A study of king penguins looked for a relationship between how deep the penguins dive to seek food and how long they stayunderwater. For all but the shallowest dives, there is a linear relationship that is different for different penguins. The study report gives ascatterplot for one penguin titled " The relation of dive duration (DD) to depth (D)." Duration DD is measured in minutes and depth D is in meters.The report then says, " The regression equation for this bird is: DD = 2.3 + 0.0021 D.%3D(a) What is the slope of the regression line?.ANSWERminutes per meter.(b) According to the regression line, how long does a typical dive to a depth of 400 meters last?ANSWERminutes.

Answered: Image /qna-images/answer/ae5447ea-2c29-4715-a539-a04f6daa1313.jpg

Answered: A study of king penguins looked for a…

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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On the first day of class, an economics professor administers a test to gauge the math preparedness of her students. She believes that the performance on this math test and the number of hours studied per week on the course are the primary factors that predict a student's score on the final exam. Using data from her class of 60 students, she estimates A portion of the regression results is shown in the following table. a. What is the slope coefficient of Hours? b. What is the sample regression equation? c. What is the predicted final exam score for a student who has a math score of 70 and studies 4 hours per week?
Imagine Daenerys Targaryen as a researcher concerned with the dragon species. The people of Westeros believed that dragons were decreasing in size due to captivity. Dragon size was normally measured as wingspan (meters) and captivity was normally measured in years. Daenerys used archival data and determined that the relationship between these two variables could be explained using the following regression equation: y-predicted = 453 - 2.5xInterpret this equation (i.e. What is its purpose? What is the intercept? What is the slope? What does it mean for dragons in Westeros?).
A real estate analyst believes that the three main factors that influence an apartment's rent in a college town are the number of bedrooms, the number of bathrooms, and the apartment's square footage. For 40 apartments, she collects data on the rent (y, in $), the number of bedrooms (x1), the number of bathrooms (x2), and its square footage (X3). The following table shows a portion of the regression results. ANOVA Significance df SS MS F F gression Residual 3 5694717 1898239 50.88 4.99E-13 36 1343176 37310 Total 39 7037893 Standard Upper 95% Coefficients Error t Stat p-value_Lower 95% Intercept 300 84.0 3.57 0.0010 130.03 470.79 Bed 226 60.3 3.75 0.0006 103.45 348.17 Bath 89 55.9 1.59 0.1195 -24.24 202.77 Sqft 0.2 0.09 2.22 0.0276 0.024 0.39 What would be the rent for a 1000-square-foot apartment that has 2 bedrooms and 2 bathrooms? $840 $1,335 $1,130 $1,260
The sweetness, y, of the fruit is supposed to be related to the average daily sunshine hours, x. The following data shows the sweetness of the same type of fruit at different locations (sunshine hours). Fit the data to a simple linear regression model. x: 5, 6, 7, 6, 6, 8, 7, 5. y: 9, 10, 10, 11, 12, 13, 12, 8. Predict the true mean sweetness for average daily hours of 8 hours, and calculate the residual for average daily sunshine hours of 8 hours.
We wants to assess the relationship between overall GPA (4.0 scale) and amount of time spent weekly on school work of 50 college students. Simple linear regression model is used and some results for the model is given: a) Is it plausible that the true intercept for the model is 2.0? Why or why not? (hint: using interval for intercept) b) If 2.0 is the real intercept for the model, does it make contextual sense? Explain why it is or why it is not. c) Using the model, calculate the number of hours needed to achieve a GPA of 4.0. Then explain why this estimate number of hours is biased. (hint: think about Y).
The systolic blood pressure dataset (in the third sheet of the spreadsheet linked above) contains the systolic blood pressure and age of 30 randomly selected patients in a medical facility. What is the equation for the least square regression line where the independent or predictor variable is age and the dependent or response variable is systolic blood pressure? Y=__________ X + ______________ Patient 7 is 67 years old and has a systolic blood pressure of 170 mm Hg. What is the residual? __________ mm Hg Is the actual value above, below, or on the line? What is the interpretation of the residual? (difference in actual &predicated bp, difference in age, the amount of systolic changes)
The applet displays a scatterplot with the following points: (7,10),(27,35),(24,25),(8,12),(10,19),(15,22). Identify the slope of the regression line, intercept of the regression line, and correlation coefficient. Report your answers accurate to within two decimal places.
A study of king penguins looked for a relationship between how deep the penguins dive to seek food and how long they stay underwater. For all but the shallowest dives, there is a linear relationship that is different for different penguins. The study report gives a scatterplot for one penguin titled, “The relation of dive duration (DD) to depth (D).” Duration DD is measured in minutes, and depth D is in meters. The report then says, “The regression equation for this bird is DD=2.69+0.0138D. (a) What is the slope of the regression line? (Enter your answer rounded to four decimal places.) slope = (b) On average, if the depth of the dive increases by one meter, what is the increase in the diving duration? (Enter your answer rounded to four decimal places.) increase in duration = minutes (c) According to the regression line, how long does a typical dive to a depth of 168 meters last? (Enter your answer rounded to three decimal places.) length…
Using a sample of recent university graduates, you estimate a simple linear regression using initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 3200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 64?
The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
Dr. Lillian Fok, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Fok has seen each year for the past 10 years. It also indicates what the robbery rate was in New Orleans during the same year. Year Number of Patients Robbery Rate per 1,000 Population The simple linear regression equation that shows the best relationship between the number of patients and the robbery rate is (round your responses to three decimal places) where y Number of Patients and x = Robbery Rate. = 1 2 3 4 6 7 36 33 40 41 55 60 58.3 61.1 73.4 75.7 81.1 89.0 101.1 5 40 8 54 94.8 9 58 103.3 10 61 116.2
Consumers are often interested in the fuel efficiency of the vehicles they choose to buy, so much so that they will research the various models they consider buying. Fuel efficiency can depend on a variety of variables. In this analysis, there are 73 automobiles that are popular with consumers. A regression analysis has been performed; the dependent variable is CityMPG (EPA miles per gallon in city driving), and independent variables are Length (vehicle length in inches), Width (vehicle width in inches), Weight (vehicle weight in pounds), and ManTran (1 if manual shift transmission, 0 otherwise). The level of significance is 0.05. Use the following MegaStat output to answer questions about this regression analysis. a. State the regression equation. b. How would CityMPG be affected if the width of a vehicle increased by an inch? c. Estimate the CityMPG for a vehicle with a length of 190 inches, a width of 75 inches, a weight of 4100 pounds, and a manual. Round your answer to the nearest…

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