Absences and Final Exam ScoresNo. ofabsences, x01For students WHO IIISS THO Classes iset the slope or the y-intercept.= as needed.)Finalexam score, y 88.9 86.6 83.6 81.5student who misses five class periods.2Print3= needed.)ow average for this number of absences?4578.2 73.7Done6 7 863.9 72.7It is not appropriate to interpret the slope.965.3 65.40OXReference345678910111213141516171819200.9970.9500.8780.8110.7540.7070.6660.6320.6020.5760.5530.5320.5140.4970.4820.4680.4560.444 (d) Draw the least-squares regression line on the scatter diagram of the data. Choose the correct graph below.OA.Exam Scores vs. AbsencesO C.Final Exam ScoreFinal Exam Score100-80-6040-20010080-60-40-20+02Number of Absences2Exam Scores vs. Absences84Number of Absences810B.D.Final Exam ScoreOA. Yes, because the absolute value of the correlation coefficient is greater than the critical value for a sample size of n = 10.OB. No, because 15 absences is outside the scope of the model.OC. No, because the absolute value of the correlation coefficient is less than the critical value for a sample size of n = 10.OD. Yes, because the purpose of finding the regression line is to make predictions outside the scope of the model.Final Exam Score100-80-60-40-20-0-100-80-60-40-20-0-Exam Scores vs. Absences24 6Number of Absences8Exam Scores vs. AbsencesNumber of Absences(e) Would it be reasonable to use the least-squares regression line to predict the final exam score for a student who has missed 15 class periods? Why or why not?10105

From the information, given thatLet X denotes the number of absences as the independent variable.Let…

Answered: d) Draw the least-squares regression…

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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Is It Getting Harder to Win a Hot Dog Eating Contest?Every Fourth of July, Nathan’s Famous in New York City holds a hot dog eating contest. The table below shows the winning number of hot dogs and buns eaten every year from 2002 to 2015, and the data are also available in HotDogs. The figure below shows the scatterplot with the regression line. Year Hot Dogs 2015 62 2014 61 2013 69 2012 68 2011 62 2010 54 2009 68 2008 59 2007 66 2006 54 2005 49 2004 54 2003 45 2002 50 Winning number of hot dogs in the hot dog eating contest Winning number of hot dogs and buns Click here for the dataset associated with this question. (a) Is the trend in the data mostly positive or negative? Positive Negative (b) Using the figure provided, is the residual larger in 2007 or 2008?Choose the answer from the menu in accordance to item (b) of the question statement 20072008 Is the residual positive or…
19. You might think that increasing the resources available would elevate the number of plant spe- cies that an area could support, but the evidence suggests otherwise. The data in the accompany- ing table are from the Park Grass Experiment at Rothamsted Experimental Station in the U.K., where grassland field plots have been fertilized annually for the past 150 years (collated by Harpole and Tilman 2007). The number of plant species recorded in 10 plots is given in response to the number of different nutrient types added Plot 1 2 3 4 5 6 7 8 9 10 Number of nutrients added 0 0 0 3144 E2 3 Number of plant species 36 36 32 34 33 30 20 23 21 16
Help with: Determine the least-squares regression line. Test whether there is a linear relation between height and weight at the α=0.05 level of significance. What is the P Value Remove the values listed for Player 4 from the data table. Test whether there is a linear relation between height and weight. Do you think that Player 4 is influential? What is the P Value
ANSWER D ONLY
Part and b. Thank you!
Prev The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, y = bo + b₁x, for predicting the number of bids an Item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember, In practice, It would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in Dollars 28 33 36 42 45 Number of Bids 1 7 8 9 10 Step 3 of 6: Find the estimated value of y when x = 33. Round your answer to three decimal places. Table Copy Data Next
Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.858 and the least squares regression line is y = 0.228x +11.187. Complete parts (a) and (b) below. Height, x 27.5 25.75 26.5 25.5 27.25 26.25 25.75 27.25 27 27.25 27 Head Circumference, y 17.4 17.2 17.2 16.9 17.6 17.1 17.1 17.4 17.4 17.3 17.3 (a) Compute the coefficient of determination, R². R² =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment on the adequacy of the linear model. Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model. According to the residual plot, the linear model appears to be
The personnel director of a large hospital is interested in determining the relationship (if any) between an employee's age and the number of sick days the employee takes per year. The director randomly selects ten employees and records their age and the number of sick days which they took in the previous year. Employee 1 2 3 4 5 6 7 8 Age 30 50 40 55 30 28 60 25 Sick Days 7 4 3 2 9 10 0 8 Copy Data The estimated regression line and the standard error are given. Sick Days = 14.310162 - 0.2369(Age 9 10 30 45 5 2 Se = 1.682207 Find the 95% confidence interval for the average number of sick days an employee will take per year, given the employee is 26. Round your answer to two decimal places.
11. For temperature (x) and number of ice cream cones sold per hour (y). (65, 8), (70, 10), (75, 11), (80,13), (85, 12), (90, 16). Interpret the coefficient of determination. Optional Answers: 1. 88.2% of the variability in the number of cones sold is explained by the least-squares regression model. 2. 93.9% of the variability in the number of cones sold is explained by the least-squares regression model. 3. 88.2% of the variability in the temperature is explained by the least-squares regression model. 4. 93.9% of the variability in the temperature is explained by the least-squares regression model.
Draw a scatterplot of the right foot temperature (y) versus the left foot temperature (x). Then draw the least-squares regression line on the graph.
First Paired Data Set 4 6 7 10 13 11 19 | 21 30. Use the First Paired Data Set. Find the equation for the least-squares regression line. A. y 2 0.804x + 3.282 С. у ~ 0.504х + 1.282 В. у 0.904х + 2.282 D. y 2 0.404x + 0.282

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