Top of Form a)Plot the monthly sales data.b)Forecast January sales using each of the following:i)Naive method.ii)A 3-month moving average.iii)A 6-month weighted average using .1, .1, .1, .2, .2, and .3, with the heaviest weights applied to the most recent months.iv)Exponential smoothing using an α = .3 and a September forecast of 18. Done7:31<SEARCHMONTHLEE Chapter 4, Problem 6PThe monthly sales for Yazici Batteries, Inc., were asfollows:January 20February 21MarchAprilMayJuneSALES15141316JulyAugustSeptember 201718October 20November 21bartleby.comDecember 23ASKAA C√x MATH SOLVERa. Plot the monthly sales data.b. Forecast January sales using each of thefollowing:

a)Plot the monthly sales data. b)Forecast January sales using each of the following: i)Naive method. ii)A 3-month moving average. iii)A 6-month weighted average using .1, .1, .1, .2, .2, and .3, with the heaviest weights applied to the most recent months. iv)Exponential smoothing using an α = .3 and a September forecast of 18.

a)Plot the monthly sales data. b)Forecast January sales using each of the following: i)Naive method. ii)A 3-month moving average. iii)A 6-month weighted average using .1, .1, .1, .2, .2, and .3, with the heaviest weights applied to the most recent months. iv)Exponential smoothing using an α = .3 and a September forecast of 18.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Related questions

Q: What is meant by "aligning the data" in the context of the table of values below: Year Sales…

Q: Amex PLC has gathered following information on the sales of face mask from April 2020 to September…

A: Given, information gathered by PLC on the sales of face mask from April 2020 to September 2020. a)…

Q: The Holy Smokes Corporation sells altar candles world-wide. Quarterly sales dat on the Q1-4 Time…

A: Introduction: In order to estimate a linear trend line for annual sales using regression, the…

Q: We want to predict the selling price of a house in Newburg Park, Florida, based on the distance the…

A: Step 1:calculate the table with the above values Step 2: Step 3:if your satisfied with my answer…

Q: A manager uses a trend equation plus quarterly relatives to predict demand. Quarter relatives are…

A: Given information: The data represents the values of demand for the periods 1 to 9.

Q: Using excel. For the Hawkins Company, the monthly percentages of all shipments received on time over…

A: Given: For the Hawkins Company, the monthly percentages of all shipments received on time over the…

Q: The November 24, 2001, issue of The Economist published economic data for 15 industrialized nations.…

Q: The sales (in millions of dollars) for an 18-month period are as follows. Month Sales Month Sales 1…

A: Forecasting of time series data is done to predict the value for the future using the past trends.…

Q: The table and graph below both display the percentage of people in the United States who do not have…

A: The given data is Year 1963 1968 1994 2012 Percent without Health Insurance 24.3% 14.5% 15.8%…

Q: You are given the following quarterly sales information for ASTRA Company over the last 3 years.…

A: 1. Centered moving average To compute the central moving average, take the average to two…

Q: The amount of time adults spend watching television is closely monitored by firms because this helps…

A: Here AS PER POLICY I HAVE CALCULATED 3 SUBPART PLZ REPOST FOR REMAINING PARTS Here given survey is…

Q: Here are the data for the past 21 months for actual sales of a particular product: LAST YEAR THIS…

A: LAST YEARTHIS…

Question

Top of Form

a)Plot the monthly sales data.

b)Forecast January sales using each of the following:

i)Naive method.

ii)A 3-month moving average.

iii)A 6-month weighted average using .1, .1, .1, .2, .2, and .3, with the heaviest weights applied to the most recent months.

iv)Exponential smoothing using an α = .3 and a September forecast of 18.

Done
7:31
<
SEARCH
MONTH
LEE Chapter 4, Problem 6P
The monthly sales for Yazici Batteries, Inc., were as
follows:
January 20
February 21
March
April
May
June
SALES
15
14
13
16
July
August
September 20
17
18
October 20
November 21
bartleby.com
December 23
ASK
AA C
√x MATH SOLVER
a. Plot the monthly sales data.
b. Forecast January sales using each of the
following:

Expert Solution

This question has been solved!

Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.

This is a popular solution!

SEE SOLUTION Check out a sample Q&A here

Step 1: Given Information:

VIEW

Step 2: a) Plot the monthly sales data:

VIEW

Step 3: b. Forecast January sales using each of the following:

VIEW

Solution

VIEW

Trending now

This is a popular solution!

