The follow table shows total dollar sales (in thousands) for a local retailer for various years.Year2019 2020 2021 2022 2023Sales ($) 162126 31 36a) What was the dollar amount of sales for 2022? $b) By how much did sales increase each year? $c) Find a linear function S(x) that models the above data, where x is the number of years after 2018 (sothat the year 2019 corresponds to x = 1, the year 2020 corresponds to x = 2, and so on) and S(x) is thedollar amount of sales in thousands.S(x) =X +d) Use S(x) to predict sales in 2025. $If needed, round answer to 5 decimal plates.Enter DNE for Does Not Exist, oo for InfinityQuestion Help: Message instructorSubmit Questionthousandthousandthousand

Given table: x 1 2 3 4 5 Year 2019 2020 2021 2022 2023 Sales($) 16 21 26 31 36

Answered: The follow table shows total dollar…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Calculate trend values by the method of least square from the data given below and estimate the sales for 1983 : Year 1976 1977 1978 1979 1980 : Sales of Co. ('000,000) : 70 74 80 86 90
Solve s(4- 3x2
The following data table gives information about the change in smartphone sales of two leading companies from 2007 to 2017. Company Smartphones sold in 2007 Smartphones sold in 2017 Smartphones sold in 2027 Apple 2.3 million 214.9 million ? Samsung 435.5 million 321.3 million ? The number of smartphones sold is changing for these companies every year. Suppose that over the next 10 years, from 2017 to 2027, their absolute rates of change of smartphone sales remains the same as the previous 10 years. Using the data table, determine which of the following statements would be true? a. Apple and Samsung will sell approximately the same number of smartphones in 2027. b. Samsung will sell more smartphones that Apple in 2027. c. Apple will sell over 400 million smartphones in 2027. d. Samsung will sell over 400 million smartphones in 2027.
The following table shows worldwide sales of a certain type of cell phone and their average selling prices in 2013 and 2017. Year 2013 2017 Selling Price ($) 335 225 Sales (millions) 1,010 2,110 (a) Use the data to obtain a linear demand function for this type of cell phone. q(p) =
The table gives the projections of the population, in millions, of a country's residents over age 16 for selected years from 2015 to 2060. Answer parts (a) through (c). b. What does the model predict that the population will be in 2052? Year 2015 2020 2025 2030 2035 c. In what year does the model predict that the population will be 336.823million? Population (millions) a. Find a linear function that models the data, with y equal to the population in millions and x equal to the number of years after 2010. y=x+ (Type integers or decimals rounded to three decimal places as needed.) 255.161 266.024 276.558 286.967 297,259 Year 2040 2045 2050 2055 2060 Population (millions) 306.634 315.152 323.314 331.770 340.868 D
TABLE 1: An economist at Nedbank ran a study of the relationship between FTSE/JSE All Shares index retu (JALSH) and consumer price index (CPI) from 2006 to 2017, the data collected is shown in the Tal below. FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017. CPI (X) 4.7 7.1 11.5 7.1 4.3 5.0 5.6 5.7 6.1 4.6 6.4 5.3 Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Question 1 Use Table 1 above to answer this question JALSH (Y) 0.41 0.19 -0.23 0.32 0.19 0.03 0.27 0.21 0.11 0.05 0.00 0.21 Q.1.1 The estimated regression equation with dependent variable FTSE/JSE All Shares index return (JALSH) and independent variable consumer price index (CPI) was Q.1.1.1 Calculate Bo JALSH, =B₁ + B₂CPI¡
An economist is studying the median yearly income of workers by their ages. Age (yr) 18 28 38 48 58 68 Median Income ($) 17,480 30,650 37,440 41,230 37,570 21,390 a. What function best models the data (linear, quadratic, exponential)? b. Write a function that models the data. c. Use your model to predit the median income for a worker who is 43 years old. Round to the nearest dollar.
Describe the patterns in quantity sold and own and rival prices during this time period using basic descriptive statistics. Graphs are welcome as well. Take the logs of the variables, and estimate the demand function. Interpret the R-square. Interpret the coefficients for logP and logPsub Interpret the p-values associated with each independent variable Are consumers price sensitive? Why or why not? (be as precise as you can – you have estimates!). Does this price sensitivity make sense given the good we are examining? How sensitive are our consumers to changes in the rival good’s price? Explain in detail. Suppose we decide to charge a per ounce price of $2, while at the same time our rival charges a price of $2.15. All else equal, what would you expect sales to be? How confident are you in your forecast? Suppose we are charging a price of $2 and our current marginal cost is $1.50 Are we maximizing profits at this price? If not, should we raise or lower price? Why?
The below data represent the advertising expenditure and sales of Liu Liu Ltd from year 2010 to 2019. Table: Advertising Expenditure vs. Sales from 2010 to 2019 Year Advert. Expenditure Sales Growth rate of Ad. Expenditure Growth rate of Sales (x, £000) (y, £000) 2010 19 84 2011 22 108 18% 29% 2012 32 82 46% -24% 2013 42 86 32% 6% 2014 47 84 11% -3% 2015 46 94 -2% 11% 2016 58 103 27% 10% 2017 63 115 8% 12% 2018 70 106 11% -8% 2019 80 142 15% 34% Total 479 1004 a. What is the statistical relationship shown in the table and list out 3 characteristics of this relationship?
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The graph below shows a company's estimated profits (in dollars) for different advertising expenses (in tens of thousands of dollars). The company's actual profit was $988,608.55 for an advertising expense of $290,000. P 1 100 000 900 000 700 000 500 000 300 000 100 000 - 100 000 (29, 988608.55) 5 10 15 20 25 30 35 (b) The company's model is X i (a) From the graph, it appears that the company could have obtained the same profit for a lesser advertising expense. Use the graph to estimate this expense (in dollars). An advertising expense of $ when x = 0 also appears to yield a profit of about $988,608.55. P = 140.75x³ + 5348.3x2 - 76,560, 0 ≤ x ≤ 35 where P is the profit (in dollars) and x is the advertising expense (in tens of thousands of dollars). Explain how you could verify the lesser expense from part (a) algebraically. To verify, evaluate P(x) at x =

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