An auto manufacturer wants to determine the relation between average speed and miles per gallon for her new economy vehicle.The table shows the results from six average speed tests.Average Speed (mph), x384148 | 59 |59| 68Miles Per Gallon, y54 53 52 48 |44 35Use the least squares regression line to estimate the miles per gallon for 34 mph. Round your answer to two decimal places, ifnecessary.Select the correct response:5848.964.463.8

Calculate Fitting a straight line - Curve fitting using Least square method X Y 38 54 41 53…

An auto manufacturer wants to determine the relation between average speed and miles per gallon for her new economy vehicle The table shows the results from six average speed tests. Average Speed (mph), x 38 48 59 59 68 Miles Per Gallon, y 54 53 52 |48 44 35 Use the least squares regression line to estimate the miles per gallon for 34 mph. Round your answer to two decimal places, if necessary. Select the correct response: 58

An auto manufacturer wants to determine the relation between average speed and miles per gallon for her new economy vehicle The table shows the results from six average speed tests. Average Speed (mph), x 38 48 59 59 68 Miles Per Gallon, y 54 53 52 |48 44 35 Use the least squares regression line to estimate the miles per gallon for 34 mph. Round your answer to two decimal places, if necessary. Select the correct response: 58

Holt Mcdougal Larson Pre-algebra: Student Edition 2012

1st Edition

ISBN:9780547587776

Author:HOLT MCDOUGAL

Publisher:HOLT MCDOUGAL

Chapter11: Data Analysis And Probability

Section11.3: Using Data Displays

Problem 2C

See similar textbooks

Similar questions

An automotive engineer computed a least-squares regression line for predicting the gas mileage (y) in miles per gallon of a certain vehicle from its speed (x) in miles per hour. The result is y = -0.14x+ 38.78. Predict the gas mileage when the vehicle is travelling at 55 miles per hour. Round your answer to one decimal place. Only write a number as your answer.
please answer d-f
A real estate company wanted to see the relationship between home prices and square footage of homes for sale. The regression line is ŷ = –802,456 + 144x, where x is the square footage of a home. Complete the statement based on the information. For every -square-foot increase, the predicted home price is predicted to increase by $
Page of 11 ZOOM + 5. The table shows how the cost of a carne asada taco at my favorite taco stand has increased as they have become more popular since their opening in 2013. Use the data to answer the questions below. Year, x 2013, 0 2014, 1 2015, 2 2016, 3 2017, 4 2018, 5 2019,6 Cost ($) 0.50 0.55 0.65 0.75 0.90 1.00 1.10 (a) What is the regression line given by your TI-84 for this data? Round values to 3 decimal places. (b) Using the regression equation above, predict the cost of a carne asada taco at my favorite taco stand in 2020. Show the work.
An auto manufacturer wants to determine the relation between average speed and miles per gallon for her new economy vehicle . The table shows the results from six average speed tests . Average Speed (mph), x 38 41 48 59 59 68 Miles per Gallon, y 54 53 52 48 44 35 Use the least squares regression line to estimate the miles per gallon for 34 mph. Round your answer to two decimal places , if necessary.
Solve.
Researchers initiated a long-term study of the population of American black bears. One aspect of the study was to develop a model that could be used to predict a bear's weight (since it is not practical to weigh bears in the field). One variable thought to be related to weight is the length of the bear. The accompanying data represent the lengths and weights of 12 American black bears. Complete parts (a) through (d) below. Click the icon to view the data table. Click the icon to view the critical values table. ..... (a) Which variable is the explanatory variable based on the goals of the research? O A. The number of bears B. The weight of the bear O C. The length of the bear (b) Draw a scatter diagram of the data. Choose the correct graph below. O A. O B. O C. D. A Weight (kg) 180- AWeight (kg) 180- ALength (cm) 180- A Weight (kg) 180- 40- 100 40- 100 Length (cm) 40- 100 40- 100 200 200 200 200 Length (cm) Weight (kg) Length (cm) (c) Determine the linear correlation coefficient between…
Which two rows of the data table show the following pattern? Select all that apply. A tripling of the value of x results in the value of y increasing by a factor of nine. Row X A 2 B C D E Rows A and B. Rows A and C Rows A and D Rows A and E Rows B and C 4 6 8 12 Tap the options below to select and deselect. Select all that apply. Rows B and D Rows B and E Rows C and D Rows C and E Rows D and E y 2 8 18 32 72
The r code for side by side boxplot of vitamind v newage and vitamin d v country. Scatterplot code for relationship between vitamin d level and age.
An environmentalist wants to determine the relationships between the numbers (in thousands) of forest fires over the year and the number (in hundred thousands) of acres burned. The data for 8 recent years are shown. Required: Find the coefficient of determination. Only the final answer should be rounded-off to TWO decimal places.
The accompanying table shows the height and weight of five football players in training camp. The body mass index (BMI) is used to assess the relative amount of fat in a person's body. If w is weight in pounds and h is height in inches, then BMI = 703wh. Some physicians consider your body fat abnormal if your BMI satisfies BMI-23>3. Which of the five players does not have abnormal body fat? does not have abnormal body fat. Player D Player B Player C Player E Player A .. Player A B C E Ht. 6-8 5-8 5-10 5-9 6-6 Wt. 359 240 227 164 342
In an area of the Great Plains, records were kept on the relationship between the rainfall (in inches) and the yield of wheat (bushes per acre). Calculate the linear coefficient. Rainfall (in inches), x 9.4 7.7 12.3 11.4 17.7 9.2 5.9 14.5 14.9 Yield (bushels per acre), y 46.5 42.2 54.8 55 78.4 45.2 27.9 72 74.8 Answer choices are: A. 0.900 B. 0.981 C. 0.899 D. 0.998