Briefly Interpret the results from the graphs/ give a brief analysis. Time(sec) Proportion(pill bugs) Proportion(Roaches)10%10%306%5%607%5%% of isopods( of Roaches and Pill Bugs) in warm vs907%6%Time1207%5%1507%7%12%1807%3%10%2107%1%2406%1%8%2706%0%6%3006%1%4%2%0%50100150200250300Time(sec)Proportion(pill bugs)-Proportion(Roaches)% odf Roaches and Pill bugs Time(sec) Proportion (roaches) Proportion(pill bugs)50%47%3067%53%6073%45%9077%38%%of isopods(roaches and pill bugs) in dark12080%35%15077%28%vs. Time18077%32%21077%28%100%24077%35%90%27080%45%80%30093%45%70%60%50%40%30%20%10%0%50100150200250300TIME(SEC)Proportion (roaches)Proportion(pill bugs)% OF ROACHES AND PILL BUGS

In the first graph the comparison has been done between the proportion of roaches and proportion of…

Answered: les) 10% 10% 30 6% 5% 60 7% 5% % of…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A survey was distributed to a group of people asking them how many times they had ordered takeout in the past week. They were also asked how much money they saved that week. The scatter plot displays the relationship between the data collected. the trend line goes through the points (1,230) and (3,190). What is the equation of the trend line. The equation should be in slope form. interpret the slope and y intercept in this context. predict the amount of money a person save when they order takeout 9 times.
The data provided give the number of standby hours based on total staff present, X₁, and remote hours, X₂. Perform a multiple regression analysis using the data provided and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity? Click the icon to view the data. Determine the VIF for each independent variable in the model. | VIF ₂2 = VIF₁ = (Round to three decimal places as needed.) Is there reason to suspect the existence of collinearity? OA. No. The VIF for each independent variable is less than 5. B. Yes. The VIF for each independent variable is greater than 5. OC. No. The VIF for each independent variable is greater than 5. OD. Yes. The VIF for each independent variable is less than 5. wwwwwww Table of Data Standby Total Staff Hours Present 245 330 274 358 195 197 117 153 115 275 200 236 336 339 321 303 286 329 352 323 Remote Hours 417 655 524 385 349 350 388 153 278 479 Print Done
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)
Below is the actual data on the speed a person walks or runs in miles/hour and the calories the person burns per lap. Find the linear equation of best fit for this data. Compare the model to the data. Does the model seem to fit the data? Explain. What is the significance of the y-intercept? What is the slope and what does it mean? What is the x-intercept and what does it mean? What is the correlation coefficient and what does it mean? Speed (mph) Calories/lap 1 42 2 31 3 27 4 41 5 40 6 40 7 39 8 38 r answers to the nearest hundredth. The y-intercept means that if a person runs at ----------mph they will burn__________ per lap. The slope means that for each mph you increase your speed, you will burn an additional------------calories pay lap
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…
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 ?
I just need the d section
I need help with this please
Given (3,7), (6,18), (12,35), what is the slope? The data are given as (x,y)

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les) 10% 10% 30 6% 5% 60 7% 5% % of isopods( of Roaches and Pill Bugs) in warm vs 90 7% 6% Time 120 7% 5% 150 7% 7% 12% 180 7% 3% 10% 210 7% 1% 240 6% 1% 8% 270 6% 0% 6% 300 6% 1% 4% 2% 0% 50 100 150 200 250 300 Time(sec) Proportion(pill bugs) Proportion(Roaches) % odf Roaches and Pill bugs