6. Economics and Marketing The following data representthe price and quantity supplied in 2009 for Dell personalcomputers.PriceQuantitySupplied(S/Computer)2300180200017317001601500150130013712001301000113(a) Using a graphing utility, draw a scatter diagram of thedata with price as the dependent variable.(b) Using a graphing utility, build a logarithmic model fromthe data.(c) Using a graphing utility, draw the logarithmic functionfound in part (b) on the scatter diagram.(d) Use the function found in part (b) to predict the numberof Dell personal computers that will be supplied if theprice is $1650.

Price($/computer) Quantity supplied 2300 180 2000 173 1700 160 1500 150 1300 137 1200…

Answered: 6. Economics and Marketing The…

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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The following table shows the average yearly tuition and required fees, in dollars, charged by four-year American private universities in the school year beginning in the given year. Date Average tuition 2012 $27,870 2013 $29,004 2014 $30,138 2015 $31,272 2016 $32,406 (a) Show that these data can be modeled by a linear function. For each change of 1 year in time there is an increase of $ in tuition. Find its formula. (Let d be the date in terms of number of years since 2012 and T tuition in dollars.) T(d) = 27,870+1134d (b) Plot the data points and add the graph of the linear formula you found in part (a). (c) What prediction does this formula give for average tuition and fees at four-year American private universities for the academic year ending in 2018?$
Find a 96% confidence interval for Hg. Let µa = H1 - H2, where u, is the mean solar energy generated for the east-west highways and µ, is the mean solar energy generated for the north-south highways. (Round to one decimal place as needed.)
Relate how the independent and dependent variables affect each other.
In agricultural economics, a “supply response function” describes how supply of a commodity responds to changes in the price of that commodity. Year Seeded Area (hectares) Harvested Area (hectares) Average Yield (kg per ha) Production (tonnes) Price per Tonne ($/tonne) 1966 1,317,000 1,317,000 1,630 2,150,000 65 1967 1,424,000 1,424,000 1,720 2,449,000 60 1968 1,376,000 1,376,000 1,800 2,477,000 48 1969 1,012,000 1,012,000 1,720 1,742,000 46 1970 567,000 567,000 1,465 830,000 52 1971 1,019,000 1,019,000 1,975 2,014,000 50 1972 1,052,000 1,052,000 1,785 1,878,000 68 1973 1,214,000 1,214,000 1,725 2,095,000 158 1974 1,133,000 1,133,000 1,415 1,605,000 147 1975 1,255,000 1,255,000 1,690 2,123,000 130 1976 1,538,000 1,538,000 1,820 2,803,000 103 1977 1,295,000 1,295,000 2,125 2,749,000 98 1978 1,376,000 1,376,000 2,055 2,831,000 133 1979 1,214,000 1,214,000 1,680 2,041,000 170 1980 1,336,000 1,336,000 1,425 1,905,000 203 1981 1,577,900 1,577,900…
Month Actual demand Forecasted Demand 1 950 1000 2 1070 1000 3 1100 1000 4 960 1000 5 1090 1000 6 1050 1000 For the dataset above, compute the overall MAPE.
In agricultural economics, a “supply response function” describes how supply of a commodity responds to changes in the price of that commodity. (production is the dependent variable,Independent variable: Price) Dataset: Year Seeded Area (hectares) Harvested Area (hectares) Average Yield (kg per ha) Production (tonnes) Price per Tonne ($/tonne) 1966 1,317,000 1,317,000 1,630 2,150,000 65 1967 1,424,000 1,424,000 1,720 2,449,000 60 1968 1,376,000 1,376,000 1,800 2,477,000 48 1969 1,012,000 1,012,000 1,720 1,742,000 46 1970 567,000 567,000 1,465 830,000 52 1971 1,019,000 1,019,000 1,975 2,014,000 50 1972 1,052,000 1,052,000 1,785 1,878,000 68 1973 1,214,000 1,214,000 1,725 2,095,000 158 1974 1,133,000 1,133,000 1,415 1,605,000 147 1975 1,255,000 1,255,000 1,690 2,123,000 130 1976 1,538,000 1,538,000 1,820 2,803,000 103…
The graph show ["", "", "", "", ""] correlation. When the world population increases, we would expect the Atmospheric Carbon Dioxide levels to ["", "", ""] . When the carbon dioxide levels were at 390 parts per million (ppm), the world population was about ["", "", ""] millions.
Price elasticity of demand (supply) or simply elasticity of demand (supply) measures the relative or percentage variation experienced by the quantity demanded (supplied) as a consequence of a change in the price of one percent (1%); In other words, it measures the intensity with which buyers (sellers) respond to a change in the priceprice. Elasticity is often used with respect to the price-demand relationship or the price-supply relationship, but the applicability of this concept is not restricted to that single case, but is broader, since the elasticity is calculated in percentages, since it is the only way to obtain a common unit of measure. When calculating the elasticity in arelationship, the units of measurement are maintained, therefore, they do not measure a proportional change, but a propensity, such as the well-known propensit to Keynesian consumption. The rate at which the selling price changes and from a product, with respect to its supply "x", is given by the following…
ENERGY (KILOWATT-HOURS) 600 500 400 300 200 400 420 370 0 JAN FEB MAR APR MAY 320 310 330 MONTH -380- JUN JUL AUG SEP 400 420 NOV 580 DEC The line graph shows the monthly consumption of energy in kilowatt-hours for a house during a one-year period. Find the total amount of energy consumed during the year.
I need expert advice please especially with the graph. The table below shows monthly data collected on production costs and on the number of units produced over a twelve month period. Month Total Production Costs Level of Activity(Units Produced) July $230,000 3,500August 250,000 3,750September 260,000 3,800October 220,000 3,400November 340,000 5,800December 330,000 5,500January 200,000 2,900February 210,000 3,300March 240,000…
Monthly savings in PKR DR 125000 10 85000 15 105000 28 98000 35 54000 44 800000 56 55000 68 7000 74 24000 28 0 35 Suppose that we have data on “Monthly savings in PKR” and “dependency Ratio (DR)”(percentage share of non-earners to earners, in a family). Run a regression that can help us predict the monthly savings, given the data of DR. Predict monthly savings, if DR=10, and if DR=90; interpret the results in terms of prediction accuracy

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