Use the given equation of the least squares regression line to predict the output when x is 5. Round the final values to three places, if necessary. (2, 13), (4, 11), (5, 7) y = 17.143-1.857x Find the predicted output when x is 5: choose your answer...

The data show the chest size and weight of several bears. Find the regression​ equation, letting chest size be the independent​ (x) variable. Then find the best predicted weight of a bear with a chest size of 58 inches. Is the result close to the actual weight of 572 ​pounds? Use a significance level of 0.05.   Chest size​ (inches) 46 57 53 41 40 40   Weight​ (pounds) 384 580 542 358 306 320   LOADING... Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression​ equation?   y=nothing+nothingx ​ (Round to one decimal place as​ needed.)

Fourteen hikers were surveyed at Algonquin Park, and asked for how many days have you been hikingand far did your travel in that time? The equation for the linear regression line is y+3x + 10.3 where x is the number of days and y is the distance travelled. Estimate the number of whole days a hiker would need to travel 35KM? Number of days hiked 1 1 2 3 3 5 5 6 7 7 9 10 11 12 Distance Traveled (km) 12 17 18 19 21 23 25 23 30 31 37 39 41 52

follow the instructions and provide complete solution, graphs, and interpretations

The equation of the least-squares regression line is ý = 68.5 + 11.4x, where ý is the number of students enrolled and x is number of years the school has been The number of students enrolled at a school varies from year to year. For the first eight years the school is open, the number of students enrolled is recorded in the table shown. open. Which shows the residual plot? Students 92 Year 2. 94 100 104 80 4 60 113 131 40 7. 8. 147 176 20 -20 0. 2. 4. 8. Number of Years 3. 56

Suppose Ms. Carr is interested in the relationship between her students' 9th grade math final exam scores and the number of hours they spent studying during the year. She collects information for 15 ninth grade students and uses it to obtain the regression equation, where ?x is the number of hours spent studying during the year and ?̂ is the predicted final exam score. ?̂ =1.48?+75.64 The scatter plot displays her results. What is the predicted ?̂ value when a student spends 13 hours studying? Round your answer to one decimal place. Select the correct interpretation. The above predicted value of ?̂  is the predicted final math test score if a student studies 13 hours during the year. the predicted score of 13 out of 15 students. what any student will score on the final exam if they study at least 13 hours. the math final test score that 13 students beat.

The point (9.1,71) is a point on the scatterplot. Draw the graph of the regression line on the scatterplot on the back of this paper using the y-intercept and the point(I = 3,y = 191). Indicate the residual for z = 9.1 by drawing the vertical line between(9.1, 71) and the corresponding point on the regression line. Will the residual be a positive or negative value?(f) Find the value of the residual for x = 9.1.

Use the given data to find the equation of the regression line. Round the final values to three significant​ digits, if necessary.   A horizontal table lists x-values in the first row and y-values in the second row. The x-values are as follows from left to right: 6, 8, 20, 28, and 36. The y-values are as follows from left to right: 2, 4, 13, 20, and 30.   A.  y with caret= −2.79 + 0.897x   B. y with caret = −3.79 + 0.801x   C.  y with caret= −2.79 + 0.950x   D. y with caret = −3.79 + 0.897x

Use the computer output to estimate the intercept β0 and the slope β1.The regression equation is Y⁢=811-3.56X. Predictor Coef SE Coef T P Constant 811.183 88.17 9.20 0.000 X -3.562 1.168 -3.05 0.006 Intercept β0: Slope β1:

A set of n = 25 pairs of scores (X and Y values) produces a regression equation Y = 3X – 2. Findthe predicted Y value for each of the following X scores: 0, 1, 3, -2.