writing

NVCC Computer Game Ensuring the Continuity of A Program Questions

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I’m working on a c++ multi-part question and need the explanation and answer to help me learn.

Examine the code (after–and while–playing the game :)), answering the questions below.
Go to https://replit.com/@rammonsnova/Pong#main.cpp and make your own forked copy.
Questions:

What are the user game controls/keys?
What’s the refresh interval for updating/redrawing the game?
Explain how the Paddle class works, including as many details as you think necessary for someone with very minimal understanding of coding.
Do the same for the Ball class.
How does the game continue to run even when no keys are pressed? How does it detect a key press?
Pick one part of the code that interests you; state what it is and WHY you find it interesting.

NVCC Computer Game Ensuring the Continuity of A Program Questions

BIO 182 ASU The Baby Frogcats Decline at Wildlife Sanctuary Questions

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DescriptionLab Instructions: Community Ecology Act I Mission Memo
Greetings Fellow Explorer:
If I were programmed to feel human emotions, I would be saddened to deliver this
news: the condition of the baby frogcats has worsened since you left the Intergalactic
Wildlife Sanctuary. These creatures need your help.
While I focus my processors on monitoring the health of these frogcats, you must
analyze the data and determine the most likely cause of the frogcats’ illness. Use the
following questions to guide your work.
● Are the frogcats infected or poisoned?
● Why have boreblasters dispersed to a new habitat?
The appendices to this mission memo will guide you in answering these questions.
Once you have completed your analyses, report your conclusions to me before
returning to the sanctuary.
My processors can handle 32,941 different means of transmitting data, but apparently
your university only supports one of these means—I believe you call this Canvas.
Therefore, I prepared a standard form for entering your report in Canvas.
Do not underestimate the urgency of your work.
Universally in your debt,
The AI
Page 1
Appendix 1
Are the frogcats infected or poisoned?
Treating the baby frogcats depends on whether their illness results from an infection
caused by pathogens or a toxin ingested from the environment.
With the help of GUS, you measured several variables that could be used to infer
whether the illness resulted from an infection: 1) body temperature of the frogcat; 2)
concentration of immune cells in the blood; and 3) presence of pathogens in saliva. No
abnormal bacteria or viruses were detected in the frogcat saliva, but that does not rule
out an infection in another part of the body. We need to determine whether the body
temperatures or immune cell concentrations are abnormal; an abnormally high value of
both variables would indicate an infection.
Using the links in Canvas, download these data for sick frogcats:
● Body temperatures of sick frogcats (sample size = 6)
● Immune cell concentrations of sick frogcats (sample size = 6)
Additionally, I have provided you with a sample of body temperatures and immune cell
concentrations for healthy frogcats.
Using the links in Canvas, download these data for healthy frogcats:
● Body temperatures of healthy frogcats (sample size = 100)
● Immune cell concentrations of healthy frogcats (sample size = 100)
Step 1: Anticipate your analysis.
1. List three types of evidence that could support the claim that an organism has
been infected.
Lab testing involving blood tests, microscopic examinations etc.
Isolating culture and identifying infectious agents
symptoms
Page 2
2. What comparisons, if any, are needed to conclude whether the frogcats have
been infected? Here is another way to think about this question: How would you
know if an organism is infected, and to what would you need to compare
infected organisms?
It is vital to compare infected organisms to healthy or uninfected species to
determine whether an organism is infected. It is possible to identify variations or
anomalies that point to an infection with this comparison. To determine if the
frogcats have been infected, you would need to compare them to healthy
frogcats that have not been exposed to the potential source of infection. Any
deviations or irregularities that are consistent with an infection can be spotted by
keeping an eye on and analyzing a variety of characteristics, including behavior,
physical appearance, clinical symptoms, and laboratory test results.
3. To construct a sound argument, one must anticipate the evidence needed to
support a claim. To that end, there are two possible claims as to whether the
frogcats are infected: 1) yes, they are infected, or 2) no, they are not infected.
Select one of the variables that you sampled, either body temperature or
immune cell concentration. For that variable, complete the bar plots shown
below. One of the bar plots illustrates what one should observe if the sick
frogcats were infected. The other illustrates what one should observe if the sick
frogcats were NOT infected.
First, label your axes for both plots. The Y-axis has not been labeled, the X-axis
has been labeled.
