How sensitive to changes in water temperature arecoral reefs? To find out, scientists examined data onsea surface temperatures and coral growth per yearat locations in the Gulf of Mexico and the CaribbeanSea. The table shows the data for the Gulf of Mexico.Sea surface temperatureGrowth26.7 26.6 26.6 20.85 0.85 0.79 0The correlation for this data is r = -0.8111.Which is the correct interpretation of this value?Coral growth is unrelated to the sea surfacetemperature.Coral growth is related to the sea surfacetemperature: as the temperature increases,Coral growth increases.Coral growth is related to the sea surfacetemperature: as the temperature increases,Coral growth decreases.Coral growth is related to the sea surfacetemperature, but in a non-linear way.

It is given that the two variables sea surface temperatures and coral growth per year at locations…

Answered: The correlation for this data is r =…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Similar questions

Shelia's doctor is concerned that she may suffer from gestational diabetes (high blood glucose levels during pregnancy). There is variation both in the actual glucose level and in the blood test that measures the level. A patient is classified as having gestational diabetes if the glucose level is above 140 milligrams per deciliter one hour after a sugary drink is ingested. Shelia's measured glucose level one hour after ingesting the sugary drink varies according to the Normal distribution with mean 128 mg/dl and standard deviation 9 mg/dl. Let ? denote a patient's glucose level. (a) If measurements are made on four different days, find the level ? such that there is probability only 0.01 that the mean glucose level of four test results falls above ? for Shelia's glucose level distribution. What is the value of ??ANSWER: (b) If the mean result from the four tests is compared to the criterion 140 mg/dl, what is the probability that Shelia is diagnosed as having gestational…
Below is a table showing the relationship between age and bone density of a typical healthy adult male. Age (years) 25 35 45 55 65 75 85 Bone density (mg/cm²) 1165 1135 1085 1060 1015 975 910 Using your line of best fit find the equation for this line. Describe the correlation between the two variables and what conclusions can you make from this set of data? Using graph plotted extrapolate to find the bone density of a 90 years old typical adult.
Ocean currents are important in studies of climate change, as well as ecology studies of dispersal of plankton. Drift bottles are used to study ocean currents in the Pacific near Hawaii, the Solomon Islands, New Guinea, and other islands. Let x represent the number of days to recovery of a drift bottle after release and y represent the distance from point of release to point of recovery in km/100. The following data are representative of one study using drift bottles to study ocean currents. 203 x days y km/100 72 76 32 14.7 94 11.7 19.5 5.3 35.6 (a) Verify that Ex = 477, Ey = 86.8, Ex? = 62,029, Ey2 = 2028.68, Exy = 11036.6, and r= 0.93853. Ex Ey Ex? Ey2| Exy (b) Use a 1% level of significance to test the claim p> 0. (Use 2 decimal places.) critical t Conclusion Reject the null hypothesis, there is sufficient evidence that p > 0. Reject the null hypothesis, there is insufficient evidence that p > 0. O Fail to reject the null hypothesis, there is insufficient evidence that p > 0. O…
A popular television show recently released a video previewing the upcoming season on his website as fans of the show discovered the video the number of views of the preview video has grown each day during the last two weeks the number of days in the release of the video and the natural log of the number of video views as shown in the scatterplot. based on the scatterplot and residual plot, what type of model would be appropriate for summarizing the relationship between days and numbers of views? an exponential model is appropriate because the Residual plot does not show a clear pattern A linear model is appropriate because of scatterplot shows a strong positive linear relationship A power model is appropriate because the scatterplot of days a natural log of use is strong and linear an exponential model is appropriate because the relationship between the days in the natural log of views in linear and the residual plot does not show a clear pattern
The correlation between a variable and itself is always equal to 0.5 -1 1
Summarize the definitions for linear correlation, quadratic correlations and exponential correlations. Provide an example graph of each of the types of correlation along with your summarized definitions.
For each pair of quantities, decide if the correlation coefficient would be close to 1, close to -1, or not be close to 1 or -1. Part: 0/4 Part 1 of 4 (a) The number of hours a student spends studying and the score on that student's exam. The correlation coefficient would be close to 1 Part: 1/4 Part 2 of 4 Part: 2/4 X (b) The number of hours a student spends studying and the number of letters in that student's name. The correlation coefficient would be close to -1 Part 3 of 4 X Ś X Ś (c) The number of hours an overweight person spends exercising and that person's weight. The correlation coefficient would be close to 1 5
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
Ocean currents are important in studies of climate change, as well as ecology studies of dispersal of plankton. Drift bottles are used to study ocean currents in the Pacific near Hawaii, the Solomon Islands, New Guinea, and other islands. Let x represent the number of days to recovery of a drift bottle after release and y represent The distance from point of release to point of recovery in km/100. The following data a representative of one study using drift bottles to study ocean currents. x day 72 79 32 96 203 y km/100 14.8 19.6 5.3 11.8 35.1 Σx=482 Σy=86.6 Σx2=62874 Σy2=2002.54 Σxy=11041.7 r=.93787 use a 1% level of significance to test the claim p>0.(use 2 decimal places) t=critical t= Se=4.4913 a=1.4966 b=.1641 D) find the predicted distance (km/100) when a drift bottle has been floating for 80 days.(use 2 decimal places) find a 90% confidence interval for your prediction of part D. (use 2 decimal places) lower limit=___km/100upper limit=___km/100 he was a 1% level of…
Determine if correlation between the two given variables is likely to be positive or negative, or if they are not likely to display a linear relationship. Your daily calorie intake and weight. (a) Positive (b) Negative (c) No correlation
How strong is this relationship? Obtain the correlation. (Provide your answer to four decimal places.) r=
Select the most appropriate response. If the correlation between a person’s age and annual income is 0.60, then the coefficient of determination tells us that: 36% of the variation in a person’s annual income can be explained by the predictor variable age. 36% of a person’s annual income can be explained by their age 60% of the variation in a person’s annual income can be explained by the predictor variable age 60% of a person’s annual income can be explained by their age

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