You are conducting a test of independence for the daim that there is an association between the row variable and the column variable. xY z A 27 72 28 B 25 32 21 What is the chi-square test-statistic for this data? x² = [three decimal accuracy]
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![You are conducting a test of independence for the daim that there is an association between the row
variable and the column variable.
xY z
A 27 72 28
B 25 32 21
What is the chi-square test-statistic for this data?
x² =
[three decimal accuracy]](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fbd04cd21-8916-42c5-ae98-184766c0ea18%2Fcecd4d2b-87a0-4887-b0de-fd02103c0528%2Fubzpg_processed.png&w=3840&q=75)
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- A statistical program is recommended. A study of emergency service facilities investigated the relationship between the number of facilities and the average distance traveled to provide the emergency service. The following table gives the data collected. Average Number of Facilities Distance (miles) 1.67 11 1.11 16 0.82 21 0.62 27 0.50 30 0.47 (a) Develop a scatter diagram for these data, treating average distance traveled as the dependent variable. 1.8 1.8 35 1.8- 1.6 1.6 1.6 1.4 30 1.4 1.4 a 1.2 1.2 25 1.2 1. 1. E 1. 0.8 20 0.8 0.8- 0.6 0.6- 15 0.6- 0.4- 0.4- 0.4 0.2 10 0.2- 0. 5 0.2 10 15 20 25 30 35 0. 5 0. 10 15 20 25 30 35 0. 0.2 0.4 0.6 0.8 1. 1.2 1.4 1.6 1.8 10 15 20 25 30 35 Number Number Distance Number (b) Does a simple linear regression model appear to be appropriate? Explain. O Yes, the scatter diagram suggests that there is a linear relationship. O No, the scatter diagram suggests that there is a curvilinear relationship. O No, the scatter diagram suggests that there is…Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.941 and the least squares regression line is y = 0.244x + 10.794. Complete parts a and b below. Height, x Head Circumference, y 27.00 25.75 26.25 17.3 25.75 27.50 17.5 26.25 17.1 26.00 27.00 17.4 17.4 17.1 17.1 17.1 (a) Compute the coefficient of determination, R?. R2 =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. % of the variation in height is explained by the least-squares regression model. (Round to one decimal place as needed.)Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.883 and the least squares regression line is y = 0.134x + 13.693. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 27.75 25.25 26 25.25 27.25 26.75 26 27.25 27 27.25 26.75 17.1 17.3 17.0 17.4 17.2 17.2 17.3 17.3 17.4 17.3 ..... (a) Compute the coefficient of determination, R?. R? % (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. Approximately % of the variation in is explained by the least-squares gression model. (Round to one decimal place as needed.)
- The side effects of a new drug are being tested against a placebo. A random sample of 565 patients yields the results in the table below. At a significance level of a = to conclude that the treatment is not causing at least some of the side effects? Hint: Use the Placebo Column as the E, Side-Effect Headache Nausea 0.0465, is there enough evidence Drug Placebo 422 395 111 104 Fatigue Increased Depression 112 Increased Infections 331 354 84 28 13 (a) Find Ho and Ha (b) Find the critical value (c) Find the test value (d) Accept or rejection Hoo pis pe Suppose a doctor measures the height, x, and head circumference, y. of 11 children and obtains the data below. The correlation coefficient is 0.899 and the least squares regression line is y = 0.185x+ 12.276. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 17.1 17.2 16.9 17.4 17.1 17.1 17.3 17.3 17.3 17.4 27.75 25.75 26.75 25.75 28 26.5 25.75 26.75 27 27.25 27.25 (a) Compute the coefficient of determination, R?. R2 = % (Round to one decimal place as needed) (b) Interpret the coefficient of determination k Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. Enter your answer in each of the answer boxes. Save for Later DUE RTTT:DY PIVT Score: o:5SYO Tor Tv attempts 3:35 PA- a 2/22/202 Type here to search insert prt sc 4+ backsp %23 6. 