Problem 3-11 (Algo)A manager of a store that sells and Installs spas wants to prepare a forecast for January, February, and March of next year. Herforecasts are a combination of trend and seasonallty. She uses the followIng equation to estimate the trend component of monthlydemand: F= 90+3t where t= 0 in June of last year. Seasonal relatives are 1.00 for January,.96 for February, and .95 for March. Whatdemands should she predict? (Round your answers to 2 decimal places.)MonthForecastJanuary of the next yearFebruary of the next yearMarch of the next year

Answered: Image /qna-images/answer/9aa45dea-2b42-4798-970a-ba2bf6cba926.jpg

Answered: A manager of a store that sells and…

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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Problem 6-11 For the Hawkins Company, the monthly percentages of all shipments received on time over the past 12 months are 80, 82, 84, 83, 83, 84, 85, 84, 82, 83, 84, and 83. Choose the correct time series plot. (i) (ii) (iii) (iv) What type of pattern exists in the data? Compare a three-month moving average forecast with an exponential smoothing forecast for α = 0.2. Which provides the better forecasts using MSE as the measure of model accuracy? Do not round your interim computations and round your final answers to three decimal places. Movingaverage Exponentialsmoothing MSE fill in the blank 3 fill in the blank 4 What is the forecast for next month? If required, round your answer to two decimal places.fill in the blank 6
Week (X) Demand (Y) 1 2000 2 2200 3 1890 4 2248 5 1902 6 2300 7 2304 8 1903 9 1899 10 2180 11 1893 12 1201 13 1000 how do I insert a linear trendline and be sure to display the equation and R value in excel?
Question 9b . Describe the relationship displayed in the scatterplot (Using DUFS)
Referring to Scenario 13-11, which of the following is the correct interpretation for the slope coefficient?a) For each decrease of 1 thousand downloads, the expected revenue is estimated to increase by $3.7297 thousands.b) For each increase of 1 thousand downloads, the expected revenue is estimated to increase by $3.7297 thousands.c) For each decrease of 1 thousand dollars in expected revenue, the expected number of downloads is estimated to increase by 3.7297 thousands.d) For each increase of 1 thousand dollars in expected revenue, the expected number of downloads is estimated to increase by 3.7297 thousands.
QUESTION 6 Suppose the following are the seasonal indices for the first three quarters of the year for a quarterly series: Quarter Seasonal Index Q1 70.5 Q2 81.7 Q3 110 Remember that the seasonal indices should average 100 so you should be able to infer the seasonal index for Q4. Furthermore, suppose that the estimated coeffcients from a regression of the deseasonalized series on Time are given below: Coefficients Intercept 2,306 Time 65.7 What is the trend projection of the series for period 52? (please round your answer to 1 decimal place)
Question 4 The below data represent the advertising expenditure and sales of Little Liu Ltd from year 2008 to 2017. Table: Advertising Expenditure vs. Sales from 2008 to 2017 Year Advert. Expenditure Sales (x, £000) (y, £000) 2008 8 30 2009 12 40 2010 11 29 2011 5 29 2012 14 43 2013 3 17 2014 6 20 2015 8 30 2016 4 22 2017 9 40 Total 80 300 Figure: Scatter Diagram of Advertising Expenditure and Sales with Trend line Work out the values of parameters of the relationship shown in the Figure (i.e. work out the equation of the relationship).
Table #2.3.7 contains the value of the house and the amount of rental income in a year that the house brings in ("Capital and rental," 2013). Create a scatter plot and state if there is a relationship between the value of the house and the annual rental income. Table #2.3.7: Data of House Value versus Rental Value Rental Value Rental Value Rental Value Rental 81000 6656 77000 4576 75000 7280 67500 6864 95000 7904 94000 8736 90000 6240 85000 7072 121000 12064 115000 7904 110000 7072 104000 7904 135000 8320 130000 9776 126000 6240 125000 7904 145000 8320 140000 9568 140000 9152 135000 7488 165000 13312 165000 8528 155000 7488 148000 8320 178000 11856 174000 10400 170000 9568 170000 12688 200000 12272 200000 10608 194000 11232 190000 8320 214000 8528 208000 10400 200000 10400 200000 8320 240000 10192…
