13:07A myopenmath.comThe table below show data that has been collectedfrom different fields from various farms in a certainvalley. The table contains the grams of Raspberriestested and the amount of their Vitamin C content inmg. Find a linear model that express Vitamin Ccontent as a function of the weight of theRaspberries.Vitamin Cgramscontent in mg6516.38023.29529.811037.212542.814050.515556.8A) Find the regression equation:Y =x +Round your answers to 3 decimalplacesB) Answer the following questions using your un-rounded regression equation.If we test 185 grams of raspberries what is theexpected Vitamin C content?mg (round tothe nearest tenth)Submit Question

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Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 33EQ

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The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
Snowpacks contain a wide spectrum of pollutants thatmay represent environmental hazards. The article“Atmospheric PAH Deposition: Deposition Velocitiesand Washout Ratios” (J. of EnvironmentalEngineering, 2002: 186–195) focused on the depositionof polyaromatic hydrocarbons. The authors proposeda multiple regression model for relating depositionover a specified time period (y, in mg/m2) to tworather complicated predictors x1 (mg-sec/m3) and x2 (mg/m2), defined in terms of PAH air concentrations forvarious species, total time, and total amount of precipitation.Here is data on the species fluoranthene andcorresponding Minitab output:obs x1 x2 flth1 92017 .0026900 278.782 51830 .0030000 124.533 17236 .0000196 22.654 15776 .0000360 28.685 33462 .0004960 32.666 243500 .0038900 604.707 67793 .0011200 27.698 23471 .0006400 14.189 13948 .0004850 20.6410 8824 .0003660 20.6011 7699 .0002290 16.6112 15791 .0014100 15.0813 10239 .0004100 18.0514 43835 .0000960 99.7115 49793 .0000896 58.9716 40656…
An experiment was performed on a certain metal to determine if the strength is a function of heating time. Results based on 10 metal sheets are given below. Use the simple linear regression model. ∑X = 30 ∑X^2 = 104 ∑Y = 40 ∑Y^2 = 178 ∑XY = 134 Find the t statistic and test H0: b1 ≤ 0 vs, Ha: b1 > 0 at α = .05.
(a)The following table shows the amount of melted plastic (in grams) at various temperatures of the plastic (in Celsius). Temperature (Celcius) 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 Melted Plastic (in grams) 8.1 7.8 8.5 9.8 9.5 8.9 8.6 10.2 9.3 9.2 10.5 (I)Find the linear regression equation of the amount of melted plastic temperature. (ii)Estimate the amount of melted plastic at temperature 1.75 Celcius. (iii)Calculate the coefficient of correlation and comment on the relationship between temperature and amount of melted plastic. (iv)Calculate the Spearman’s rank correlation coefficient for the above data. (b)A random sample of twelve students were chosen, and their midterm test score ( y), assignment score (x1), and missed classes (x2) were…
18 An unknown metal has been found and the following experimental results have been tabulated in the table below. The table contains the grams of the unknown metal and the volume in milliliters of water displacement. Find a linear model that expresses mass as a function of the volume. grams Volume in ml 13 133.6 14.5 149.1 16 171.2 17.5 181.7 19 199.3 20.5 217.2 22 230.8 A) Write the linear regression equation for the data in the chart.Volume =______ x+______ where x is the grams of the unknown metal. Round your answers to 3 decimal places B) If the mass of an unknown metal is 11, using your un-rounded regression equation find its predicted volume. Round your answer to 1 decimal place. _______mL
In experimental studies conducted on bacteria in the bioprocess laboratory, bacterial growth rate (Y) was measured in response to different concentrations of the substrate (fattening) substance added to the fattening medium. The table below gives the results. Since it is known that these data fit the Y=aX^b model, write the model by finding the constants contained in the regression model and roughly draw the graph manually. Observation Substrate Concentration (X) Growth rate (Y) 1 360 90 2 165 105 3 21 21 4 23 26 5 11 14 6 18 28
An unknown metal has been found and the following experimental results have been tabulated in the table below. The table contains the grams of the unknown metal and the volume in milliliters of water displacement. Find a linear model that expresses mass as a function of the volume. grams Volume in ml 13 150.4 14.5 164.4 16 183.3 17.5 196.5 19 213.3 20.5 237.1 22 249.5 A) Write the linear regression equation for the data in the chart.Volume == x+x+ where x is the grams of the unknown metal. Round your answers to 3 decimal places B) If the mass of an unknown metal is 11, using your un-rounded regression equation find its predicted volume. Round your answer to 1 decimal place. mLmL
A study investigating the relationship between level x of fertilizer application and crop yield y on 25 one-acre test plots produced r = 0.79, r2 = 0.62, se = 0.97, and the regression equation y-hat = 652x + 311. 1) For the level of fertilizer application 0.38 units, the mean crop yield is predicted to be about what? 2) The proportion of the variability in yield that is accounted for by the level of fertilization is about what?
A group of Maternal and Child Health public health practitioners are interested in the relationship between bacterial vaginosis (BV) and a number of negative health outcomes. Suppose the research team gathers information on a group of participants, and constructs a multiple linear regression model looking at the relationship between BV and depression, controlling for maternal age. The following is a computerized output displaying the results of their analysis.Parameter Intercept Maternal Age DepressionEstimate StandardError tValue Pr>|t|0.2186206635 -.0046496845 0.19124124150.06635040 0.00221338 0.031518843.29 0.0010 -2.10 0.0360 6.07 <.0001 A) What are the dependent and independent variables in this investigation?B) Based on the information above, was the research team justified in controlling for maternal age in this population? Why or why not?C) Write out the model in symbols. Round to 3 decimal places.D) Is there a significant association between BV and depression?
According to the summary result of linear regression model between A and B obtained from R given below, we can fit a regression line. Assume thatA has any value. If we decrease the value of A by 3, how would Y be affected?a) 58.8945 decreaseb) 58.8945 increasec) 29.8827 increased) 49.5142 decreasee) 29.8827 decrease
Sherry is a production manager for a small manufacturing shop and is interested in developing a predictive model to estimate the time to produce an order of a given size---- that is, that total time (in minutes) to produce a certain quantity of the product. She has collected data on the total time to produce 30 different orders of various quantities in the file Setup. A)Write out the estimated linear regression equation. ( define the variables first.) B) Interpret the intercept coefficient. C)Interpret the slope coefficient. D) Test for a significant relationship. Use α = 0.05. file Setup Quantity 105 125 135 141 149 171 190 204 206 240 255 277 299 335 371 388 392 400 421 439 439 455 458 480 486 493 506 586 589 665 Total Time 173 188 222 324 249 318 371 185 250 176 396 226 227 368 490 352 429 411 545 442 320 588 484 512 422 404 700 592 457 642
Consider the following regression model wage 0+3male+imale edut Bedutu where wage is the hourly wage measured in dollars; male is a dummy variable for males; edu is the years of education male edu is the interaction of male and edu variables. The parameter estimates for B parameters are B-152:8-215: 8-0,15 -0,67. What is the predicted marginal effect of years of education formales? Please do fast ASAP fast

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