14.Step 1:Global warming may be due to increased concentrations of greenhouse gases such as carbon dioxide (co2). Here are data from the National Oceanic and Atmospheric Administration Web site (www.noaa.gov),where co2 is measured in parts per million by volume:CO, 315.98 324.62 336.78 352.90 368.14 387.35Year 1959 19691979 1989 1999 2009A regression line for predicting carbon dioxide from time ispredicted carbon dioxide concentration =311.662 1.43866 x (years elapsed since 1959).(Fill in the blanks below and give your answers to 4 decimal places.)What is the slope of this line?(1)For each additional year the amount of carbon dioxide is increasing by(2)_ parts per million by volume.eBookAnswer 1Answer 2Continue

Introduction:In this case, the response variable is the carbon dioxide concentration, while the…

Answered: 14. Step 1: Global warming may be due…

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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We have measurements from eight companies for the % workforce change in 2010 from 2009 and the % change in profits from 2010 to 2011. % workforce change (x): 1.0 % profit change (y): 1.5 -0.4 -2.6 -3.8 -5.8 -2.5 -0.1 0.4 0.4 0.1 -0.2 -0.5 -7.5 0.2 0.3 We can calculate: Er = -12.7, Ex² = 64.51, Συ--6.8 , Σ 57, Σεy- 46.35. Find the sample correlation between the two variables, and fit a simple linear model to the dataset. Also, plot the residuals, ri, against xi, and comment on the fit of the model.
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. x days y km/100 71 76 31 92 203 14.2 19.6 5.8 11.2 35.9 (a) Verify that Ex = 473, Ey = 86.7, Ex = 61,451, Ey = 2033.69, Exy = 10995.7, and r 0.93868. %3D %3D %3D %3D Σχ 1 473 ΣΥ| 86.7 Ex2 61451 Ey2 2033.69 Exy 10995.7 r0.93868 (b) Use a 1% level of significance to test the claim p > 0. (Use 2 decimal places.) t 4.72 critical t 4.54 Conclusion Reject the null hypothesis, there is sufficient evidence that p > 0. O Reject the null hypothesis, there is insufficient evidence that p > 0. Fail to reject…
Question 2 A regression was run to determine if there is a relationship between hours of study per week (x) and the final exam scores (y). The results of the regression were: y=ax+b a=6.992 b=38.9 > r²=0.779689 r=0.883 Use this to predict the final exam score of a student who studies 4 hours per week, and please round your answer to a whole number.
1.
8.6 Cherry Trees: Timber yield is approximately equal to the volume of a tree, however, this value is difficult to measure without first cutting the tree down. Instead, other variables, such as height and diameter, may be used to predict a tree's volume and yield. Researchers wanting to understand the relationship between these variables for black cherry trees collected data from 31 such trees in the Allegheny National Forest, Pennsylvania. Height is measured in feet, diameter in inches (at 54 inches above ground), and volume in cubic feet. (Hand, 1994) Estimate Std. Error t value P(>|t|) (Intercept) -57.99 8.64 -6.71 0.00 height 0.34 0.13 2.61 0.01 diameter 4.71 0.26 17.82 0.00
4. Summary statistics for the data are shown in the table below. Меan Standard Deviation Iland, x 17.682 1.168 Foot, y 23.318 1.230 Pearson correlation r 0.948 (a) Find the slope by using the formula (b) Find the y-intercept by using the formula a = y – br (c) Find the regresssion equation, using the words "IHand" and "Foot," not r and y. (d) Using the regression equation, predict the foot length (in em) for someone who has a hand length of 18 cm.
7.24 Diamonds, Part I. Prices of diamonds are determined by what is known as the 4 Cs: cut, clarity, color, and carat weight. The prices of diamonds go up as the carat weight increases, but the increase is not smooth. For example, the difference between the size of a 0.99 carat diamond and a 1 carat diamond is undetectable to the naked human eye, but the price of a 1 carat diamond tends to be much higher than the price of a 0.99 diamond. In this question we use two random samples of diamonds, 0.99 carats and 1 carat, each sample of size 23, and compare the average prices of the diamonds. In order to be able to compare equivalent units, we first divide the price for each diamond by 100 times its weight in carats. That is, for a 0.99 carat diamond, we divide the price by 99. For a 1 carat diamond, we divide the price by 100. The distributions and some sample statistics are shown below.20 Conduct a hypothesis test to evaluate if there is a difference between the average standardized…
Part D. Data from the Statistical Abstract of the United States provides a panel data collected at the state level in 1987 and 1990. These data are used to estimate MODEL 1: The variables used in the analysis are: infmort is number of deaths within the year per 1,000 live births Ipcinc is natural log of per capita income Ipopul is natural log of the population (the population is in thousands) Iphysic is natural log of physicians per 100,000 inhabitants d90 is year dummy for 1990. For questions 1 to 4 you can assume that MLR 1-4 are satisfied. A 1. Use the Stata output below to interpret ß3. Test at a 5% significance level whether the number of physicians per capita has any effect on infant mortality rate. reg infmort 1pcinc 1popul 1physic d90 Source Model Residual Total infmort infmort = Po + B₁lpcinc + B₂lpopul + ß3lphysic + 8₁ d90 + u SS 78.0499129 350.452136 428.502049 df . 19.5124782 4 97 3.61290862 Coef. Std. Err. MS 101 4.24259454 1pcinc -4.693354 1.638132 1popul - .0551426…
Question 4 A company that focuses on research and development (R&D) is interested in the relationship between profit and some variables that can explain profit variations. They want to predict the profits of some new and exciting projects because some are risky. The predictor variables considered are: RISK which is a company derived metric, R&D which is the research and development costs, REGION (WC, EC and KZN) and average per capita income (INCOME in R1000.00). The analyst decides to estimate the regression function with the following response function. (profit) = bo + b₁XRISK + b₂XR&D + b₂XWc + b₁XEC + b₂XINC Answer the following questions. 4.1. The analyst considered the fact that the effects of multicollinearity may influence some analytical and visual conclusions. Use the following results to show the process of establishing by using extra sums of squares whether there is that multicollinearity present or not. Explain and interpret in detail. SSR (X) = 2573.72, SSR(x₁) = 2600.7,…
Algal blooms can have negative effects on an ecosystem by dominating its phytoplankton communities. Gonyostomum semen is a nuisance alga infesting many parts of northern Europe. Could the overall biomass of G. semen be controlled by grazing zooplankton species? A research team examined the relationship between the net growth rate of G. semen and the number of Daphnia magna grazers introduced in test tubes. Net growth rate was computed by comparing the initial and ﬁnal abundance of G. semen in the experiment, with a negative value indicative of a decrease in abundance. The table contains the findings. Number of D. magnagrazers 1 2 3 4 5 6 Net growth rate of G. semen -1.9 -2.5 -2.2 -3.9 -4.1 -4.3 Find the correlation, ?. Use decimal notation. (Enter your answer rounded to three decimal places.)
Question 38. You have performed a linear regression analysis to explore sunflowers' growth (in meters per month) depending on the watering (in litres per day). You have estimated the regression coefficient to be ß = 1.6. What can you conclude? a) There is a signifleant correlation between watering and growth. b) An average sunflower growths 1.6 meters per month. c) If you give it an additional litre of water per day, there will be an additional average growth of 1.6 meters per month. d) According to the model assumptions, an additional litre of water per day will result in additional 19.2 meters of growth after one year. e) You should consider further influencing quantities.
Please answer question b and c

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