Question: The table shows data collected on the relationship between the time spent studying per day and the time spent reading per day. The line of best fit for the data is yˆ=0.16x+36.2. Assume the line of best fit is significant and there is a strong linear relationship between the variables. Studying (Minutes) 50,70,90,110 Reading (Minutes) 44,48,50,54 According to the line of best fit, what would be the predicted number of minutes spent reading for someone who spent 67 minutes studying? Round your answer to two decimal places.
Question: Michelle is studying the relationship between the hours worked (per week) and time spent reading (per day) and has collected the data shown in the table. The line of best fit for the data is yˆ=−0.79x+98.8. Assume the line of best fit is significant and there is a strong linear relationship between the variables. Hours Worked (per week) 30,40,50,60 Minutes Reading (per day) 75,68,58,52 According to the line of best fit, what would be the predicted number of minutes spent reading for a person who works 27 hours (per week)? Round your answer to two decimal places, as needed.
Question: The table shows data collected on the relationship between the time spent studying per day and the time spent reading per day. The line of best fit for the data is yˆ=0.16x+36.2. Assume the line of best fit is significant and there is a strong linear relationship between the variables. Studying (Minutes) 50, 70,90,110 Reading (Minutes) 44,48,50,54
According to the line of best fit, what would be the predicted number of minutes spent reading for someone who spent 67 minutes studying? Round your answer to two decimal places.
Question: The table shows data collected on the relationship between the time spent studying per day and the time spent reading per day. The line of best fit for the data is yˆ=0.16x+36.2.
According to the line of best fit, the predicted number of minutes spent reading for someone who spent 67 minutes studying is 46.92.
Is it reasonable to use this line of best fit to make the above prediction?
Question: Michelle is studying the relationship between the hours worked (per week) and time spent reading (per day) and has collected the data shown in the table. The line of best fit for the data is yˆ=−0.79x+98.8. Assume the line of best fit is significant and there is a strong linear relationship between the variables.
Hours Worked (per week) 30405060 Minutes Reading (per day) 75685852
According to the line of best fit, what would be the predicted number of minutes spent reading for a person who works 27 hours (per week)? Round your answer to two decimal places, as needed.
Question: Michelle is studying the relationship between the hours worked (per week) and time spent reading (per day) and has collected the data shown in the table. The line of best fit for the data is yˆ=−0.79x+98.8.
Hours Worked (per week) 30405060 Minutes Reading (per day) 75685852
According to the line of best fit, the predicted number of minutes spent reading for a person who works 27 hours (per week) is 77.47. Is it reasonable to use this line of best fit to make the above prediction?
Question: The table shows data collected on the relationship between the time spent studying per day and the time spent reading per day. The line of best fit for the data is yˆ=0.16x+36.2. Assume the line of best fit is significant and there is a strong linear relationship between the variables.
(a) According to the line of best fit, what would be the predicted number of minutes spent reading for someone who spent 67 minutes studying? Round your answer to two decimal places.
Question: The table shows data collected on the relationship between the time spent studying per day and the time spent reading per day. The line of best fit for the data is yˆ=0.16x+36.2.
(a) According to the line of best fit, the predicted number of minutes spent reading for someone who spent 67 minutes studying is 46.92.
(b) Is it reasonable to use this line of best fit to make the above prediction?
Question: Michelle is studying the relationship between the hours worked (per week) and time spent reading (per day) and has collected the data shown in the table. The line of best fit for the data is yˆ=−0.79x+98.8. Assume the line of best fit is significant and there is a strong linear relationship between the variables.
Hours Worked (per week) 30405060 Minutes Reading (per day) 75685852
(a) According to the line of best fit, what would be the predicted number of minutes spent reading for a person who works 27 hours (per week)? Round your answer to two decimal places, as needed.
Question: Michelle is studying the relationship between the hours worked (per week) and time spent reading (per day) and has collected the data shown in the table. The line of best fit for the data is yˆ=−0.79x+98.8.
Hours Worked (per week) 30405060 Minutes Reading (per day) 75685852
(a) According to the line of best fit, the predicted number of minutes spent reading for a person who works 27 hours (per week) is 77.47.