Question 4 The below data represent the advertising expenditure and sales of Little Liu Ltd from year 2008 to 2017. Table: Advertising Expenditure vs. Sales from 2008 to 2017 Year Advert. Expenditure Sales (x, £000) (y, £000) 2008 8 30 2009 12 40 2010 11 29 2011 5 29 2012 14 43 2013 3 17 2014 6 20 2015 8 30 2016 4 22 2017 9 40 Total 80 300 Figure: Scatter Diagram of Advertising Expenditure and Sales with Trend line (attached as image) a)What is the statistical relationship shown in the Figure and list out 3 characteristics of this relationship? b) Work out the values of parameters of the relationship shown in the Figure (i.e. work out the equation of the relationship). c)Explain the relationship and make recommendation to Little Liu Ltd based on the information given.
Question 4 The below data represent the advertising expenditure and sales of Little Liu Ltd from year 2008 to 2017. Table: Advertising Expenditure vs. Sales from 2008 to 2017 Year Advert. Expenditure Sales (x, £000) (y, £000) 2008 8 30 2009 12 40 2010 11 29 2011 5 29 2012 14 43 2013 3 17 2014 6 20 2015 8 30 2016 4 22 2017 9 40 Total 80 300 Figure: Scatter Diagram of Advertising Expenditure and Sales with Trend line a) What is the statistical relationship shown in the Figure and list out 3 characteristics of this relationship? b) Work out the values of parameters of the relationship shown in the Figure (i.e. work out the equation of the relationship) c) Explain the relationship and make recommendation to Little Liu Ltd based on the information given.
Problem 1: Consider the following data from a random sample. x-Average daily temperature (°C): 31, 28, 39, 42, 37, 36, 32, 29, 33, 42. y-Average daily consumption (kWh) per family: 355, 349, 506, 567, 440, 443, 380, 374, 442, 542. Answer each of the following questions, supporting your conclusion.a) Is there a linear relationship between these two variables and how much is this linear relationship?b) Indicate on average how much y=average consumption is expected to change for a change of 1 °C inthe x=temperature.c) Indicate the % of the total variation of Y that is explained by the regression model for thesedata, is it a good model?d) Could we infer that the model in general is significant for the population at a level ofsignificance of 0.05?e) Could we infer that the Bo coefficient model is significant for the population at a level ofsignificance of 0.05?f) Predict the average daily consumption expected for a day with a mean temperature of 38°C andgive your confidence interval
Question # 1 A well-known multinational FMCG produces more than fifty products and sells them in the market. Out of fifty products one is mineral water for drinking purpose and supplies different size pack bottles in the market. Product manager observed that, during hot days the sale of water is more as compared to the normal days. He started the collection of data of weekly sale of water and the average weekly temperature. Product manager was interested in developing a relationship between sales and temperature; therefore, he discussed and shared the following data with you. sales 75 77 69 63 79 80 77 70 73 87 72 73 80 80 69 84 77 72 74 81 temperature 32 36 31 31 34 29 32 35 28 31 30 31 29 35 36 28 32 33 32 33 Sale is in thousand liters and temperature is in degree Celsius. Data…
PROBLEM 3 A classic application of correlation involves the association between the temperature and the number of times a cricket chirps in 1 minute. Listed below are the number of chirps in 1 minute and the corresponding temperatures in degree Fahrenheit. Is there a significant evidence to conclude that there is a linear correlation between the number of chirps in 1 minute and the temperature? Use alpha = 0.01. Chirps in 1 minute (x) Temperature (y) 882 69.7 1188 93.3 1104 84.3 864 76.3 1200 88.6 1032 82.6 960 71.6 900 79.6

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