This particular graph would not benetit from an equat x-axis is broken making it appear that when you are at age 0, you would be approximately 64 inches tall. When you have a broken x-axis, use the line of best fit to help you make predictions without the equation. When you are interpolating, this is easier. When extrapolating, it is more complicated because you are having to extend your line and graph to consider where the line of best fit would intersect. Basketball Player Age v/s Height 78 74 Use the line tool to create a line of best fit. Predict the height if a basketball player is the following age. 70 19 12 16 21 66 Would these predictions always be reasonable? Describe when the equation appears to be no longer valid. 13 14 15 16 17 18 19 20 Age (Years) Height (Inches)

This particular graph would not benetit from an equat x-axis is broken making it appear that when you are at age 0, you would be approximately 64 inches tall. When you have a broken x-axis, use the line of best fit to help you make predictions without the equation. When you are interpolating, this is easier. When extrapolating, it is more complicated because you are having to extend your line and graph to consider where the line of best fit would intersect. Basketball Player Age v/s Height 78 74 Use the line tool to create a line of best fit. Predict the height if a basketball player is the following age. 70 19 12 16 21 66 Would these predictions always be reasonable? Describe when the equation appears to be no longer valid. 13 14 15 16 17 18 19 20 Age (Years) Height (Inches)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

The scatter plot shows the time spent studying, x, and the quiz score, y, for each of 23 students. (a) Write an approximate equation of the line of best fit for the data. It doesn't have to be the exact line of best fit. (b) Using your equation from part (a), predict the quiz score for a student who spent 70 minutes studying. Note that you can use the graphing tools to help you approximate the line. y 100 90- So (a) Write an approximate equation of the line of best fit. 70 y = Quiz score 60 50 (b) Using your equation from part (a), predict the quiz 40 score for a student who spent 70 minutes studying. 30- 20- 10- 10 20 30 40 50 60 70 80 90 100 Time spent studying (in minutes)
Researchers are trying to predict driving speed from energy drink consumption. They found that people drive on average 15km/h faster for every one energy drink they drink. If the intercept is 0.5, how fast do you expect someone to drive if they drink 5 energy drinks? Your final answer should reflect how fast they will drive, not how much faster they will drive.
I'm looking at the coefficents between two variables on Excel. Copying and pasting is not recommended by my professor. Can anyone give me an idea on how to graph it?
Range of ankle motion is a contributing factor to falls among the elderly. Suppose a team of researchers is studying how compression hosiery, typical shoes, and medical shoes affect range of ankle motion. In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes. Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision. ?̂ = A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places. ?̂ = Suppose Jan's…
The scatter plot shows the time spent watching TV, x, and the time spent doing homework, y, by each of 23 students last week. (a) Write an approximate equation of the line of best fit for the data. It doesn't have to be the exact line of best fit. (b) Using your equation from part (a), predict the time spent doing homework for a student who spends 15 hours watching TV. Note that you can use the graphing tools to help you approximate the line. Time spent doing homework (in hours) 32 28 24 20 16+ 12 8 4 0 y XX 4 X X X X X X X X 8 12 X X 16 X X X X -X X 20 24 Time spent watching TV (in hours) X X X 28 32 X X Ś (a) Write an approximate equation of the line of best fit. y = 0 (b) Using your equation from part (a), predict the time spent doing homework for a student who spends 15 hours watching TV. hours X S
The scatter plot shows the time spent watching TV, x, and the time spent doing homework, y, by each of 23 students last week. (a) Write an approximate equation of the line of best fit for the data. It doesn't have to be the exact line of best fit. (b) Using your equation from part (a), predict the time spent doing homework for a student who spends 15 hours watching TV. Note that you can use the graphing tools to help you approximate the line. Time spent doing homework Kin hours) 32- 28- Y 244 20- 124 F 44 B * K 12 x 14 20 24 26 Time spent watching TV (in hours) 32 X (a) Write an approximate equation of the line of best fit. = 0 (b) Using your equation from part (a), predict the time spent doing homework for a student who spends 15 hours watching TV. hours
Data was collected for a regression analysis comparing car weight and fuel consumption. b0 was found to be 32.7, b1 was found to be -7.6, and R2 was found to be 0.86. Interpret the y-intercept of the line. On average, each one unit increase in the weight of a car decreases its ful consumption by 7.6 units. On average, when x=0, a car gets -7.6 miles per gallon. On average, when x=0, a car gets 32.7 miles per gallon. On average, each one unit increase in the weight of a car increases its fuel comsumption by 32.7 units. We should not interpret the y-intercept in this problem.
The scatter plot shows the average monthly temperature, x, and a family's monthly heating cost, y, for 25 different months. (a) Write an approximate equation of the line of best fit for the data. It doesn't have to be the exact line of best fit. (b) Using your equation from part (a), predict the monthly heating cost for a month with an average temperature of 35 °F. Note that you can use the graphing tools to help you approximate the line. y 100- 90+ 80+ ? 70+ Monthly heating cost (in dollars) 60+ 50+ 40+ 30- 20+ 10+ X + 0 10 20 30 40 50 60 70 80 90 100 Average monthly temperature (in °F) X X X X X X x X xx X X X X X xx X X X X X A X Ś (a) Write an approximate equation of the line of best fit. y = 0 (b) Using your equation from part (a), predict the monthly heating cost for a month with an average temperature of 35 °F. $0 X Ś ?
What is the plot of 2/3
The table and scatter plot show the number of hours worked, x, and the amount of money spent on entertainment, y, by each of 9 students. The equation of the line of best fit is y = 0.9x+18.98. Amount Number of hours 36 spent on entertainment, y (in dollars) 32 worked, x x x x 28- 3.0 17.48 Amount 24 spent on 4.0 22.48 20 entertainment 4.4 27.70 (in dollars) 16+ 5.4 19.95 12. 7.1 28.96 IS- 7.2 23.38 4- 8.0 28.50 10 10 12 14 16 9.0 28.50 Number of hours worked 12.0 29.78 Use the equation of the line of best fit to fill in the blanks below. Give exact answers, not rounded approximations. Observed amount Predicted amount Residual Number of hours worked spent on entertainment spent on entertainment (in dollars) (in dollars) (in dollars) 8.0 12.0
The scatter plot shows the number of years of experience, x, and the amount charged per hour, y, for each of 23 dog sitters in California. (a) Write an approximate equation of the line of best fit for the data. It doesn't have to be the exact line of best fit. (b) Using your equation from part (a), predict the amount charged per hour by a dog sitter with 10 years of experience. Note that you can use the graphing tools to help you approximate the line. Amount charged in dollars \per hour/ 22- 20+ 18+ 16+ 14+ 12+ 10- 8- 6- 4+ 2+ 0 2 4 X 6 X X +3 +: X 8 10 12 14 16 18 20 22 Years of experience X S (a) Write an approximate equation of the line of best fit. :0 y = (b) Using your equation from part (a), predict the amount charged per hour by a dog sitter with 10 years of experience. $0 x Ś
How would I approach this problem?