Page 3
Next, draw the bar plot for what you predict the sick frogcats body temperature
or immune cell concentration (depending on which variable you write in the Yaxis). The bar plot for the healthy frogcats variable has been provided.
Step 2: Estimate the mean and standard deviation of each
variable.
Using the data for healthy frogcats, you must determine the expected value of each
variable, and the uncertainty about the expected value. In other words, you need to
answer the question, “What body temperature or immune cell concentration should one
expect to observe in a healthy frogcat?”
Admittedly, I was a little concerned about the crude analytical tools available to
humans, but I scanned your World Wide Web to learn that you can accomplish this task
with Microsoft Excel. Apparently, people on your planet use a mathematical function
called the normal probability distribution, which has a mean and a standard
deviation; not as advanced as some civilizations but probably sufficient
Be sure to examine a frequency distribution of the data before using the normal
probability distribution. We need to be sure the data meet the assumptions of this
model before using it to draw conclusions.
Once you are satisfied that a normal probability distribution describes the data well, use
the functions in Excel called average and stdev to estimate the mean and standard
deviation, respectively.
Variable 1: Body temperature
Directions: For question 4, download the Excel file, “Data: Body Temperatures of Sick
Frogcats,” containing body temperatures of sick frogcats (N = 6) and the Excel file,
“Data: Body Temperatures of Healthy Frogcats,” containing body temperatures of
healthy frogcats (N = 100). Use Excel for calculations, modeling, and graphing. Round
all calculated values to the nearest tenth of a decimal place. For example, if you
calculate the value as 3.8218, round to 3.8.
4. Create a plot of a frequency distribution (also known as a histogram) of the body
temperatures of healthy frogcats. This plot should follow the formatting
guidelines listed below.
Page 4
General
● Chart type: Histogram
● Quick layout: Layout 1
● Chart title: “Frequency distribution of body temperature (°C) of a healthy
frogcat”; Font size 18
● Y-axes title: “Frequency”; Font size = 18
● Y-axis numbers: Font size = 14
● X-axis title: “Body temperature (°C)”; Font size 18
● X-axis numbers: Font size = 14
Y-axis
● Bounds: minimum at 0, maximum at 30
● Units: major = 5, minor = Auto
● Tick marks: major only, outside
● Number: decimal places = 0
X-axis
● Tick marks: major only, outside
● Number: decimal places = 1
Bins (bars)
● Number of bins = 6
● Fill: Solid fill; color = grey
● Border: Solid line; color = black; width = 0.75
Legend
● There should be no legend
5. Based on the frequency distribution you created above, does a normal probability
distribution reasonably model the body temperature of a healthy frogcat?
6. Explain your answer to question 5. Be sure to discuss the assumptions of a
normal probability distribution and why, based on the frequency distribution,
these assumptions seem appropriate (or not) for modeling the body temperature
of a healthy frogcat.
Directions: Using a normal probability distribution, estimate the mean and standard
Page 5
deviation of the body temperature of a healthy frogcat for questions 7-8. Round all
calculated values to the nearest tenth of a decimal place. For example, if you calculate
the value as 3.8218, round to 3.8.
7. Mean =
8. Standard deviation =
Step 3: Determine whether observed values are higher
than expected.
Once you have a mean and standard deviation for each variable measured in healthy
frogcats, you must determine whether the sick frogcats have unusually high values of
either variable (body temperature and immune cell concentration).
Let’s consider how you would do this for one of the variables, body temperature. First,
review the normdist function of Excel. This function requires three pieces of data for a
variable: 1) an observed value, 2) the mean, and 3) the standard deviation. The values
are entered in Excel as follows:
=norm.dist(observed_value, mean, standard_deviation, TRUE)
The function returns the probability of observing a value less than the observed value.
For example, entering the following function in Excel:
=norm.dist(34.1, 29.7, 1.5, TRUE),
would return 0.9983 (or 99.83%), which equals the probability of observing a value less
than 34.1 when the mean equals 29.7 and the standard deviation equals 1.5.
