The following are the annual profit in thousands in a.certain business.2004200520027220062001602003752007-97YearProfit (000OF it a straight line trend by the method of least square and tabulate the trend valuesand short term fluctuation.e What is the monthly incrèase in profit?O Estimate profit for 2014.658085

Answered: Image /qna-images/answer/c4ace088-1d47-469b-a6be-201e64891a0a.jpg

Answered: The following are the annual profit 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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B3 Calculate (predict) t = 11 for each trend method. Create a Linear prediction for Federal Debt-GDP = Create an Exponential prediction for Federal Debt-GDP = Create a Polynomial (order 5) prediction for Federal Debt-GDP = Year t Federal Debt - GDP 2011 1 96.018 2012 2 100.061 2013 3 100.810 2014 4 102.818 2015 5 100.246 2016 6 105.337 2017 7 104.806 2018 8 105.632 2019 9 107.047 2020 10 128.332
The attached table shows the level of water (y) measured in centimeters from the bottom of the container after (x) seconds. Create a table in DESMOS and graph the data. Attach a screenshot of your data plot from DESMOS. Does your data plot look linear or quadratic?
A popular television show recently released a video previewing the upcoming season on his website as fans of the show discovered the video the number of views of the preview video has grown each day during the last two weeks the number of days in the release of the video and the natural log of the number of video views as shown in the scatterplot. based on the scatterplot and residual plot, what type of model would be appropriate for summarizing the relationship between days and numbers of views? an exponential model is appropriate because the Residual plot does not show a clear pattern A linear model is appropriate because of scatterplot shows a strong positive linear relationship A power model is appropriate because the scatterplot of days a natural log of use is strong and linear an exponential model is appropriate because the relationship between the days in the natural log of views in linear and the residual plot does not show a clear pattern
the table shows the percent of households with internet access for selected years from 2009 and projected through 2015. Year Percent of households 2009 67 2010 70 2011 72.5 2012 75 2013 76.5 2014 77.2 2015 78 Use the model to predict the percent of households with internet access in 2022.
Each year, the campers at Pamela's summer camp try to set that summer's record for finishing the obstacle course as quickly as possible. Record obstacle course completio times 30 29 28 27 26 25 24 23 22 Year According to the graph, what was the rate of change between 2018 and 2019? minutes per year Record time (minutes) 2017 2018 2019 2020 2021
PART A The following table shows quarterly sales (in thousand units) for a product over 4 years. The overall sales average for the entire 4 years is 156.5625 (thousand units). Fill in the missing values assuming there is no trend. Round seasonal indexes to 4 decimal places. Report Averages accurate to at most 2 decimal places. Report Actual sales ('000) accurate to the nearest integer. Year 1 Year 2 Year 3 Year 4 Average Seasonal Index Quarter 1 86 93 95 0.6004 Quarter 2 205 207 198 1.2838 Quarter 3 154 159 153 175 160.2 1.023 Quarter 4 184 167 158 175 171 1.092 PART B Suppose actual quarterly sales (in thousands) for Year 5 are 82, 196, 178, and 180 respectively. Assuming there is no trend, forecast sales for the four quarters of Year 5. Use seasonal indexes (rounded to 4 decimal places) from Part A. Report forecast answers as integers accurate to the nearest thousand. Quarter 1 forecast = thousand Quarter 2 forecast= thousand Quarter 3 forecast= thousand Quarter 4 forecast= thousand…
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The equation of the trend line is P = 2001284(1-0.04)t. predict the population of the country in 1994. Include units. Round to the nearest whole number.
Eloise needs to finish a 516-page report on international trade so she can present it at the big conference this weekend. She's been tracking her page count at the end of each business day to see if she's on track. Use Excel to fit a trendline to Eloise's data to create a model of her productivity. According to your model, will Eloise be able to finish her report by the end of the day next Friday? Assume she works only on weekdays. Day Pages Monday 425 Tuesday 431 Wednesday 449 Thursday 464 Friday 471 A: Use Excel to fit a trendline to Eloise's data. What are the slope and intercept for this line? The slope is The intercept is B: Use your model (trendline) to answer the question. Will Eloise finish her report by the end of next friday? Yes
I already know it's a negative correlation and a exponential function I just need help with the other parts and calculations!
Q1: In what years were global temperatures the lowest? Q2: In what years were global temperatures the highest? Q3: What trend is apparent in this graph of actual global temperatures?

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