A group of researchers are working to determine the historicsea levels of the body of water. They are attempting to dothis by taking samples around the body of water and in anearby cave and after analyzing sediment cores from aroundthe body of water to those in the cave.The Climatologist that is working in the cave is trying todetermine the age and growth rate of stalactites, to get amore accurate picture of the age of the existing stalactites.The following table contains the estimated age (to thenearest thousand) of the sample and the length of the samplein micrometers. Find a linear model that express length as afunction of the age.Round your answers to 2 decimal placesAge (nearest thousand)Lengthin thousands of years=Micrometers790690431009110808110241123511532768797104106108111x+13.6151 o where x is the age

Given: Age, x Length in Micrometers, y 76 7906 87 9043 97 10091 104 10808 106 11024…

Answered: The Climatologist that is working in…

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 street light is mounted at the top of a 15-ft-tall pole. A man 6 ft tall walks away from the pole with a speed of 4 ft/s along a straight path. How fast is the tip of his shadow moving when he is 30 ft from the pole? 16/3 X ft/s Enhanced Feedback Please try again. Draw a diagram for this problem. Draw a right triangle with horizontal and vertical edges. Let the vertical edge be the pole. Draw another vertical line with one end on the hypotenuse: and the other end on the horizontal edge depicting the man. Label the distance between the man and the pole x and the distance between the man and the tip of the shadow y. Use properties of similar triangles to find a relation among x, y, the height of the man, and the height of the pole. Differentiate this equation with respect to time, t, using the Chain Rule, to find the equation for the rate at which the tip of the shadow is moving, (x + y). Then, use the values from the exercise to evaluate the rate of change of the distance between the…
The table below gives the percent of men 65 years or older in the workforce for selected years from 1920 and projected to 2030. Complete parts a and b below. Click to view the table of the percentages. a) With x = 0 representing 1900, find the cubic function that models the data. Report the model with coefficients to six decimal places, y=0 example Textbo Data table Year 1920 1930 1940 1950 1960 1970 Percent 45.5 42.5 41.8 43.2 33.4 22:3 Print Year 1980 1990 2000 2010 2020 2030 Percent D 19.3 16.4 17.5 23,6 27.4 28.1 Done X lear all Check answe 6:33 PM
Given a regression model with theta0 = 67.4 and theta1 = 18.28, find the estimated y value for x = 16. (Use 4 significant figures)
The table below show data that has been collected from different fields from various farms in a certain valley. The table contains the grams of Raspberries tested and the amount of their Vitamin C content in mg. Find a linear model that express Vitamin C content as a function of the weight of the Raspberries. grams55606570758085 Vitamin Ccontent in mg11.614.115.918.920.322.825.5 A) Find the regression equation: y= x+Round your answers to 3 decimal placesB) Answer the following questions using your un-rounded regression equation. If we test 115 grams of raspberries what is the expected Vitamin C content? mg(round to the nearest tenth)
Use the estimated regression equation to predict the total time to produce the order of size 240. Round to 2 decimals.
Find the r^2 value
To estimate ages of trees, rangers use a simple regression model that relates the tree diameter (inches) to their age (years). The model is useful because tree diameter has an association to tree age (count of cross section rings). 8 trees were sampled. The regression model is: TreeAge= -0.15228+6.451 (Diameter) Formulas: a) The value of the slope is ["", "", "", ""] . b) The value of the y-intercept is ["", ""] . c) The predicted tree age for a tree with diameter 9.5 inches is ["", ""] years.
(a) Make a scatter diagram of the data. (b) Use the regression feature of a calculator to find the best-fitting linear function for the data. Graph the function with the data. (c) Repeat part (b) for a cubic function. (d) Estimate the minimum sight distance for a car traveling 68 mph using the functions from parts (b) and (c). (e) By comparing the graphs of the functions in parts (b) and (c) with the data, decide which function best fits the given data.
Based on data from 34 adults who exercise regularly, the line of best fit for the relationship between bicep girth (the length in centimeters around the upper arm) and the person's weight is: predicted weight = 2.6 bicep girth – 10.5 %3D where predicted weight is measured in kilograms and bicep girth is measured in centimeters.
Contains data on brain mass in different species versus glia-neuron ratio, the latter being a measurement of brain metabolism as the glia provides the metabolic needs of the neurons. The relationship between THE LOGARITHM of the brain mass (in the third column) and Glia-neuron ratio (fourth column) appears linear and it is these two variables that we wish to analyze via linear regression. We would like to know if the human brain fits the trend from the other species. Towards this end we will perform the regression on all species EXCEPT humans (Homo sapiens). Again, throw out the human data from your analysis. You will however need the human numbers for some of the questions. The analysis to be performed is as follows: 1. Calculate the regression line (slope and intercept) 2. Perform an ANOVA test of the null hypothesis for zero slope. From this analysis, obtain SStotal, SSregression and SSresidual as well as the corresponding MS statistics. 3. Perform a t-test of the null…
A researcher knows that people with higher annual salaries commit fewer crimes. He is creating a regression model to predict the number of crimes a person will commit based on their salary Based on this information alone which of the following MUST be the slope of the regression line choose one 1.00 or 0.50 or -0.50
We want to predict the selling price of a house in Newburg Park, Florida, based on the distance the house lies from the beach. Suppose that we're given the data in the table below. These data detail the distance from the beach (x, in miles) and the selling price (y, in thousands of dollars) for each of a sample of fifteen homes sold in Newburg Park in the past year. The data are plotted in the scatter plot in Figure 1. Also given is the product of the distance from the beach and the house price for each of the fifteen houses. (These products, written in the column labelled "xy", may aid in calculations.) Distance from the beach, x (in miles) Selling price, y (in thousands of dollars) xy 5.0 270.1 1350.5 11.5 205.9 2367.85 5.9 309.4 1825.46 12.2 200.6 2447.32 2.6 307.1 798.46 5.9 266.0 1569.4 8.3 297.3 2467.59 18.3 224.2 4102.86 6.5 242.4 1575.6 12.1 192.6 2330.46 11.6 229.4 2661.04 9.5 230.9 2193.55 10.1 277.0 2797.7 13.5 270.8 3655.8 6.2…

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