The actual sales of car manufacturer in January is 120 units but the car manufacturer underestimated the sales of car by 20 units. If the manufacturer uses exponential smoothing method with a smoothing constant of alpha = 0.2
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- Forecast sales for the 7th period. For leveling, use exponential smoothing 0.20 and moving average 3 for averaging; and linear and exponential functions for trend data. Assume an initial exponential forecast of 60 units in period 2 if you decide to use it (i.e., no forecast for period 1). Period Demand 1 67 2 72 3 68 4 20 5 70 6 66 7 68The processing of raw coal involves “washing,” in which coal ash (nonorganic, incombustible material) is removed. The article “Quantifying Sampling Precision for Coal Ash Using Gy’s Discrete Model of the Fundamental Error” (Journal of Coal Quality, 1989:33–39) provides data relating the percentage of ash to the volume of a coal particle. The average percentage of ash for six volumes of coal particles was measured. The data are as follows: Volume (cm3) 0.01 0.06 0.58 2.24 15.55 276.02 Percent ash 3.32 4.05 5.69 7.06 8.17 9.36 Using the most appropriate model, predict the percent ash for particles with a volume of 48 cm3. Round answer to three decimal places. * the answer i got was of 6.260 was wrongAn electrical contractor’s records during the last five weeks indicate the number of job requests: Week 1 2 3 4 5 Jobs 20 22 18 21 22 Predict the number of requests for week 6 using each of this method:c. Exponential smoothing with α = .30; use 20 for week 2 forecast
- A textbook publishing company has compiled data on total annual sales of its business texts for thepreceding nine years:Year 1 2 3 4 5 6 7 8 9Sales (000) 40.2 44.5 48.0 52.3 55.8 57.1 62.4 69.0 73.7a. Using an appropriate model, forecast textbook sales for each of the next five years.b. Prepare a control chart for the forecast errors using the original data. Use 2s limits.c. Suppose actual sales for the next five years turn out as follows:Year 10 11 12 13 14Sales (000) 77.2 82.1 87.8 90.6 98.9Is the forecast performing adequately? Explain.A special case of a linear function occurs when we talk about direct variation. If the quantities x and y are related by an equation y − kx for some constant k ± 0, we say that y varies directly as x, or y is proportional to x. The constant k is called the constant of proportionality. Equivalently, we can write fsxd − kx, where f is a linear function whose graph has slope k and y-intercept 0. (a) As dry air moves upward, it expands and cools. If the ground temperature is 20°C and the temperature at a height of 1 km is 10°C, express the temperature T (in °C) as a function of the height h (in kilometers), assuming that a linear model is appropriate. (b) Draw the graph of the function in part (a). What does the slope represent?(c) What is the temperature at a height of 2.5 km?The heat transfer between a solid body and a fluid medium is determined by the equation Q=h·A·(Ts-Tf). Here; Q is the amount of heat transferred, h is the heat transfer coefficient, A is the heat transfer surface area, Ts is the temperature of the surface and Tf is the temperature of the fluid. These parameters were measured as h=250±1.75 W/m2ºC, A=20±0.75 m2, Ts =100±0.75ºC and Tf =25±0.75ºC, including error levels. What is the total uncertainty in the amount of heat transferred, in ±%? a. 3.98 b. 4.07 c. 2.73 d. 2.95 e. 3.88
- The speed of sound traveling through the sea is a function of temperature, salinity, and pressure. It is modeled by the function C = 1449.2 + 4.67T -0.055T² +0.00029T³ + (1.34-0.01T) (S-35) + 0.016D where C is the speed of sound (in meters per second), T is the temperature (in degrees Celsius), S is the salinity (the concentration of salts in parts per thousand, which means grams of dissolved solids per 1000 grams of water), and D is the depth below the sea surface, in meters. Calculate the following (Check attached image d3) when T = 10 °C, S = 35 parts per thousand, and D = 100 m. Explain the physical meaning of these derivatives.The drag on an airplane wing in flight is known to be a function of the density of air (), the viscosity of air(), the free-stream velocity (U), a characteristic dimension of the wing (s), and the shear stress on the surface of the wing (s). Show that the dimensionless drag, sU2, can be expressed as a function of the Reynolds number, Us.We are using simple exponential smoothing to predictmonthly electric shaver sales at Hook’s Drug Store. At theend of October 2006, our forecast for December 2006 saleswas 40. In November 50 shavers were sold, and duringDecember 45 shavers were sold. Suppose a 0.50. At theend of December, 2006, what is our prediction for the totalnumber of shavers that will be sold during March and Aprilof 2007?
- the following data is obtained for the velocity of a vehicle during a crash test: t(ms) v(mph) 0 30 10 29.5 20 28 30 23 40 10 50 5 60 2 70 0.5 80 0 if the vehicle's weight is 2,400 lb, approximate the force f in lb acting on the vehicle 40ms after the crash. the force can be calculated by F=m(dv/dt) , and the mass of the car m is 2400/32.2 slug. note that 1 ms=10^-3 s and 1 mile = 5,280 ft. convert t to secons and mph to fps. use 1st order forward, backward, and centered difference and apply Richardson's approximation. use h1=0.02 and h2-0.01s.Show detailed solution. Thanks!Please help Matlab, as well needs to be on excel data sheet. P14.19 You perform experiments and determine the following values of heat capacity cat various temperatures T for a gas:I) For c, determine (a) the mean, (b) median, (c) mode, (d) range, (e) standarddeviation, (f) variance, and (g) coefficient of variation.II) Using linregr given function, fit the data using a straight line (determine a1,a0, r2). Plot the data and the regression curve.III) Using polyfit command, fit the data using a quadratic curve (determine a2, a1, a0).Plot the data and the regression curve.IV) Using linregr given function, fit the data using exponential model (determineα, β, r2). Plot the data and the regression curve in the T-c space (not the T-log(c)space) T -50 -30 0 60 90 110 C 1250 1280 1350 1480 1580 1700As an industrial engineer, you intend to use linear trend (or linear regression) method to solve a forecasting problem. You have decided to use the equation of y = m(x) + c to establish the relationship between the sales (y) and the related month (x). It is known that 8 consecutive months data (Jan to Aug) were used and they resulted to the following parameter values of m = 320 and c = 1017. Using the regression technique, estimate the percentage of sales improvement from December this year to June next year.