ELEMENTARY STATISTICS W/CONNECT >C<
3rd Edition
ISBN: 9781307235012
Author: Navidi
Publisher: MCG/CREATE
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Chapter 4, Problem 6WAI
To determine
To explain: The circumstance of a line which has the sum of squared residuals is zero and the relationship with the least-square regression line.
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Interpret the least squares regression line of this data set.
Meteorologists in a seaside town wanted to understand how their annual rainfall
is affected by the temperature of coastal waters.
For the past few years, they monitored the average temperature of coastal
waters (in Celsius), x, as well as the annual rainfall (in millimetres), y.
Rainfall statistics
• The mean of the x-values is 11.503.
• The mean of the y-values is 366.637.
• The sample standard deviation of the x-values is 4.900.
• The sample standard deviation of the y-values is 44.387.
• The correlation coefficient of the data set is 0.896.
The correct least squares regression line for the data set is:
y = 8.116x + 273.273
Use it to complete the following sentence:
The least squares regression line predicts an additional
annual rainfall if the average temperature of coastal waters increases by one degree
millimetres of
Celsius.
Find the least-squares regression line treating square footage as the explanatory variable.
y =
(Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.)
when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?
Chapter 4 Solutions
ELEMENTARY STATISTICS W/CONNECT >C<
Ch. 4.1 - In Exercises 9-12, fill in each blank with the...Ch. 4.1 - In Exercises 9-12, fill in each blank with the...Ch. 4.1 - In Exercises 9-12, fill in each blank with the...Ch. 4.1 - In Exercises 9-12, fill in each blank with the...Ch. 4.1 - Prob. 13ECh. 4.1 - Prob. 14ECh. 4.1 - In Exercises 13-16, determine whether the...Ch. 4.1 - In Exercises 13-16, determine whether the...Ch. 4.1 - In Exercises 17-20, compute the correlation...Ch. 4.1 - In Exercises 17-20, compute the correlation...
Ch. 4.1 - In Exercises 17-20, compute the correlation...Ch. 4.1 - In Exercises 17-20, compute the correlation...Ch. 4.1 - In Exercises 21-24, determine whether the...Ch. 4.1 - In Exercises 21-24, determine whether the...Ch. 4.1 - In Exercises 21-24, determine whether the...Ch. 4.1 - In Exercises 21-24, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - In Exercises 25-30, determine whether the...Ch. 4.1 - Price of eggs and milk: The following table...Ch. 4.1 - Government funding: The following table presents...Ch. 4.1 - Pass the ball: The following table lists the...Ch. 4.1 - Carbon footprint: Carbon dioxide (CO2) is produced...Ch. 4.1 - Foot temperatures: Foot ulcers are a common...Ch. 4.1 - Mortgage payments: The following table presents...Ch. 4.1 - Blood pressure: A blood pressure measurement...Ch. 4.1 - Prob. 38ECh. 4.1 - Police and crime: In a survey of cities in the...Ch. 4.1 - Age and education: A survey of U.S. adults showed...Ch. 4.1 - Whats the correlation? In a sample of adults, the...Ch. 4.1 - Prob. 42ECh. 4.1 - Changing means and standard deviations: A small...Ch. 4.2 - In Exercises 5-7, fill in each blank with the...Ch. 4.2 - In Exercises 5-7, fill in each blank with the...Ch. 4.2 - In Exercises 5-7, fill in each blank with the...Ch. 4.2 - Prob. 8ECh. 4.2 - Prob. 9ECh. 4.2 - Prob. 10ECh. 4.2 - Prob. 11ECh. 4.2 - Prob. 12ECh. 4.2 - In Exercises 13-16, compute the least-squares...Ch. 4.2 - In Exercises 13-16, compute the least-squares...Ch. 4.2 - In Exercises 13-16, compute the least-squares...Ch. 4.2 - In Exercises 13-16, compute the least-squares...Ch. 4.2 - Compute the least-squares regression he for...Ch. 4.2 - Compute the least-squares regression he for...Ch. 4.2 - In a hypothetical study of the