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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1. It has been noted that there is a positive correlation between the U.S. economy and the height of women's hemlines (distance from the floor of the bottom of a skirt or dress) with shorter skirts corresponding to economic growth and lower hemlines to periods of economic recession. Comment on the conclusion that economic factors cause hemlines to rise and fall. # of Absences (in weeks) Exam Grade 1 2 345 23 014 90 85 95 92 80
9. A wildlife researcher is interested in predicting a mammal’s lifespan (in years) based on its average number of hours of sleep per night. Data was obtained from a large random sample of mammals, and the regression equation turned out as follows: Predicted lifespan = 36.93 – 1.64 (average hours of sleep) Which one of the following statements is a correct interpretation of this equation? 1. Approximately 1.64% of the variability in lifespan can be explained by the regression equation. 2. As lifespan increases by one year, average hours of sleep is predicted to decrease by 1.64 hours. 3. As lifespan increases by one year, average hours of sleep is predicted to increase by 36.93 hours. 4. As average hours of sleep increases by one hour, lifespan is predicted to increase by 36.93 years. 5. As average hours of sleep increases by one hour, lifespan is predicted to decrease by 1.64 years.
QUESTION 5 Suppose you wish to see if there is a relationship between the price (units=$1000) and the rating (units-10 points) of laptop computers tested by Consumer Reports. A regression analysis on 14 computers revealed Ex₁ = 18.20, Ex² = 26.76, Eyi = 111.30, Ey2 = 894.19, and Exiyi = 149.60. What is the interpretation of B₁? Oa. None of the answers is correct b. For an increase of $1000 in price, the mean Consumer Report rating increases by 15.8387 points. OC. For an increase of 10 points in the Consumer Report rating, the mean price of a laptop increases by $158.3871. Od. For an increase of $1000 in price, the mean Consumer Report rating increases by 1.5839 points. Oe. For an increase of 10 points in the Consumer Report rating, the mean price of a laptop increases by $524.8530. QUESTION C ck Save and Submit to save and submit. Click Save All Answers to save all answers. F1 F2 20 F3 $ 000 000 F4 % S F5 MacBook Pro A 6 F6 & F7 DII * FB ∞
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 D and H please
1. Linear Trendlines (See this link for trendline help): Using the data set given in Excel Supplement Part 1, we want to show that the beam deflection, given in millimeters, is linearly dependent on the load, given in Newtons. This means deflection will be plotted as a function of load. In other words, the deflection will be measured along the y-axis and the load will be measured along the x-axis. a. Add a linear curve fit of the plotted data with the line going through the origin by adding a linear Trendline element to your chart and setting the intercept of that line to zero (i.e., make sure "Set Intercept" is selected and equal to 0). b. Display the linear trendline equation on the chart (i.e., “Display Equation on chart" is selected). Display the equation's slope to 3 decimal places (select Category: Number and Decimal places: 3). c. Make sure your chart's axes and title are appropriately labeled. Include units with your axis labels. Do not display a legend. For the Chart title,…
a. State the Pearson correlation trend between the two variables b. List the necessary steps to determine if there is a linear relationship between two variables.
The following table gives the regression results of consumption behaviour between female and male. Consumption (C), in RM Model 1 Model 2 Constant 0.7515 0.6587 (0.024) (0.037) Y 0.8603 0.5442 (0.0301) (0.2881) Gen 0.2001 (0.0004) Y*Gen 0.3105 (0.0076) Adjusted R 0.78 0.78 No. of Observations 47 47 Note: Y=income (RM) Gen= Gender ( It is equal to 1 if person is female; 0 is for male) Figures in the parentheses are p- values a) Identify which are the qualitative, quantitative and interaction variable. Refer to Model 1: b) Write the regression equations for female and male. Draw the regression lines for female and male on the same diagram. What can you c) say? d) Interpret all the estimated slope coefficients. e) Conduct an appropriate test to determine whether variable gender is statistically significant at 5%. Should this variable be dropped from this regression model.
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,…
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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, 315.98 324.62 336.78 352.90 368.14 387.35 1999 2009 Year 1959 1969 1979 1989 A regression line for predicting carbon dioxide from time is predicted carbon dioxide concentration = 311.6621.43866 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. eBook Answer 1 Answer 2 Step 2: (Fill in the blank below and give your answer to 4 decimal places.) Predict the carbon dioxide concentration for 2006. In fact, the observed value was 381.85 Since we treat 2006 as 47 years elapsing since 1959, the predicted carbon dioxide concentration is
QUESTION 1 Mr Stat was hired to do some research for the local potion master. He ran a Minitab analysis and found the regression equation for the age increase in years based on the quantity in milliliters, of Ageing Potion one consumed. Age Increase = 0.045*Quantity %3D a) What is the explanatory variable? Quantity b) What is the response variable? Age Increase Suppose the quantities in the st anged from 150ml to 740ml. If unable to predict, answer with n/a. c) How many years would someone's age increase if they drank 200ml? d) How many years would someone's age increase if they drank 100ml? n/a

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