8.Can movie rental revenue be predicted? A movie studio wishes to determine the relationship between the revenue from rental of comedies on streaming services and the revenue generated from the theatrical release of such movies. The studio has the following bivariate data from a sample of fifteen comedies released over the past five years. These data give the revenue x from theatrical release (in millions of dollars) and the revenue y from streaming service rentals (in millions of dollars) for each of the fifteen movies. Also shown are the scatter plot and the least-squares regression line for the data. The equation for this line is ŷ=3.38+0.15x. Theater revenue, x (in millions of dollars) Rental revenue, y (in millions of dollars) 21.0 5.5 60.9 10.0 61.0 16.0 27.5 3.1 36.7 12.7 30.6 5.7 14.8 2.0 49.6 15.7 13.1 10.2 25.9 8.9 44.1 6.5 66.9 9.5 27.5 11.8 24.9 7.9 6.9 1.5 Send data to calculator Send data to Excel Rental revenue (in millions of dollars) 18- 16+ x 14 12 10+ x 50 60 70…
- Please give answers of b&cI need #4 answeredSuppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.858 and the least squares regression line is y = 0.228x +11.187. Complete parts (a) and (b) below. Height, x 27.5 25.75 26.5 25.5 27.25 26.25 25.75 27.25 27 27.25 27 Head Circumference, y 17.4 17.2 17.2 16.9 17.6 17.1 17.1 17.4 17.4 17.3 17.3 (a) Compute the coefficient of determination, R². R² =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment on the adequacy of the linear model. Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. According to the residual plot, the linear model appears to be
- The Cadet is a popular model of sport utility vehicle, known for its relatively high resale value. The bivariate data given below were taken from a sample of sixteen Cadets, each bought new two years ago, and each sold used within the past month. For each Cadet in the sample, we have listed both the mileage x (in thousands of miles) that the Cadet had on its odometer at the time it was sold used and the price y (in thousands of dollars) at which the Cadet was sold used. The least-squares regression line for these data has equation Ŷ=42.80-0.53x. This line is shown in the scatter plot below. (The 2nd picture contains the rest of the data as it would not fit in the first pic and it includes the question as well.)A study of emergency service facilities investigated the relationship between the number of facilities and the average distance traveled to provide the emergency service. The following table gives the data collected. Average Distance Number of Facilities (miles) 1.65 11 1.12 16 0.83 21 0.62 27 0.50 30 0.47 (a) Develop a scatter diagram for these data, treating average distance traveled as the dependent variable. 1.8 - 35- 1.8 1.8 1.6 1.6 1.6- 30 1.4- 1.4 1.4 1.2- 25 1.2 1.2 1. 1. 1. 20 0.8 0.8 0.8 0.6- 15 0.6- 0.6 0.4- 0.4 0.4 10 0.2 0.2 0.2 0. 5 0.- 0. 10 15 20 25 30 35 0. 0.2 0.4 0.6 0.8 1. 1.2 1.4 1.6 1.8 10 15 20 25 30 35 10 15 20 25 30 35 Number Distance Number Number (b) Does a simple linear regression model appear to be appropriate? Explain. O No, the scatter diagram suggests that there is no relationship. No, the scatter diagram suggests that there is a curvilinear relationship. O Yes, the scatter diagram suggests that there is a linear relationship. (c) Develop an estimated…A study of emergency service facilities investigated the relationship between the number of facilities and the average distance traveled to provide the emergency service. The following table gives the data collected. Number of Facilities Average Distance (miles) 9 1.67 11 1.11 16 0.84 21 0.61 27 0.51 30 0.48 (a) Develop a scatter diagram for these data, treating average distance traveled as the dependent variable. CELL 0.2 0.4 0.6 0.8 1.2 1.4 1.6 1.8 Number Number Number Distance @ (b) Does a simple linear regression model appear to be appropriate? Explain. O Yes, the scatter diagram suggests that there is a linear relationship. O No, the scatter diagram suggests that there is no relationship. O No, the scatter diagram suggests that there is a curvilinear relationship. (c) Develop an estimated regression equation for the data of the form ý = b + b₁x + b₂x²: a second-order model with one predictor variable. (Round your numerical values to four decimal places.) ŷ =