relationship...Ch. 4.2 - Assume in a study of educational level in years...Ch. 4.2 - Price of eggs and milk: The following table...Ch. 4.2 - Government funding: The following table presents...Ch. 4.2 - Pass the ball: The following table lists the...Ch. 4.2 - Carbon footprint: Carbon dioxide (CO2) is produced...Ch. 4.2 - Foot temperatures: Foot ulcers are a common...Ch. 4.2 - Mortgage payments: The following table presents...Ch. 4.2 - Blood pressure: A blood pressure measurement...Ch. 4.2 - Butterfly wings: Do larger butterflies live...Ch. 4.2 - Interpreting technology: The following display...Ch. 4.2 - Interpreting technology: The following display...Ch. 4.2 - Interpreting technology: The following MINITAB...Ch. 4.2 - Interpreting technology: The following MINITAB...Ch. 4.2 - Prob. 33ECh. 4.2 - Prob. 34ECh. 4.2 - Least-squares regression line for z-scores: The...Ch. 4.3 - In Exercises 5-10, fill in each blank with the...Ch. 4.3 - In Exercises 5-10, fill in each blank with the...Ch. 4.3 - In Exercises 5-10, fill in each blank with the...Ch. 4.3 - In Exercises 5-10, fill in each blank with the...Ch. 4.3 - In Exercises 5-10, fill in each blank with the...Ch. 4.3 - Prob. 10ECh. 4.3 - Prob. 11ECh. 4.3 - In Exercises 11-14, determine whether the...Ch. 4.3 - Prob. 13ECh. 4.3 - In Exercises 11-14, determine whether the...Ch. 4.3 - For the following data set: Compute the...Ch. 4.3 - For the following data set: Compute the...Ch. 4.3 - For the following data set: Compute the...Ch. 4.3 - For the following data set: Compute the...Ch. 4.3 - Prob. 19ECh. 4.3 - Prob. 20ECh. 4.3 - Prob. 21ECh. 4.3 - Prob. 22ECh. 4.3 - Hot enough for you? The following table presents...Ch. 4.3 - Presidents and first ladies: The presents the ages...Ch. 4.3 - Mutant genes: In a study to determine whether the...Ch. 4.3 - Imports and exports: The following table presents...Ch. 4.3 - Energy consumption: The following table presents...Ch. 4.3 - Cost of health care: The following table presents...Ch. 4.3 - Prob. 29ECh. 4.3 - Prob. 30ECh. 4.3 - Prob. 31ECh. 4.3 - Transforming a variable: The following table...Ch. 4.3 - Prob. 33ECh. 4.3 - Prob. 34ECh. 4 - Compute the correlation coefficient for the...Ch. 4 - The number of theaters showing the movie Monsters...Ch. 4 - Use the data in Exercise 2 to compute the...Ch. 4 - A scatterplot has a correlation of r=1. Describe...Ch. 4 - Prob. 5CQCh. 4 - Prob. 6CQCh. 4 - Use the least-squares regression line computed in...Ch. 4 - Use the least-squares regression line computed in...Ch. 4 - Prob. 9CQCh. 4 - A scatterplot has a least-squares regression line...Ch. 4 - Prob. 11CQCh. 4 - Prob. 12CQCh. 4 - A sample of students was studied to determine the...Ch. 4 - In a scatter-plot; the point (-2, 7) is...Ch. 4 - The correlation coefficient for a data set is...Ch. 4 - Prob. 1RECh. 4 - Prob. 2RECh. 4 - Hows your mileage? Weight (in tons) and fuel...Ch. 4 - Prob. 4RECh. 4 - Energy efficiency: A sample of 10 households was...Ch. 4 - Energy efficiency: Using the data in Exercise 5:...Ch. 4 - Prob. 7RECh. 4 - Prob. 8RECh. 4 - Prob. 9RECh. 4 - Prob. 10RECh. 4 - Baby weights: The average gestational age (time...Ch. 4 - Commute times: Every morning, Tania leaves for...Ch. 4 - Prob. 13RECh. 4 - Prob. 14RECh. 4 - Prob. 15RECh. 4 - Describe an example which two variables are...Ch. 4 - Two variables x and y have a positive association...Ch. 4 - Prob. 3WAICh. 4 - Prob. 4WAICh. 4 - Prob. 5WAICh. 4 - Prob. 6WAICh. 4 - Prob. 7WAICh. 4 - Prob. 8WAICh. 4 - Prob. 9WAICh. 4 - The following table, reproduced from the chapter...Ch. 4 - Prob. 2CSCh. 4 - Prob. 3CSCh. 4 - Prob. 4CSCh. 4 - Prob. 5CSCh. 4 - Prob. 6CSCh. 4 - Prob. 7CSCh. 4 - Prob. 8CSCh. 4 - Prob. 9CSCh. 4 - Prob. 10CSCh. 4 - Prob. 11CSCh. 4 - Prob. 12CSCh. 4 - Prob. 13CSCh. 4 - If we are going to use data from this year to...Ch. 4 - Prob. 15CS