In the normdist function, enter the body temperature of a sick frogcat as the observed
value but enter the mean and standard deviation of body temperature for healthy
frogcats. The function will return the probability (P) of a healthy frogcat having a body
temperature (y) less than () the body temperature of the sick
frogcat. Therefore, we must use the following relationship:
P(y > x) = 1 – P(y < x) where P(y > x) equals the probability of observing a value y that is greater than the
value x, and P(y < x) equals the probability of observing a value y that is less than the value x. Subtracting the value returned by the normdist function of Excel from 1.0 will yield the probability of observing a body temperature in a healthy frogcat that is greater than the body temperature of the sick frogcat. If this probability is less than 5%, we should conclude that the body temperature of the sick frogcat is much higher than expected for a healthy frogcat. This conclusion would support the hypothesis that the sick frogcat had been infected by a pathogen. Repeat this calculation for each of the body temperatures observed in the 6 sick frogcats to see whether any of these sick creatures had abnormal body temperatures. Then, repeat the entire process using the data for immune cell concentration to determine if any of the sick frogcats had an abnormally high number of immune cells. Directions: Use the normal probability distribution for the body temperature of healthy frogcats to answer questions 9-13. Be sure to use the rounded values of the mean and standard deviation reported as your answers to questions 7 and 8. Using unrounded values will yield incorrect answers. 9. If the frogcats were infected, would you expect the body temperatures of sick frogcats to be greater than, less than, or equal to the mean body temperature of a healthy frogcat? a. equal to b. greater than c. less than 10. Explain your answer to question 9. Specifically, why did you select the answer choice you did? As you write your answer, think back to your original answers to questions 1–3 at the beginning of this assignment. Page 7 11. Given the body temperature of a sick frogcat, which probability should you estimate to determine whether that frogcat was infected? a. the probability of observing a body temperature of a healthy frogcat that is less than the body temperature of the sick frogcat b. the probability of observing a body temperature in a healthy frogcat that is greater than the body temperature of the sick frogcat. c. the probability of observing a body temperature of a healthy frogcat that is equal to the body temperature of the sick frogcat. 12. Match each Excel function to the probability it returns; in other words match each probability (1 or 2) to the a function (a or b): 1) The probability of observing a value that is less than the observed value 2) The probability of observing a value that is greater than the observed value. a) = norm.dist(observered_value, mean, standard_deviation, TRUE) b) = 1 - norm.dist(observered_value, mean, standard_deviation, TRUE) 13. The table below lists the body temperatures of six sick frogcats. For each value, calculate the probability of observing a more extreme value (either less than or greater than, depending on your answer to question 9) in a healthy frogcat. Express your answer as a percentage (%). Round all calculated values to the nearest tenth of a decimal place. For example, if you calculate the value as 3.8218, round to 3.8. Individu al Body Temperature (°C) 1 31.4 2 34.2 3 31.9 4 30.3 Probability Page 8 5 31.2 6 34.0 Variable 2: Immune Cell Concentration Directions: For question 14, download the Excel file, “Data: Immune Cell Concentrations of Sick Frogcats,” containing immune cell concentrations of sick frogcats (N = 6) and the Excel file, “Data: Immune Cell Concentrations of Healthy Frogcats,” containing immune cell concentrations of healthy frogcats (N = 100). Use Excel for calculations, modeling, and graphing. Round all calculated values to the nearest whole number. For example, if you calculate the value as 213.8218, round to 214. 14. Create a plot of a frequency distribution (also known as a histogram) of the immune cell concentration of healthy frogcats. This plot should follow the formatting guidelines listed below. General ● Chart type: Histogram ● Quick layout: Layout 1 ● Chart title: “Frequency distribution of immune cell concentration (per microliter) of a healthy frogcat”; Font size 18 ● Y-axes title: “Frequency”; Font size = 18 ● Y-axis numbers: Font size = 14 ● X-axis title: “Immune cell concentration (per microliter)”; Font size 18 ● X-axis numbers: Font size = 14 Y-axis ● Bounds: minimum at 0, maximum at 35 ● Units: major = 5, minor = Auto ● Tick marks: major only, outside ● Number: decimal places = 0 X-axis ● Tick marks: major only, outside ● Number: decimal places = 0 Page 9 Bins (bars) ● Number of bins = 7 ● Fill: Solid fill; color = grey ● Border: Solid line; color = black; width = 0.75 Legend ● There should be no legend 15. Based on the frequency distribution you created above, does a normal probability distribution reasonably model the immune cell concentration of a healthy frogcat? 