Step by step

Solved in 4 steps with 10 images

SEE SOLUTION Check out a sample Q&A here

Similar questions

Use the following sales data: Week Sales 1 30 2 35 3 56 4 85 5 95 6 45 7 65 8 74 9 73 10 39 Use naive method, a three-period moving average and exponential smoothing with an a=0.35 for forecast sales Compare the forecasts using MSE and MAD. Explain which one is the best. Make a forecast for weeks 11 and week 12 by using the optimal method.
The following chart shows the actual sales for the last 12 months for a given company. Assume that sales are best fit by a linear trend and you can use single linear regression to set up a forecasting model. Using the sales data answer below questions (justify your answers): A.What would be the typical linear regression equation for the number of sales? B.Make the sales forecast for period 15 of next year. C. Make the sales forecast for period 17 of next year. D. What is the standard error for the data?
If you want to use the build-down method to test a model using age (in number of years) and sex (male or female) to predict income, how large a data set would you need to collect: 8 8 8 8 20 50 40
For the data set, perform exponential smoothing with alpha = 0.1 to determine the forecast for week 20. week Sales (1000s of gallons) 1 17 2 21 3 19 4 23 5 18 6 16 7 20 8 18 9 22 10 20 11 15 12 22 13 31 14 34 15 31 16 33 17 28 18 32 19 30
Test the following claim. Identify the null hypothesis, alternative hypothesis, test statistic, critical value(s), conclusion about the null hypothesis, and final conclusion that addresses the original claim. Tests of older baseballs showed that when dropped 22 ft onto a concrete surface, they bounced an average of 236.82 cm. In a test of 40 new baseballs, the bounce heights had a mean of 231.3 cm. Assume that the standard deviation of bounce heights of all new baseballs is 4.24 cm. Use a 0.05 significance level to test the claim that the new baseballs have bounce heights with a mean different from 236.8 cm. Are the new baseballs different? What is the value of the test statistic? Identify the critical value(s) of z.
We want to predict the selling price of a house in Newburg Park, Florida, based on the distance the house lies from the beach. Suppose that we're given the data in the table below. These data detail the distance from the beach (x, in miles) and the selling price (y, in thousands of dollars) for each of a sample of fifteen homes sold in Newburg Park in the past year. The data are plotted in the scatter plot in Figure 1. Also given is the product of the distance from the beach and the house price for each of the fifteen houses. (These products, written in the column labelled "xy", may aid in calculations.) Distance from the beach, x (in miles) Selling price, y (in thousands of dollars) xy 5.0 270.1 1350.5 11.5 205.9 2367.85 5.9 309.4 1825.46 12.2 200.6 2447.32 2.6 307.1 798.46 5.9 266.0 1569.4 8.3 297.3 2467.59 18.3 224.2 4102.86 6.5 242.4 1575.6 12.1 192.6 2330.46 11.6 229.4 2661.04 9.5 230.9 2193.55 10.1 277.0 2797.7 13.5 270.8 3655.8 6.2…
A study was done to look at the relationship between number of vacation days employees take each year and the number of sick days they take each year. The results of the survey are shown below. Vacation Days 5 15 13 3 9 0 3 7 7 14 4 Sick Days 5 5 1 5 4 9 9 6 5 3 9 Use the model to predict the number of sick days taken for an employee who took 3 vacation days this year.Sick Days = ? (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: As x goes up, y goes down. The slope has no practical meaning since a negative number cannot occur with vacation days and sick days. For every additional vacation day taken, employees tend to take on average 0.40 fewer sick days. Interpret the y-intercept in the context of the question: The y-intercept has no practical meaning for this study. If an employee takes no vacation days, then that employee will take 8 sick days. The average number of sick days is…
Pa.n.n
the table shows the percent of households with internet access for selected years from 2009 and projected through 2015. Year Percent of households 2009 67 2010 70 2011 72.5 2012 75 2013 76.5 2014 77.2 2015 78 Use the model to predict the percent of households with internet access in 2022.
The following chart shows the actual sales for the last 12 months for a given company. Assume that sales are best fit by a linear trend and you can use single linear regression to set up a forecasting model. Using the sales data answer below questions (justify your answers): A.What would be the typical linear regression equation for the number of sales? B.Make the sales forecast for period 15 of next year. C. Make the sales forecast for period 17 of next year. D. What is the standard error for the data?
Suppose a firm has had the following historic sales figures. Year: 2016 2017 2018 2019 2020 Sales $2,570,000 $3,750,000 $4,380,000 $5,010,000 $5,520,000 What would be the forecast for next year’s sales using regression to estimate a trend?
The following time series shows the sales of supermarket chain over the last six months. Month Sales ($ 000) August 2021 250 Sep 2021 280 Oct 2021 295 Nov 2021 320 Dec 2021 380 Jan 2022 360 Develop a linear trend equation that can be used to forecast sales in Feb 2022. Forecast the sales in Feb 2021 using a three-period weighted moving average designed with the following weights: Nov 2021 weight 0.6, Dec 2021 weight 0.3 and Jan 2022 weight 0.1. Which method (A or B) is the best? Explain why.