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- If your graphing calculator is capable of computing a least-squares sinusoidal regression model, use it to find a second model for the data. Graph this new equation along with your first model. How do they compare?arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardThe weight (in pounds) and height (in inches) for a child were measured every few months over a two-year Using technology, what is the slope of the least-squares regression line and what is its interpretation? period. The results are given in the table. The slope is 1.98, which means for each additional 35 inch in height, the child's weight will increase by 1.98 Weight (x) 8. 12 18 24 30 32 37 40 30 32 33 36 38 pounds. Helght (v) 22 23 26 35 The slope is 1.98, which means for each additional inch in height, the child's weight is predicted to increase by 1.98 pounds. The slope is 0.50, which means for each additional pound in weight, the child's height will increase by 0.5 inches. The slope is 0.50, which means for each additional pound in weight, the child's height is predicted to increase by 0.5 inches.arrow_forward
- Help please!!arrow_forwardCompute the least-squares regression line for predicting the price of milk from the price of eggs. Round the slope and -intercept to at least four decimal places.arrow_forwardA regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The least squares regression line is weight = -5.94 + 0.1875 length. Explain in words what this model means (slop and intercept) The new- born boy was 48 cm long, what is the predicted weight of this boy? It is known that the boy is weighed 3 kg. what was his residual? What does that say about him?arrow_forward
- Use the least squares regression line of this data set to predict a value. Meteorologists in a seaside town wanted to understand how their annual rainfall is affected by the temperature of coastal waters. For the past few years, they monitored the average temperature of coastal waters (in Celsius), x, as well as the annual rainfall (in millimetres), y. Rainfall statistics • The mean of the x-values is 11.503. • The mean of the y-values is 366.637. • The sample standard deviation of the x-values is 4.900. • The sample standard deviation of the y-values is 44.387. • The correlation coefficient of the data set is 0.896. The least squares regression line of this data set is: y = 8.116x + 273.273 How much rainfall does this line predict in a year if the average temperature of coastal waters is 15 degrees Celsius? Round your answer to the nearest integer. millimetresarrow_forwardCompute the least-squares regression line for predicting the right foot temperature from the left foot temperature. Round the slope and y-Intercept values to four decimal places.arrow_forwardCompute the least-squares regression line for predicting the number of stays from the cost. Round your answers to four decimal places.arrow_forward
- A recent study showed that the hours a person exercised in a week affected the individual'sresting heart rate. It was computed that r = -.68 and the least squares regression line was?̂ = 83-1.4x, where x is the hours exercised and y is the resting heart rate. d. What percentage of variability in resting heart rate can be explained by variability inhours exercised?arrow_forwardA least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight = -5.25 +0.1696 length. A newborn was 48 cm long and weighed 3 kg. According to the regression model, what was his residual? What does that say about him?arrow_forwardCompute the least-squares regression line for predicting the 2012 budget from the 2006 budget. Round the slope and y- intercept to at least four decimal places.arrow_forward
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