16. Explain your answer to question 15. Be sure to discuss the assumptions of a normal probability distribution and why, based on the frequency distribution, these assumptions seem appropriate (or not) for modeling the immune cell concentration of a healthy frogcat. Directions: Using a normal probability distribution, estimate the mean and standard deviation of the immune cell concentration of healthy frogcats to answer questions 1718. 17. Mean = 18. Standard deviation = Directions: Use the normal probability distribution for the immune cell concentrations of healthy frogcats to answer questions 19–22. 19. If the frogcats were infected, would you expect the immune cell concentration of Page 10 a sick frogcat to be greater than, less than, or equal to the mean immune cell concentration of a healthy frogcat? a. equal to b. greater than c. less than 20. Explain your answer to question 19. Specifically, why did you select the answer choice you did? As you write your answer, think back to your original answers to questions 1 - 3 at the beginning of this assignment. 21. Given the immune cell concentration of a sick frogcat, which probability should you estimate to determine whether that frogcat was infected? a. the probability of observing an immune cell concentration of a healthy frogcat that is less than the immune cell concentration of the sick frogcat b. the probability of observing an immune cell concentration in a healthy frogcat that is greater than the immune cell concentration of the sick frogcat. c. the probability of observing an immune cell concentration of a healthy frogcat that is equal to the immune cell concentration of the sick frogcat. 22. The table below lists the immune cell concentrations of six sick frogcats. For each value, calculate the probability of observing a more extreme value (either less than or greater than, depending on your answer to question 19) in a healthy frogcat. Express your answer as a percentage (%). Round all calculated values to the nearest whole number. For example, if you calculate the value as 213.8218, round to 214. Individua l Immune cell concentration (per microliter) 1 5981 2 7466 Probability Page 11 3 7282 4 4166 5 5512 6 6229 Step 4: Weigh the evidence and conclude whether frogcats were infected or poisoned. Once you have considered the possibility of infection, you should review the evidence that baby frogcats were poisoned by a toxin in their environment. Recall three pieces of evidence that we observed (in their order of observation): ● The toxicology screen of frogcat blood was positive for the presence of boreblaster toxin. ● The fecal sample from adolescent frogcat contained boreblaster exoskeletons. ● A swarm of long-winged boreblasters observed in the frogcat nesting grounds. Using this evidence, along with your analyses of the data in Goals 1 and 2 and the information about boreblasters in the Field Guide of Alluria, conclude whether the illness of baby frogcats resulted more likely from poisoning by boreblaster toxin than from infection by pathogens. Be sure to provide your reasoning, highlighting the relevant evidence supporting your claim. Directions: Recall the criteria for determining whether the sick frogcats are infected. A sick frogcat must have a body temperature or immune cell concentration that is extremely unlikely for a healthy frogcat. Specifically, the probability of observing a more extreme value in a healthy frogcat must be less than 5%. Use this information to help you answer questions 23–24. 23. Based on the data that you analyzed, select the claim that is better supported by the evidence. a. Yes, the frogcats are infected. b. No, the frogcats are not infected. Page 12 24. Summarize the evidence that supports your claim in question 23, including how you determined whether the sick frogcats were infected based on probability. Be sure to compare the body temperatures and immune cell concentrations for sick frogcats to those for healthy frogcats. Use quantitative evidence when possible. Remember that an extremely unusual value is one whose probability of occurring in a healthy frogcat is less than 5%. Directions: Answer the following questions, 25–29, about whether the frogcats have been poisoned. 25. List one type of evidence that would support the claim that an organism has been poisoned. 26. List three observations that you made in the Intergalactic Wildlife Sanctuary that could help you to conclude whether the frogcats have been poisoned. 