ii.The last seven weeks of sales at KC car dealership can be seen in Table 2 below.Table 2WeekSales125|230327431527297308a. Use a three-period weighted-moving average forecast to determine a forecast for the 8th week usingweights of 3, 2, and 1 (where the most recent week receives the highest weight). (Round all forecasts to thenearest whole unit.)b. Calculate the MAD for this forecast.c. What does the MAD indicate?

Here use weighted moving average formulas

Answered: a. Use a three-period weighted-moving…

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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For the data set, perform a 3 month moving average to determine the forecast for month 13. Show all work in an Excel file. month rate 1 9.5 2 9.3 3 9.4 4 9.6 5 9.8 6 9.7 7 9.8 8 10.5 9 9.9 10 9.7 11 9.6 12 9.6
Need answers for question (d) and (e) without using the Ezcle formula . Show working
A survey is carried out at a university to estimate the percentage of undergraduates living at home during the current term. What is the population? the parameter?
The forecasts generated by two forecasting methods and actual sales have been collected in the Microsoft Excel Online file attached. Use the Microsoft Excel Online file attached to develop forecast accuracy and answer the following questions. 1. What is the MAD, the MSE, the MAPE, the RSFE, and the tracking signal for each forecasting method? Do not round intermediate calculations. Round your answers to two decimal places. Use the minus sign to enter negative values, if any. 2. What can be concluded about the quality of the forecasts 2? Assume that the control limit for the tracking signal is ±3. The results indicate (bias or no bias) in the forecasts 2, and that the tracking signal (is not or is) within the control limits of ±3.
Profits per shop Number of shop 0–100- 12 100–200 18 200-300 27 300–400 20 400–500 17 500-600 06
State if these variables would be expected to have a positive, negative, or no association. A. Number of schools and population size. o Positive Negative No association B. Income and number of health conditions. Positive o Negative No association C. Time spent meditating and stress level. Positive o Negative No association D. Number of pets and amount of money spent on printer ink. Positive Negative o No association E. Life expectancy and death rate. Positive Negative o No association
Solve. 4) Construct a box plot from the data below. 20 25 26 26 26 272933 41 43 45 46 47 4850 50 50 51 53 55 57 60 61 62 63
Which of the following is the most appropriate type of chart for determining the number of observations at or below a specific value? Select one: a. A histogram. b. A pie chart. c. A time-series chart. d. A cumulative frequency ogive.
Read the following prompt and complete 3.a and 3.b
A meteorologist relocated to the city of Windhoek and decided to carry out a research on theamount of rainfall a month recorded in the city in a particular year. His data contained thefollowing: 14 14 10 12 11 13 11 11 11 10 13 8 a. Use the data to calculate the Mean, Mode and Median for the set of rainy days. b. Interpret each central measure
Use the information attached to answer Question 2 and Question 3. The cumulative frequency below displays the amount of time (in minutes) taken to travel to work by employees at a shoefactory.Find the median amount of time (in minutes) for the above data.A. 40B. 45C. 50D. 55 Question 3 Find the interquartile range for the above data.A. 7B. 6.5 C. 10D. 13.5
The authors of a paper were interested in how the distance a deer mouse will travel for food is related to the distance from the food to the nearest pile of debris. Distances were measured in meters. The data and computer output are given below. Distance from Debris Distance Traveled 6.94 0.00 5.23 6.13 5.21 11.29 7.10 14.35 8.16 12.03 5.50 22.72 9.19 20.11 9.05 26.16 9.36 30.65 Simple Linear Regression Results: Dependent Variable: Traveled Independent Variable: Debris Sample size: 9 R (correlation coefficient) = 0.5657 R-sq = 0.32002088 Estimate of error standard deviation 8.670711 Parameter estimates: Parameter Estimate Std. Err. Alternative DF T-Stat P-Value Intercept -7.6854587 13.332196 ≠ 0 7 -0.5764586 0.5824 Slope 3.2340908 1.7818117 ≠ 0 7 1.8150575 0.1124 a)What is the least squares regression line for the output given above? b) what is the predicted traveled distance given the distance from debris is 6.5 meters?

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