.30293 |
| 6/10/14 | 0.811804 |
| 13/10/14 | -7.32571 |
| 20/10/14 | -6.68475 |
| 27/10/14 | 5.020247 |
| 3/11/14 | 5.211116 |
| 10/11/14 | -3.42055 |
| 17/11/14 | 5.224398 |
| 24/11/14 | 0.954401 |
| 1/12/14 | -11.8592 |
| 8/12/14 | 3.67537 |
| 15/12/14 | 1.951856 |
| 22/12/14 | -18.1888 |
| 29/12/14 | -3.50331 |
| 5/1/15 | -17.1584 |
| 12/1/15 | 65.68169 |
| 19/1/15 | -39.7557 |
| 26/1/15 | 6.946934 |
| 2/2/15 | 4.622242 |
| 9/2/15 | -0.12349 |
| 16/2/15 | 9.690883 |
| 23/2/15 | -0.98915 |
| 2/3/15 | 15.51773 |
| 9/3/15 | -13.8077 |
| 16/3/15 | 8.627292 |
| 23/3/15 | -15.6421 |
| 30/3/15 | 18.52383 |
| 6/4/15 | -3.9322 |
| 13/4/15 | -17.8082 |
| 20/4/15 | 8.226664 |
| 27/4/15 | -8.86103 |
| 4/5/15 | 16.59964 |
| 11/5/15 | -5.1213 |
| 18/5/15 | 12.93072 |
| 25/5/15 | -11.0606 |
| 1/6/15 | -2.52433 |
| 8/6/15 | -2.38066 |
| 15/6/15 | 4.075175 |
| 22/6/15 | 11.22781 |
| 29/6/15 | 22.47501 |
| 6/7/15 | -7.08553 |
| 13/7/15 | -2.4724 |
| 20/7/15 | 3.244106 |
| 27/7/15 | -12.7614 |
| 3/8/15 | -9.10397 |
| 10/8/15 | 8.645318 |
| 17/8/15 | -10.3851 |
| 24/8/15 | 9.069912 |
| 31/8/15 | -5.33967 |
| 7/9/15 | -2.2763 |
| 14/9/15 | 7.179764 |
| 21/9/15 | 1.206417 |
| 28/9/15 | -3.15691 |
| 5/10/15 | 9.994406 |
| 12/10/15 | 7.089126 |
| 19/10/15 | 19.41951 |
| 26/10/15 | 15.42842 |
| 2/11/15 | -14.4362 |
| 9/11/15 | 1.080991 |
| 16/11/15 | 8.702216 |
| 23/11/15 | 4.280561 |
| 30/11/15 | 12.00192 |
| 7/12/15 | 1.780459 |
| 14/12/15 | -5.68447 |
| 21/12/15 | 0.201301 |
| 28/12/15 | 10.27165 |
| 4/1/16 | -13.6904 |
| 11/1/16 | 3.543327 |
| 18/1/16 | -7.20309 |
| 25/1/16 | -0.59897 |
| 1/2/16 | 7.113843 |
| 8/2/16 | 7.505511 |
| 15/2/16 | -0.48063 |
| 22/2/16 | -9.66077 |
| 29/2/16 | -0.79917 |
| 7/3/16 | 7.520833 |
| 14/3/16 | 0.922022 |
| 21/3/16 | -0.70342 |
| 28/3/16 | -5.14834 |
| 4/4/16 | 3.467952 |
| 11/4/16 | 7.176527 |
| 18/4/16 | -4.52944 |
| 25/4/16 | 11.48942 |
| 2/5/16 | -2.0126 |
| 9/5/16 | -4.65557 |
| 16/5/16 | 14.44635 |
| 23/5/16 | 12.46595 |
| 30/5/16 | 14.50507 |
| 6/6/16 | 16.60521 |
| 13/6/16 | -13.9974 |
| 20/6/16 | -0.94628 |
| 27/6/16 | -2.84702 |
| 4/7/16 | 2.692938 |
| 11/7/16 | -0.16648 |
| 18/7/16 | -7.87224 |
| 25/7/16 | -4.28217 |
| 1/8/16 | -4.75042 |
| 8/8/16 | 1.265823 |
| 15/8/16 | 1.315789 |
| 22/8/16 | 5.922075 |
| 29/8/16 | -0.19617 |
| 5/9/16 | 2.578623 |
| 12/9/16 | -5.84318 |
| 19/9/16 | 4.225384 |
| 26/9/16 | -0.46984 |
| 3/10/16 | 4.712041 |
| 10/10/16 | 0.822016 |
| 17/10/16 | 7.430719 |
| 24/10/16 | 0.089732 |
| 31/10/16 | 0.655629 |
| 7/11/16 | 7.36345 |
| 14/11/16 | 0.244868 |
| 21/11/16 | 2.123698 |
| 28/11/16 | 4.972315 |
| 5/12/16 | 2.883185 |
| 12/12/16 | 11.72844 |
| 19/12/16 | 11.76919 |
| 26/12/16 | -9.91675 |
| 2/1/17 | -11.9936 |
| 9/1/17 | 11.69143 |
| 16/1/17 | 1.237738 |
| 23/1/17 | 8.83441 |
| 30/1/17 | -0.46448 |
| 6/2/17 | 2.569548 |
| 13/2/17 | 12.90091 |
| 20/2/17 | 8.806797 |
| 27/2/17 | -2.43571 |