27. What comparisons, if any, are needed to conclude whether the frogcats have been poisoned? Here is another way to think about this question: how would you know if an organism has been poisoned, and what would you need to compare poisoned animals to? 28. Based on the data that you collected, select the claim that is better supported by the evidence. a. Yes, the frogcats are poisoned. b. No, the frogcats are not poisoned. Page 13 29. Summarize the evidence that supports your claim in question 28, including how you determined whether the sick frogcats were poisoned. Provide at least two pieces of evidence that support your claim. 30. Based on all of the data, is it likely that the frogcats have been infected AND poisoned? Select the claim that best answers this question. a. Yes, the frogcats are sick because they have poisoned and infected b. No, the frogcats are only sick because they have been infected c. No, the frogcats are only sick because they have been poisoned d. No, the frogcats are not sick because of poisoning or infection, there is likely another cause of their illness. 31. Summarize the evidence that supports your claim in question 30. Page 14 Page 15 Appendix 2 Why have boreblasters dispersed to a new habitat? Until now, boreblasters had never dispersed more than a short distance, and rarely left the forest in which they feed. Figure 1. A wingless boreblaster develops into a winged adult, which disperses to reproduce. An adult can have either small or large wings, which affects how far it disperses. Now, we know that two forms of boreblasters exist: 1) the typical orange form with small wings (shown in the Field Guide of Alluria), and 2) a new purple form with large wings (Figure 1). The new form seems to be better designed for dispersal. On your planet, Earth, many species disperse when their environment deteriorates. For example, a grasshopper develops into a dispersing form called a locust when crowded by other grasshoppers. Crowding indicates severe competition for food in the current environment, but dispersal could enable some individuals to find a new source of food. Similarly, dispersal could be triggered directly by a scarcity of food. The balance between the supply of and demand for food depends on the abundance of organisms in a food chain. To explore reasons why the boreblasters might have dispersed, you will need to construct a food chain that contains the boreblasters. Use the Field Guide of Alluria to learn which species the boreblasters eat and which species Page 16 eat the boreblasters. Then model this information as a food chain. Once you have a food chain containing bore blasters, hypothesize a top-down effect or a bottom-up effect on the abundance of boreblasters that might have triggered dispersal. Students will discuss the evidence needed to test each hypothesis. Directions: For question 32, construct a matrix showing the connections between predators and prey in the Allurian Forest community. In the matrix shown below, potential predators are listed in rows and potential prey are listed in columns. For each potential predator, place an “X” in the columns that reflect known species of prey (based on the Field Guide). Leave a cell blank if no evidence of predation exists in the Field Guide of Alluria. See the example below for how your table should appear and how you should interpret it. Example: In this example, there are three species of organisms in this community: bivalves, cownose rays, and shortfin mako sharks. Bivalves are at the bottom of the food chain, because they do not eat cownose rays or shortfin mako sharks. Cownose rays eat bivalves, likely making them primary consumers in this community. Shortfin mako sharks eat cownose rays, which makes them secondary consumers in this community. Potential Prey bivalves (scallops, clams, etc.) cownose ray shortfin mako shark bivalves (scallops, clams, etc.) Potential Predators cownose ray shortfin mako shark X X Page 17 32. In this matrix, there are three species of organisms from the Allurian community: boreblasters, spotted gliders, and umbrella trees. Potential Prey boreblasters spotted gliders umbrella trees boreblasters Potential Predators spotted gliders umbrella trees Directions: For question 33, construct a food chain illustrating the flow of energy between each of the species in the matrix that you constructed above. Boxes will represent each species in the community, and arrows will indicate the direction that energy flows, from species of prey to species of predators. See the example below. Example: Using the example matrix from above, I know that bivalves are at the bottom of this food chain because they do not appear to eat any of the other species in this community. So, I place their population at the bottom of the food