Suburban counties
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Consider the Categorical Variable County Classification with the following categories : Urban , Suburban Exurban , and Rural . The dependent variable in the Linear Regression is the percentage of the population under 18 years of age in decimal form . Suppose Urban is the excluded category . The coefficient on Suburban is 0.07 . The coefficient on Exurban is -0.002 . The coefficient on Rural is -0.12. What is the interpretation of the coefficient on Suburban ?
A. Suburban counties have a 7 percentage point higher population under 18 years of age compared to Urban counties
B. Suburban counties have a 7 percentage point higher population under 18 years of age compared to Rural counties
C. Urban counties have a 7 percentage point higher population under 18 years of age compared to Suburban counties
D. There no way to determine from these results how the percentage of the population under 18 years of age is different in different county classifications
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- The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 58 inches. Is the result close to the actual weight of 572 pounds? Use a significance level of 0.05. Chest size (inches) 46 57 53 41 40 40 Weight (pounds) 384 580 542 358 306 320 LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=nothing+nothingx (Round to one decimal place as needed.)A. run a simple regression- dependent variable is Weeks, independent variable is Age. B. run a multiple regression with dependent variable weeks and independent variable-age, married, head, manager and sales. C. Create the regular and standardized residual plots for both. Please show the tables when entering values of the regression for both the outputs and the scatter plots.The following are the intelligence quotients (IQ) and the grade point average (GPA) of incoming Grade 12 students. If a significant relationship exists between the variables, perform a regression analysis. What GPA will students A and B obtain if their IQs are 159 and 92, respectively? Support your answer with computations/tables and draw the corresponding scatter diagram. Student IQ GPA 1 153 94 120 87 108 89 135 93 97 85 110 86 155 95 126 88 122 86 10 94 84 23455 6 7 8 9은
- . Determine the regression equation using values you create for x and y for at least 10 pairs of data. Show the regression equation, correlation coefficient, and coefficient of determination. Then switch the x and y values for each data point. Based on that, again show the regression equation, correlation coefficient, and coefficient of determination. Discuss the similarities and differences between the results.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…The table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, yˆ=b0+b1x, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age Bone Density34 35745 34148 33160 32965 325 Step 3 of 6: Determine the value of the dependent variable yˆ at x=0.
- Two variables have a positive linear correlation. Is the slope of the regression line for the variables positive or negative? A. The slope is negative. As the independent variable increases the dependent variable also tends to increase. B. The slope is negative. As the independent variable increases the dependent variable tends to decrease. C. The slope is positive. As the independent variable increases the dependent variable also tends to increase. D. The slope is positive. As the independent variable increases the dependent variable tends to decrease.Compute the value of the correlation coefficient for the data obtained in the study of the number of absences and the final grade of the seven students in the statistics class. Student. Number of absences. Also, find the equation of the regression line for the given data? Student. Number of absences. Final grade% ---------------------------------------------------------------------------- A. 6 82 B 2 86 C. 15 43 D. 9 74 E. 12 58 F 5 90 G 8 78In a dataset, X is the independent variable, and Y is the dependent variable. Which of the following statement is correct? None of these Regression between X and Y determines the nature of the relationship between the variables. Regression between X and Y determines whether there exists any relationship between the variables. Correlation between X and Y determines the nature of the relationship between the variables.
- Which of the following statements is sensible? A 102.4% of the total variation in a football player's weight is accounted for, or explained by its linear regression with the time spent practicing football. B. The correlation coefficient between a car's length and its fuel efficiency is7 es per gallon. C. There is a very strong direct linear correlation (0.95) between amount of d od consumption and the brand of dog food. D. The correlation coefficient between the amounts of fertilizer used and quantity of beans harvested is 0.42. OD O A OBIs It Getting Harder to Win a Hot Dog Eating Contest?Every Fourth of July, Nathan’s Famous in New York City holds a hot dog eating contest. The table below shows the winning number of hot dogs and buns eaten every year from 2002 to 2015, and the data are also available in HotDogs. The figure below shows the scatterplot with the regression line. Year Hot Dogs 2015 62 2014 61 2013 69 2012 68 2011 62 2010 54 2009 68 2008 59 2007 66 2006 54 2005 49 2004 54 2003 45 2002 50 Winning number of hot dogs in the hot dog eating contest Winning number of hot dogs and buns Click here for the dataset associated with this question. (a) Is the trend in the data mostly positive or negative? Positive Negative (b) Using the figure provided, is the residual larger in 2007 or 2008?Choose the answer from the menu in accordance to item (b) of the question statement 20072008 Is the residual positive or…Body Fat. Where we considered the regression of percentage of body fat on nine body measurements: height, weight, hip, forearm, neck, wrist, triceps, scapula, and sup. Describe and discuss problems that could have arisen in the collection of the data for this regression analysis.