(b) Is it reasonable to use this line of best fit to make the above prediction?
Question: A medical experiment on tumor growth gives the following data table. The least squares regression line was found. Using technology, it was determined that the total sum of squares (SST ) was 3922.8 and the sum of squares of regression (SSR ) was 3789.0 . Calculate R2 , rounded to three decimal places.
Question: A scientific study on mesothelioma caused by asbestos gives the following data table…… Using technology, it was determined that the total sum of squares (SST) was 1421.2 and the sum of squares due to error (SSE) was 903.51 . Calculate R2 and determine its meaning. Round your answer to four decimal places.
Question: A new mine opened and the number of dump truck loads of material removed was recorded. The table below shows the number of dump truck loads of material removed and the number of days since the mine opened.
A least squares regression line was found. Using technology, it was determined that the total sum of squares (SST ) was 278.0 and the sum of squares of regression (SSR ) was 274.3 . Use these values to calculate the coefficient of determination. Round your answer to three decimal places.
Question: A new mine opened and the number of dump truck loads of material removed was recorded. The table below shows the number of dump truck loads of material removed and the number of days since the mine opened…….. A least squares regression line was found. Using technology, it was determined that the total sum of squares (SST) was 2349 and the sum of squares of error (SSE) was 329. Use these values to calculate the coefficient of determination. Round your answer to three decimal places.
Question: A scientific study on bat populations gives the following data table……. A least squares regression line was found. Using technology, it was determined that the total sum of squares (SST ) was 46.8 and the sum of squares of regression (SSR ) was 14.55 . Use these values to calculate the percent of the variability in y that can be explained by variability in the regression model. Round your answer to the nearest integer.
Question: A fishing enthusiast puts out different numbers of lines at once on several fishing trips to the same location and records the number of fish he catches on each trip. The table below shows the number of lines and number of fish caught on his trips……. Using technology, it was determined that the total sum of squares (SST) was 203.20 and the sum of squares of error (SSE) was 41.62 . Use these values to calculate the coefficient of determination.
Question: A scientific study on calorie intake gives the following data table……… Using technology, it was determined that the total sum of squares (SST) was 237.2 , the sum of squares regression (SSR) was 177.96 , and the sum of squares due to error (SSE) was 59.244 . Calculate R2 and determine its meaning. Round your answer to four decimal places.
Question: A scientific study on graphite density gives the following data table……… Using technology, it was determined that the total sum of squares (SST) was 542.07 , the sum of squares regression (SSR) was 521.02 , and the sum of squares due to error (SSE) was 21.044 . Calculate R2 and determine its meaning. Round your answer to four decimal places.
Question: Given the SSE, SSR, and SST, find the variance in the dependent variable that can't be explained by the variance in the independent variable.
Question: For a particular regression equation, SSR=325 and SST=550. What is SSE?
Question: For a particular regression equation, SSE=19 and SST=31. What is SSR?
Question: Given the SSR and SSE, find SST.
Question: A scientific study on construction delays gives the following data table……. Using technology, it was determined that the total sum of squares (SST) was 2542.8 , the sum of squares regression (SSR) was 2194.8 , and the sum of squares due to error (SSE) was 347.99 . Calculate R2 and determine its meaning. Round your answer to four decimal places.
Question: Given the SSE, SSR, and SST, find the variance in the dependent variable that can be explained by the variance in the independent variable.
Question: Given the SSE, SSR, and SST, find the variance in the dependent variable that can be explained by the variance in the independent variable.
Question: A scientific study on calorie intake gives the following data table……. Using technology, it was determined that the total sum of squares (SST) was 76 , the sum of squares regression (SSR) was 54.850 , and the sum of squares due to error (SSE) was 21.150 . Calculate R2 and determine its meaning. Round your answer to four decimal places?
Question: A scientific study on lift strength gives the following data table……. Using technology, it was determined that the total sum of squares (SST) was 1989.2 , the sum of squares regression (SSR) was 1598.1 , and the sum of squares due to error (SSE) was 391.10 . Calculate R2 and determine its meaning. Round your answer to four decimal places.
Instituition / Term
Term
Fall 2020
Institution
MATH 225N Statistical Reasoning for the Health Sciences