| 6/3/17 | -17.3931 |
| 13/3/17 | -6.21463 |
| 20/3/17 | 15.28401 |
| 27/3/17 | 9.501789 |
| 3/4/17 | -1.49303 |
| 10/4/17 | 5.961288 |
| 17/4/17 | 5.836195 |
| 24/4/17 | 23.28998 |
| 1/5/17 | 18.13655 |
| 8/5/17 | 10.24173 |
| 15/5/17 | 8.177288 |
| 22/5/17 | 12.87583 |
| 29/5/17 | 11.34152 |
| 5/6/17 | -7.72858 |
| 12/6/17 | -2.38377 |
| 19/6/17 | -4.58281 |
| 26/6/17 | 2.176345 |
| 3/7/17 | -26.5117 |
| 10/7/17 | 41.09562 |
| 17/7/17 | -0.33206 |
| 24/7/17 | 15.03765 |
| 31/7/17 | 30.97158 |
| 7/8/17 | -0.36442 |
| 14/8/17 | 6.062555 |
| 21/8/17 | 7.088966 |
| 28/8/17 | -11.6134 |
| 4/9/17 | -13.6557 |
| 11/9/17 | 0.703891 |
| 18/9/17 | 20.32222 |
| 25/9/17 | 5.785614 |
| 2/10/17 | 22.75064 |
| 9/10/17 | 6.741201 |
| 16/10/17 | 3.950253 |
| 23/10/17 | 20.87309 |
| 30/10/17 | -18.236 |
| 6/11/17 | 34.93625 |
| 13/11/17 | 15.00381 |
| 20/11/17 | 22.16785 |
| 27/11/17 | 41.00506 |
| 4/12/17 | 22.66562 |
| 11/12/17 | -27.117 |
| 18/12/17 | 0.58581 |
| 25/12/17 | 20.00694 |
| 1/1/18 | -16.7119 |
| 8/1/18 | -20.4455 |
| 15/1/18 | -4.64241 |
| 22/1/18 | -29.2092 |
| 29/1/18 | 1.534346 |
| 5/2/18 | 28.46779 |
| 12/2/18 | -7.77999 |
| 19/2/18 | 20.02501 |
| 26/2/18 | -17.7474 |
| 5/3/18 | -12.3261 |
| 12/3/18 | 3.684747 |
| 19/3/18 | -19.9581 |
| 26/3/18 | 3.331936 |
| 2/4/18 | 16.69075 |
| 9/4/18 | 6.597227 |
| 16/4/18 | 9.470194 |
| 23/4/18 | 2.009693 |
| 30/4/18 | -8.8514 |
| 7/5/18 | -2.0897 |
| 14/5/18 | -13.8397 |
| 21/5/18 | 4.933133 |
| 28/5/18 | -12.4771 |
| 4/6/18 | -2.66984 |
| 11/6/18 | -5.32603 |
| 18/6/18 | 2.861289 |
| 25/6/18 | 5.472698 |
| 2/7/18 | -4.44636 |
| 9/7/18 | 16.2674 |
| 16/7/18 | 11.72963 |
| 23/7/18 | -13.9845 |
| 30/7/18 | -8.7872 |
| 6/8/18 | 2.301333 |
| 13/8/18 | 2.825531 |
| 20/8/18 | 9.907119 |
| 27/8/18 | -12.6849 |
| 3/9/18 | 2.912837 |
| 10/9/18 | 0.6556 |
| 17/9/18 | 0.235353 |
| 24/9/18 | 1.36778 |
| 1/10/18 | -5.70931 |
| 8/10/18 | 3.087778 |
| 15/10/18 | 0.156903 |
| 22/10/18 | -1.22667 |
| 29/10/18 | -0.75856 |
| 5/11/18 | -14.2755 |
| 12/11/18 | -28.2834 |
| 19/11/18 | 2.779471 |
| 26/11/18 | -12.0244 |
| 3/12/18 | -9.65332 |
| 10/12/18 | 26.02761 |
| 17/12/18 | -2.50028 |
| 24/12/18 | 4.221579 |
| 31/12/18 | -13.6894 |
| 7/1/19 | 1.104282 |
| 14/1/19 | -0.40807 |
| 21/1/19 | -4.2057 |
| 28/1/19 | 8.408738 |
| 4/2/19 | -0.95726 |
| 11/2/19 | 2.572986 |
| 18/2/19 | 2.418486 |
| 25/2/19 | 4.027091 |
| 4/3/19 | 1.283677 |
| 11/3/19 | -0.15854 |
| 18/3/19 | 2.14614 |
| 25/3/19 | 26.41332 |
| 1/4/19 | -0.53834 |
| 8/4/19 | 3.085379 |
| 15/4/19 | -0.4304 |
| 22/4/19 | 9.657475 |
| 29/4/19 | 22.68234 |
| 6/5/19 | 19.29905 |
| 13/5/19 | 6.162498 |
| 20/5/19 | -0.0825 |
| 27/5/19 | -12.8747 |
| 3/6/19 | 18.0031 |
| 10/6/19 | 20.14936 |
| 17/6/19 | -2.52176 |
| 24/6/19 | 7.825277 |
| 1/7/19 | -10.4531 |
| 8/7/19 | 2.733494 |
| 15/7/19 | -7.74446 |
| 22/7/19 | 16.13422 |
| 29/7/19 | 5.607618 |
| 5/8/19 | -9.91204 |
In: Math