Having wrapped up your last project, you begin to pack up when you see a text from Casey. Theynoticed that you were in the office and were hoping you could do one final check on one of their slow-growing bacteria that they are working on. Wanting to be helpful, you check on the results and see thatthe computer has generated a population model P (t) 268,525e0.25t where t is measured in days.Casey would like to know how many days will it take for the population to reach one million, assumingthis model holds?-Round your answer to the nearest hundredth of a day (i.e. 2 decimal places).The population will reach one million in Numberdays.

Answered: Image /qna-images/answer/459bcec8-795a-40bf-9394-36f1a5384b2a.jpg

Answered: Having wrapped up your last project,…

Calculus: Early Transcendentals

8th Edition

ISBN:9781285741550

Author:James Stewart

Publisher:James Stewart

Chapter1: Functions And Models

Section: Chapter Questions

Problem 1RCC: (a) What is a function? What are its domain and range? (b) What is the graph of a function? (c) How...

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Use the data below to solve for the following: 2. Naïve method 3. Unweighted 3 month moving average 4. Weighted Moving Average (3 months, with the following weights: 0.45, 0.35, 0.20) 5. Simple Exponential Smoothing with the following parameters: Ft+1=32 and the α = .15 6. Time Series Regression Months 1 2 3 4 5 6 7 8 9 10 11 12 Firm's Actual Market share 30 32 33 34 28 33 29 27 32 33 28 33 7. Which of the following forecasting method will you use? 8. What are your basis in choosing for your forecasting techniques? Explain briefly. ONLY DO 56
PLEASE DO THIS BY EXCEL AND COMPLETE SOLUTION AND FORMULAS. I WILL UPVOTE THANK YOU
Please answer as many parts as possible. Also, the last answer I received was incorrect. Thank you
We all know that when the temperature of a metal increases, it begins to expand. So, we experimented with exposing a metal rod to different temperatures and recorded its length as follows: Temp Length 20 25 30 35 40 45 50 55 60 65 0.5 1.8 5 6.2 6.5 7.8 9.4 9.8 10.9 Required: 1. Implement and plot a simple linear regression for the above data, where the temperature is "x", and the length is "y" 2. Implement and plot a multiple linear regression "Polynomial regression" with different degrees. For example, Degree of 3: Y = Wix' + w2x? + w3x? + W4 Where wa represents bias. *you can use normal equation to calculate W' as follow: w = (X".X)4.(XT.Y) Then calculate Y, Where Y = X.WT 3. Try degree of 2, 3, 5, and 8
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QUESTION 15 Problem 4b: A forester has a unique ability to estimate the volume (in cubic feet) of trees prior to a timber sale. The timber company wants him to train other employees in his technique of estimation. The forrester's assistant estimates the cubic-foot volume of each tree. After the tree has been chopped down, the forresters obtains the actual cubic-foot volume for a total of 26 trees. A regression model was fitted to the data, with the Estimated Volume y fitted against the Actual Volume x of each tree. The results of the regression are shown below: Coefficients Analysis of Variance Model Summary DF Adj SS Adj MS F-Value P-Value 1 234.31 234315 294.81 Source Term Coef SE Coef T-Value P-Value R-sq R-sq(adj) 92.16% Regression 0.000 Constant 1.845 0.856 2.15 0.041 0.891520 92.47% Error 24 19.08 0.795 Act vol 0.7830 0.0456 17.17 0.000 Total 25 253.39 b) If the assistant is producing an accurate estimate of the volume, it is reasonable to expect that the slope 8, = 1. In a test…
QUESTION 18 Problem 4e: A forester has a unique ability to estimate the volume (in cubic feet) of trees prior to a timber sale. The timber company wants him to train other employees in his technique of estimation. The forrester's assistant estimates the cubic-foot volume of each tree. After the tree has been chopped down, the forresters obtains the actual cubic-foot volume for a total of 26 trees. A regression model was fitted to the data, with the Estimated Volume y fitted against the Actual Volume x of each tree. The results of the regression are shown below: Analysis of Variance Coefficients Model Summary DF Adj SS Adj MS F-Value P-Value 1 234.31 234315 294.81 Source Term Coef SE Coef T-Value P-Value 0.000 R-sq R-sq(adj) 92.16% Regression Constant 1.845 0.856 2.15 0.041 0.891520 92.47% Error 24 19.08 0.795 Act vol 0.7830 0.0456 17.17 0.000 Total 25 253.39 e) A prediction of y for x-15 was performed based on the fitted regression, with the following results: Settings Prediction…
QUESTION 13 Suppose dfErr = 16, SST = 1917, and Se = 3.9 for the simple regression ý = bo + b1(x). What is r2? a. 0.8731 b. None of the answers is correct c. 0.8874 d. 0.8811 e. 0.8651 QUESTION 14 New Last Year Comple Cinall Click Save and Submit to save and submit. Click Save All Answers to save all answers. MacE 20 D00 FA F1 F3 F5
Please calculate the following Chi Square equations. 1. Chi Square Single Sample Physical activity generally declines when students leave high school and enroll in college. This suggests that college is an ideal setting to promote physical activity. One study examined the level of physical activity in a sample of 570 college students. Use the hypothesis steps provided in the video to determine whether there is a significant difference in physical activity among college students. State whether you reject or fail to reject the null hypothesis.
Note: Use a computer application (SPSS) to solve for the following problems.
Let Yt be the sales during month t (in thousands of dollars) for a photography studio, and let Pt be the price charged for portraits during month t. The data are in the file Week 4 Assignment Chapter 12 Problem 64. Use regression to fit the following model to these data:Yt = a + b1Yt−1 + b2Pt + etThis equation indicates that last month’s sales and the current month’s price are explanatory variables. The last term, et, is an error term. If the price of a portrait during month 21 is $10, what would you predict for sales in month 21? Sales Price $400,000 $15 $1,042,000 $12 $1,129,000 $24 $1,110,000 $18 $1,336,000 $18 $1,363,000 $30 $1,177,000 $27 $603,000 $24 $582,000 $36 $697,000 $27 $586,000 $24 $673,000 $27 $546,000 $30 $334,000 $33 $27,000 $24 $76,000 $27 $298,000 $30 $746,000 $18 $962,000 $21 $907,000 $24

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