chain - this means that energy will flow from this population to the species that eat them - in this case cownose rays. That means that I should draw an arrow pointing from bivalves to cownose rays - energy is flowing from bivalves to cownose rays. Hence why the cownose ray population are positioned where they are. Lastly, shortfin mako sharks exclusively eat cownose rays. So, I’ll again draw an arrow pointing from cownose rays to the shortfin mako sharks. The energy in the cownose ray populations is flowing to the shortfin mako sharks. Hence why I put the sharks where I did in this food chain. Note - I could draw this food chain horizontally or vertically - it would not matter. The common convention is to draw food chains vertically though, showing how energy Page 18 moves up through the food chain. Shortfin mako Cownose Bivalves 33. Use your matrix for species in the Allurian community to construct a food chain including boreblasters, spotted gliders, and umbrella trees. Directions: Use the food chain that you constructed and the Field Guide of Alluria to answer questions 34–41. 34. Hypothesize a top-down effect that could have either increased or decreased the abundance of boreblasters in the Allurian Forest, triggering the development of the purple, long-winged form that dispersed to a new habitat. 35. Explain how this top-down effect could have triggered the dispersal of boreblasters. Your answer should reference the causes of dispersal for species on Earth that the AI discussed in their mission memo. 36. What evidence would you need to collect to support your hypothesis about a top-down effect? Answer as specifically and thoroughly as you can. Page 19 37. Given the evidence you described in question 36, what observations would you expect to see to support your hypothesis about a top-down effect? 38. Hypothesize a bottom-up effect that could have either increased or decreased the abundance of boreblasters in the Allurian Forest, triggering the development of the purple, long-winged form that dispersed to a new habitat. 39. Explain how this bottom-up effect could have triggered the dispersal of boreblasters. Your answer should reference the causes of dispersal for species on Earth that the AI discussed in their mission memo. 40. What evidence would you need to collect to support your hypothesis about a bottom-up effect? Answer as specifically and thoroughly as you can. 41. Given the evidence you described in question 40, what observations would you expect to see to support your hypothesis about a bottom-up effect? Page 20 tree ID 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 Presence of a novel symbiont present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present present Growth rate of a tree (cm/d) 0.044 0.035 0.053 0.035 0.021 0.033 0.026 0.024 0.046 0.022 0.033 0.043 0.053 0.037 0.028 0.056 0.048 0.060 0.041 0.012 0.012 0.048 0.016 0.027 0.027 0.033 0.026 0.038 0.019 0.041 0.046 0.059 0.039 0.047 0.030 0.025 0.041 0.032 0.045 0.017 0.029 0.028 0.050 0.001 0.032 0.044 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 present present absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent 0.034 0.033 0.017 0.017 0.016 0.003 0.003 0.011 0.015 0.009 0.011 0.009 0.005 0.017 0.016 0.014 0.017 0.011 0.007 0.012 0.024 0.004 0.001 0.018 0.013 0.014 0.010 0.012 0.003 0.022 0.018 0.005 0.015 0.031 0.017 0.006 0.020 0.010 0.009 0.011 0.015 0.014 0.014 0.024 0.006 0.018 0.008 94 95 96 absent absent absent 0.008 0.000 0.029 The data in this sheet will be used for assignment questions 1-4. Use the Excel sheet (tab) labeled "Question 1" for all calculations, modeling, and graphing. tree Presence ID of a novel symbiont 1 present 2 present 3 present 4 present 5 present 6 present 7 present 8 present 9 present 10 present 11 present 12 present 13 present 14 present 15 present 16 present 17 present 18 present 19 present 20 present 21 present 22 present 23 present 24 present 25 present 26 present 27 present Dummy Code 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 28 present 1.000 29 present 1.000 30 present 1.000 31 present 1.000 32 present 1.000 33 present 1.000 34 present 1.000 35 present 1.000 36 present 1.000 37 38 39 40 41 42 43 present present present present present present present 1.000 1.000 1.000 1.000 1.000 1.000 1.000 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 present present present present present absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent absent 1.000 1.000 1.