Example 5.12. Fit a straight line to the given data usingweighted least-square approximationX:0Y:-1W:125151210720210264t

Answered: Image /qna-images/answer/67d549d0-89c7-4e8e-8240-6e4a6a2dc990.jpg

Answered: weighted least-square X: 0…

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter5: Inverse, Exponential, And Logarithmic Functions

Section5.3: The Natural Exponential Function

Problem 44E

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Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
The following data shows the atmospheric pollutants yi(relative to an EPA standard) at half hour interval xi. Find the equation y=a+bx of the least square line that best fits the data points given by 2,1, 5,2, 7,3, 8,3. Hence predict the atmospheric pollutant at x=6 half hour.
Suppose the least squares regression line for predicting weight (in pounds) from height (in inches) is given by Weight= -110+3.5*(height) Which of the following statements is correct? l. A person who is 61 inches tall will weigh 103.5 pounds ll. For each additional inch of height, weight will decrease on average by 3.5 pounds. lll. There is a negative linear relationship between height and weight. a) l and lll only b) l and ll only c) ll only d) l only e) ll and lll only
Recently, the annual number of driver deaths per 100,000 for the selected age groups was as follows. Age Number of Driver Deaths per 100,000 17.5 38 22 36 29.5 24 44.5 20 64.5 18 80 28 a. Calculate the least squares (best-fit) line. Put the equation in the form of: ý = a+ bx. ý = 35.582+-.192x For each age group, pick the midpoint of the interval for the x value. (For the 80+ group, use 85. Enter exact numbers as integers, fractions, or decimals.) i. Age Group Midpoint 15-24 25-39 40-69 70-79 80+ Predict the number of deaths for age 26. (Use your equation from part (a). Round your answer to one decimal place.) ii. deaths per 100,000 Predict the number of deaths for age 60. (Use your equation from part (a). Round your answer to one decimal place.) iii. deaths per 100,000
When a least squares line is fit to the 8 observations in the fuel consumption data, we obtain SSE = 3.264. Calculate s? and s. (Round your answers to 3 decimal places.)
Fit a straight linc trend by the method of least squares and estimate the production in 2015. 2006 2007 2008 2009 2010 2011 2012 Year: Production (in '000 tonnes): 80 90 92 83 94 99 92
Please do 3c and 3d with handwritten working out
Using the guide of the textbook and your RQ, determine the equation of the least-square line for the following data: 1 6 3. Select the correct answer in the slope-intercept form. O y=-x+10.5 O y=-2x+11 O y=x O y=x+10 O x+y=11
The following x-y data is given, but the y-value that corresponds to x=6 is missing. Usenumerical techniques to obtain a reasonable value for y at the missing point with minimum error.Please explain your work. Plz don't use chat gpt
Find the least square fitting for the following data and function type. Input the closest integer value for every unknown coefficient off. Make sure to write the closest integer to the estimate that you have found for all coefficients. x= 1x8 0.1234 0.5678 0.1441 0.2271 0.2956 0.3218 0.6082 0.3169 y= 1x8 -5.5130 -4.3120 -3.3450 -5.7650 -3.5780 -4.8450 -5.1315 -4.2050 f= ax? + bx + c a = ? b = ? c = ?
Find the least squares approximating line y = 20 21 for the following sets of data points. What is the value forz1? (1, 0), (2, 2), (3, 3), (4, 6) -1.9 2.9 -2.9 1.9

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weighted least-square X: 0 approximation 2 5