a) Plot the above data on a graph. Do you observe any trend, cycles, or random variations?
b) Starting in year 4 and going to year 12, forecast demand using a 3-year moving average. Plot your forecast on the same graph as the original data.
c) Starting in year 4 and going to year 12, forecast demand using a 3-year moving average with weights of .1, .3, and .6, using .6 for the most recent year. Plot this forecast on the same graph.

(2) The monthly sales for Telco Batteries, Inc., were as follows:
Month Sales
January 20
February 21
March 15
April 14
May 13
June 16
July 17
August 18
September 20
October 20
November 21
December 23

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.
v) A trend projection.
c) With the data given, which method would allow you to forecast next March's sales?

(3) Dell uses the CR5 chip in some of its laptop computers. The prices for the chip during the past 12 months were as follows:
Month Price per Chip
January $1.80
February $1.67
March $1.70
April $1.85
May $1.90
June $1.87
July $1.80
August $1.83
September $1.70
October $1.65
November $1.70
December $1.75

a) Use a 2-month moving average on all the data and plot the averages and the prices.
b) Use a 3-month moving average and add the 3-month plot to the graph created in part (a).
c) Which is better (using the mean absolute deviation): the 2-month average or the 3-month average?
d) Compute the forecasts for each month using exponential smoothing, with an initial forecast for January of $1.80. Use α = .1, then α = .3, and finally α = .5. Using MAD, which α is the best?

How would I plot a graph for the following RLC circuit which shows the magnitude of Z (the input impedance) as a function of frequency from 10Hz to 10KHz?
See attached file for full problem description.

Refer to the graph given below and identify the graph that represents the corresponding function. Justify your answer.
y = 4^x
y = log4x
Plot the graphs of the following functions. Scan the graphs and post them to the Facilitator along with your response.
1. f(x) = 5x
2. f(x) = 4x+2
3. f(x) = (1/3)x
4. f(x

1. Graph the equation by plotting points
y = -2x
2. Graph the equation by plotting points.
y = -3x
3. Graph the equation by plotting points.
y = x - 3
4. Graph the equation by plotting points.
y = x + 3
5. Use the following equation. Fill in the table. Determine whether the graph has a positive o

Please see attachment for data.
a.) Plot the data in the attachment on a graph. Do you observe any trend, cycles, or random variations?
b.) Starting in year 4 and going to year 12, forecast demand using a 3-year moving average. Plot your forecast on the same graph as the original data.
c.) Starting in year 4 and going to y

Identify at least three specific trends related to any of the 4Ps and name a company impacted by each of the trends.
Additionally, identify the source of these trendsand what future trends will impact the companies you named.

Consider a finite-support signal
x(t) = t 0<=t<=1
and zero elsewhere.
- Using Matlab, plot x(t+1)
- Using Matlab, plot x(-t+1)
- Add the above two signals together and plot the new signal y(t).

Can you please explain what I need to do to complete this? I do not understand how to plot the figures within the spreadsheet or calculate them.
Sample 1 2 3 4 5 Xbar R
1 1.55 1.58 1.64 1.67 1.50 1.588 0.17
2 1.52 1.62 1.71 1.74 1.60
3 1.47

Hi. I've been given a table of data with the following columns:
Date Time (hours) Rainfall(mm)
In each column, values have been given.
The first question that is required of me is to plot rainfall intensity (mm/h) against time in hourly steps. I think this is pretty straight forward.
The second q

Control charts are graphs that show upper and lower limits for a process an organization wants to control, depicting a graphic presentation of data over time. A control chart can indicate a process is out of control by showing the target line, andplotting actual performance against the line (Render, Stair & Hanna, 2011). When t

A new fashion in clothes is introduced. It spreads slowly through the population at first but then speeds up as more people become aware of it. Eventually those willing to try the new fashions begin to dry up and while the number of people adopting the fashion continues to increase. It does so at a decreasing rate. Later the fas