Solve it correctly please. I will rate accordingly with multiple votes. My last attempt. Question 7Problem Z: Interpolation, least squares, and finite differenceConsider the following data table:O 0.70O 0:00O 0.76○ 3.0300.40.81.2Using the second-order accurate central finite difference, the computed value for the second derivative of f(a) at as-0.8 isNone of the choicesPreviousf(x) =2.4002.7893.1173.332Mont

It is not clear the given options. Confused whether a negative sign exists in first option or not.

Answered: Question 7 Problem Z: Interpolation,…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 2GP

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Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?
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?
Planetary Velocity The following table gives the mean velocity of planets in their orbits versus their mean distance from the sun. Note that 1AU astronomical unit is the mean distance from Earth to the sun, abut 93 million miles. Planet d=distance AU v=velocity km/sec Mercury 0.39 47.4 Venus 0.72 35.0 Earth 1.00 29.8 Mars 1.52 24.1 Jupiter 5.20 13.1 Saturn 9.58 9.7 Uranus 19.20 6.8 Neptune 30.05 5.4 Astronomers tell us that it is reasonable to model these data with a power function. a Use power regression to express velocity as a power function of distance from the sun. b Plot the data along with the regression equation. c An asteroid orbits at a mean distance of 3AU from the sun. According to the power model you found in part a, what is the mean orbital velocity of the asteroid?
Q3 Part ( C ) A researcher estimated following model using data for the period 1991-2018 Discuss the nature of autocorrelation in the above model. Which test will you use? Why?
A rich sports car owner wants to develop a regression equation that determines mileage as a function of the age of a car in years. He collects the data shown below for the 12 cars he has on his lot. Age Mileage 7 52654 4 49300 13 113671 7 63001 7 69850 7 68048 12 106979 8 82719 7 80894 10 109258 14 149804 8 98915 a) What is the slope of the regression equation? Give your answer to two decimal places. i got 9157.61 correctb) What is the value of the correlation coefficient? Give your answer to two decimal places. i got 0.92 correct c) A 4 year old car is delivered to his lot with 160000 miles. Manually enter these values in the data table above and rerun the regression analysis. What is the value of the slope? i got 10203.66 but that was wrong d) Including the additional car, what is the value of the correlation coefficient? i got 0.924 but that was wrong. only c and d need to be answered.
10) A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.767 b=31.009 r2=0.609961 r=-0.781 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)
Only need last part
Looking at this output in the photo, we know that the proportion of the variation in mileage is accounted for by the linear relationship with the weight of the car is 43.8 % and that the estimate of the regression standard deviationis is 6.78. Determine the equation of the Least Squares Regression Line and what the interpretation of the slope for weight of car is? Then performing a T-test, determine what the value of the t stastitic is if we wanted to test if there is a significant straight-line relationship between the weight and the mileage of a car.
The scatter plot below shows the average cost of a designer jacket in a sample of years between 2000 and 2015. The least squares regression line modeling this data is given by yˆ=−4815+3.765x. A scatterplot has a horizontal axis labeled Year from 2005 to 2015 in increments of 5 and a vertical axis labeled Price ($) from 2660 to 2780 in increments of 20. The following points are plotted: (2003, 2736); (2004, 2715); (2007, 2675); (2009, 2719); (2013, 270). All coordinates are approximate. Interpret the slope of the least squares regression line. Select the correct answer below: 1.The average cost of a designer jacket decreased by $3.765 each year between 2000 and 2015. 2.The average cost of a designer jacket increased by $3.765 each year between 2000 and 2015. 3.The average cost of a designer jacket decreased by $4815 each year between 2000 and 2015. 4. The average cost of a designer jacket increased by $4815 each year between 2000 and…
Only b part
4
A study investigated how the content of vitamin A in carrots is affected by the time being cooked. In this example: X represents the amount of time, in minutes, that the carrot slices were cooked Y represents the content of vitamin A (in milligrams) in the carrot slices The least-squares regression equation for this relationship is: Y = 21.4 – 0.75X What is the slope of the regression line? Provide a numeric value as shown in the equation.

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