The following data represent the time between eruptions and the length of eruption for 8 randomly selected geyser eruptions.
Time, x Length, y
12.16 1.87
11.73 1.80
11.99 1.87
12.17 1.89
11.28 1.64
11.68 1.74
12.24 1.90
11.57 1.71
11.74 1.78
(a) What type of relation appears to exist between time between eruptions and length of eruption?
A.
Linear, negative association
B.
Linear, positive association
Your answer is correct.
C.
A nonlinear pattern.
D.
No association.
(b) Does the residual plot confirm that the relation between time between eruptions and length of eruption is linear?
A.
Yes. The plot of the residuals shows a discernible pattern, implying that the explanatory and response variables are linearly related.
B.
No. The plot of the residuals shows that the spread of the residuals is increasing or decreasing, violating the requirements of a linear model.
C.
No. The plot of the residuals shows no discernible pattern, implying that the explanatory and response variables are not linearly related.
D.
Yes. The plot of the residuals shows no discernible pattern, so a linear model is appropriate.
Ans:
a)
Linear, positive association
b)
Yes. The plot of the residuals shows no discernible pattern, so a linear model is appropriate.
The following data represent the time between eruptions and the length of eruption for 8 randomly...
The following data represent the time between eruptions and the length of eruption for 8 randomly selected geyser eruptions. Complete parts (a) through (c) below. Click here to view a scatter plot of the data. Click here to view a residual plot of the data. Time, x 12.15 11.62 11.96 12.19 11.29 Length, y 1.86 1.74 1.81 1.93 1.67 Time, x 11.68 12.13 11.59 11.68 Length, y 1.78 1.85 1.75 1.71 (a) What type of relation appears to exist between...
Length, y The following data represent the time between eruptions and the length of eruption for 8 randomly selected geyser eruptions. Complete parts (a) through (c) below Click here to view a scatter plot of the data, Click here to view a residual plot of the data Time, x 12.14 11.75 12.02 12.11 11.29 1.88 1.72 1.86 1.87 1.65 Time, 11.66 12.19 11.61 11.66 Length, y 1.69 1.87 1.71 1.75 (a) What type of relation appears to exist between time...
The table below shows a sample waiting time between eruptions and the duration of the eruption of the old faithful geyser in Yellowstone National Park, Wyoming , USA Eruption 270 230 272 121 130 288 102 276 Waiting 81 74 82 60 52 76 59 88 1. compute the correlation and give an interpretation. 2 Use the least -squares regression line to predict the waiting times for the eruption lasting 222 seconds.
5. The data below represent duration times in seconds) of eruptions and time intervals (in minutes) to the next eruption for randomly selected eruptions of the Old Faithful geyser in Yellowstone National Park. Duration 242 255 227 251 262 207140 Interval After 91 81 91 92 102 94 91 a. Find the regression equation. b. Construct a residual plot for the data. Use the table below to guide you. y-9 Point on Plot Y c. Is a linear model appropriate...
Styles The data in the accompanying table represent the population of a certain country every 10 years for the years 1900-2000. An ecologist is interested in finding an equation that describes the population of the country over time. Complete parts (a) through (3) below Year, x 1900 1910 1920 1930 1940 1950 Population, y Year, x Population, y 179,323 203,302 79,212 1960 95,228 1970 104,021 1980 123,202 1990 132,164 2000 151,325 226,542 248,709 281,421 (a)Determine the least-squares regression equation, treating...
The following are 30 time lapses in minutes between eruptions of Old Faithful geyser in Yellowstone National Park, recorded between the hours of 8 a.m. and 10 p.m. on a certain day, and measured from the beginning of one eruption to the beginning of the next: 68, 63, 66, 63, 61, 44, 60, 62, 71, 62, 62, 55, 62, 67, 73, 72, 55, 67, 68, 65, 60, 61, 71, 60, 68, 67, 72, 69, 65, 66 A researcher wants to...
Help with coding in R: cyl<-factor(scan(text= "6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4")) am<-factor(scan(text= "1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 1 1 1 1 1 1 1")) ## 1)## Using the data `cyl` and `am` (transmission...
6). a.b.b. The data in the table to the right are based on the results of a survey comparing the commute time of adults to their score on a well-being test. Complete parts (a) through (d) below. Click the icon to view the critical values for the correlation coefficient. Commute Time (in minutes) Well-Being Score 5 69.5 16 68.9 27 67.5 34 67.4 47 66.9 68 65.9 97 63.9 (a) Which variable is likely the explanatory variable and which is...
(Just need help with part F) File_size_(MB) Time_(sec) 77 31.1 93 35.1 85 35.3 94 35.7 20 14.4 74 28.9 68 29.6 88 33.5 42 21.7 20 15.3 72 28.4 24 11.5 95 35.7 59 25.6 93 36.6 71 29.1 87 34.3 92 37.2 90 35.6 67 26.8 87 32.6 83 31.2 80 34.1 57 22.8 52 25.4 76 28.9 96 38.7 70 31.8 59 24.2 57 28.1 Before taking the plunge into videoconferencing, a company ran tests of its...
File_Size_(MB) Transfer_Time_(sec) 48 17.3 59 30.3 81 27.8 74 24.3 22 8.3 21 12.9 31 16.4 49 18.6 99 32.5 22 19.6 51 29.2 99 31.6 68 26.7 69 23.6 98 44.6 32 23.8 87 35.1 81 29.6 29 14.6 97 32.9 Before taking the plunge into videoconferencing, a company ran tests of its current internal computer network. The goal of the tests was to measure how rapidly data moved through the network given the current demand on the network....