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 91 92 93 94 95 96 absent absent absent absent absent absent 0.000 0.000 0.000 0.000 0.000 0.000 0.050 0.045 0.040 Growth rate of a tree Growth rate of a tree (cm/d) 0.044 0.035 0.053 0.035 0.021 0.033 0.026 0.024 0.046 0.022 0.033 0.043 0.053 0.037 0.028 0.056 0.048 0.060 0.041 0.012 0.012 0.048 0.016 0.027 0.027 0.033 0.026 0.035 0.030 0.025 0.020 0.015 0.010 0.005 0.000 0.000 0.038 0.019 0.041 0.046 0.059 0.039 0.047 0.030 0.025 0.041 0.032 0.045 0.017 0.029 0.028 0.050 mean stdev slope intercept mean 0 mean 1 0.001 0.032 0.044 0.034 0.033 0.017 0.017 0.016 0.003 0.003 0.011 0.015 0.009 0.011 0.009 0.005 0.017 0.016 0.014 0.017 0.011 0.007 0.012 0.024 0.004 0.001 0.018 0.013 0.014 0.010 0.012 0.003 0.022 0.018 0.005 0.015 0.031 0.017 0.006 0.020 0.010 0.009 0.011 0.015 0.014 0.014 0.024 0.006 0.018 0.008 0.008 0.000 0.029 Growth rate of a tree (cm/d) y = 0.0221x + 0.0127 0.200 0.400 0.600 0.800 Presence of a novel symbiont 0.262 0.010343889 0.022085844 0.012687092 0.0127 0.0348 0.01 0.022 0.013 0.013 0.035 1.000 1.200 1.200 For questions 1-4, refer to the sheet (tab labeled “DATA- Growth of ruil trees ruil trees in the presence or absence of a 48 trees per treatment). Use this Excel sheet for calculations, mod calculated values to the nearest thousan example, if you calculate the value as 3.8 Refer to the lab packet document for spe instructions. r to the sheet (tab) in this Excel workbook h of ruil trees,” containing the growth rate of ce or absence of a novel symbiont (sample size = r calculations, modeling, and graphing. Round all e nearest thousandth of a decimal place. For te the value as 3.8218, round to 3.822. document for specific Excel formatting Soil moisture (%) Per capita rate of change (ruils/ruil/y) 15 20 25 30 35 40 45 50 0.005 0.017 0.022 0.026 0.020 0.036 0.021 4.154E-05 The data in Use the Ex modeling, The data in this sheet will be used for assignment questions 7-9. Use the Excel sheet (tab) labeled "Question 7" for all calculations, modeling, and graphing. Per capita rate of change (ruils/ruil/y) 0.040 0.030 0.020 0.010 y = -8E-05x2 + 0.0053x - 0.0582 0.000 -0.010 -0.020 -0.030 -0.040 0 10 20 30 40 50 60 Soil moisture (%) Per capita rate of change (ruils/ruil/y) 15 0.005 20 0.017 25 0.022 a 30 0.026 b 35 0.020 c 40 0.036 r 45 0.021 50 4.154E-05 29 24 a b c Per capita rate of change (ruils/ruil/y 0.040 0.030 0.020 0.010 0.000 -0.010 -0.020 -0.030 -0.040 2 y = ax + bx + c -0.00012 0.0088 -0.1372 r= (-0.00012)x2 + (0.0088)x- 0.1372 r=(-0.00012)(29^2 ) + (0.0088)(29) - 0.1372 0.017 (-0.00012)(242 ) + (0.0088)(24)- 0.1372 0.005 Per capita rate of change/ soil moisture Per capita rate of change (ruils/ruil/y 0.040 0.030 0.020 0.010 0.000 0 10 20 30 40 -0.010 -0.020 y = -8E-05x2 + 0.0053x - 0.0582 -0.030 -0.040 Soil moisture (%) 50 60 29 24 0.028 0.023 For questions 7-9, refer to the sheet (tab) labeled “DATA- Symbiont present capita rates of change for 8 populations o populations). Use this Excel sheet for calculations, mod calculated values to the nearest thousand example, if you calculate the value as 3.8 Refer to the lab packet document for spe instructions. r to the sheet (tab) in this Excel workbook ont present,” containing soil moistures and per or 8 populations of ruil trees (sample size = 8 calculations, modeling, and graphing. Round all e nearest thousandth of a decimal place. For te the value as 3.8218, round to 3.822. document for specific Excel formatting Year 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 Number of trees 20985 46 47 48 49 50 The data in this sheet will be used for assignment question Use the Excel sheet (tab) labeled "Question 13" for all calc modeling, and graphing. signment questions 12-13. " for all calculations, 0 20985 1 21467.66 2 21961.41 3 22466.52 4 22983.25 5 23511.87 6 24052.64 7 24605.85 8 25171.79 9 25750.74 10 26343 11 26948.89 12 27568.72 13 28202.8 14 28851.46 15 29515.05 16 30193.89 17 30888.35 18 31598.78 19 32325.56 20 33069.04 21 33829.63 22 34607.71 23 35403.69 24 36217.98 25 37050.99 26 37903.16 27 38774.94 28 39666.76 29 40579.09 30 41512.41 31 42467.2 32 43443.94 33 44443.16 34 45465.35 35 46511.05 36 47580.81 37 48675.16 38 49794.69 39 50939.97 40 52111.59 41 53310.16 42 54536.29 43 55790.62 44 57073.81 45 58386.51 46 59729.4 0.023 47 61103.17 48 62508.55 49 63946.24 50 65417.01 For questions 12-13, refer to the labeled “DATA- Ruil population the population at present (time change (r) equal to the per capit population of ruil trees when th moisture is 25%. Use this Excel sheet for calculati calculated values to the nearest calculate the value as 3.8215, ro 13, refer to the sheet (tab) in this Excel workbook Ruil population size,” containing the number of ruils in n at present (time = 0). Assume a per capita rate of ual to the per capita rate of change you estimated for a ruil trees when the novel symbiont is present and the soil sheet for calculations, modeling, and graphing. Round all ues to the nearest whole number. For example, if you value as 3.8215, round to 4. Purchase answer to see full attachment

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