2. Using the same data above, compute for the WMA using the below weights. Compute for the MAD, MSE and MAPEH.Weights Period 5 Last Month 4 Two Months Ago 3 Three Months Ago 2 Four Months Ago 1 Five Months Ago Develop--pdfForecast= Open with Google DocsMonth Unit Sales12012413041451551101148.1569.121101181111712118Page1 / 213119N2.3. pdfOpen with Google Docs1451551107.1148156121101181111712118131191411315Page17 21.6.9.

Given Information: Consider the given data: Month Unit Sales 1 120 2 124 3 130 4 145 5…

2. Using the same data above, compute for the WMA using the below weights. Compute for the MAD, MSE and MAPEH. Weights Period 5 Last Month 4 Two Months Ago 3 Three Months Ago 2 Four Months Ago 1 Five Months Ago

2. Using the same data above, compute for the WMA using the below weights. Compute for the MAD, MSE and MAPEH. Weights Period 5 Last Month 4 Two Months Ago 3 Three Months Ago 2 Four Months Ago 1 Five Months Ago

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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A legal case rested on whether a patent witness' signature was written on top of key text in a notebook or under the key text. The zinc measurements for three notebook locations on a text line, on a witness line, and on the intersection of the witness and text line-are provided in the table below. Complete parts a through c below. Text line Witness line 0.319 0.384 0.327 Intersection Find the test statistic. HT-1400 0.321 0.307 0.327 t = (Round to two decimal places as needed.) Find the p-value. p-value= (Round to three decimal places as needed.) a. Use a test (at a = 0.02) to compare the mean zinc measurement for the text line with the mean for the intersection. Let μ represent the mean zinc measurement for the text line, let uw represent the mean zinc measurement for the signature of a patent witness, and let μ, represent the mean zinc measurement for the intersection line. Select the correct hypotheses below. OA. Ho: HT-Hw=0, H₂: HT μ₁0 OB. Ho: HT-H₁0, H₂: HT-H₁0 O C. Ho: HT-HW = 0,…
4. Define the following terms and give example each: Population Sample Survey 1. 11. 11. Iv. Census V. Parameter VI Statistic
From September 1980 to August 1982, 50 premature infants were admitted to the Neonatal ICU of Lungsod ng Kabataan Children’s Hospital due to severe hyaline membrane disease. Data on the weights of these infants are shown below. Table X. Weights of Premature Infants with Severe Hyaline Membrane Disease Treated with Assisted Ventilation Weights in Grams Number of Patients 800-1000 1001-1200 1201-1400 1401-1600 1601-1800 1801-2000 2001-2200 2201-2400 3 4 6 5 5 8 9 10 Total 50 Find the following: Final Answer Interpretation Computation Mean Median Mode Range SD D6 P40 Q3
Sheet 2 a. Using information from sheet 1, construct, for the two data sets, the following: i. Histogram using relative frequency
Question 15 to 12 13 14 i5 16 17 18 19 20 10 11 data Based on the boxplot above, identify the 5 number summary Question Help: DVideo D Post to forum Submit Question
The table provided below shows paired data for the heights of a certain country's presidents and their main opponents in the election campaign. Construct a scatterplot. Does there appear to be a correlation? Click the icon to view the data table for election heights. Construct a scatterplot. Choose the correct graph below. OA. В. C. D. 200- 200- 200- 200- 160+ 160 President's height 160+ 160 President's height 160+ 160 President's height 160- 160 President's height 200 200 200 200 Does there appear to be a correlation between the president's height and his opponent's height? A. Yes, there appears to be a correlation. As the president's height increases, his opponent's height increases. B. Yes, there appears to be a correlation. The candidate with the highest height usually wins. C. Yes, there appears to be a correlation. As the president's height increases, his opponent's height decreases. D. No, there does not appear to be a correlation because there is no general pattern to the data.…
2. The following data was collected from 1 bag of Hershey Kisses®. Each Kiss® was weighed in grams with the wrapper and recorded in the table below. Hershey claims that there are 368 grams of chocolate in one bag. Hershey Kiss Weights in Grams 4.76 4.72 4.74 4.55 4.91 4.74 4.78 4.71 4.80 4.78 4.78 4.75 4.79 4.82 4.91 4.83 4.68 4.74 4.70 4.80 4.70 4.76 4.70 4.83 4.93 4.74 4.84 4.82 4.76 4.77 4.72 4.78 4.83 4.75 4.74 4.68 4.84 4.71 4.71 4.76 4.66 4.78 4.73 4.74 4.92 4.77 4.80 4.79 4.86 4.64 4.78 4.70 4.75 4.78 4.76 4.83 4.66 4.77 4.83 4.78 4.69 4.81 4.68 4.78 4.88 4.72 4.85 4.85 4.81 4.74 4.80 4.82 4.84 4.70 4.85 4.70 4.81 4.72 4.79 4.73 4.61 What could be some reasons for variation in the weights of the Kisses®? Note: Take time answering this one. There are lots of things to consider here and I'll be looking for a well thought out answer with several given reasons contributing to the variation. Of course, the wrappers and tags could vary but what about…
Question1) given below: The annual precipitation data (mm) recorded at Kumköy. Istanbul in period 1952-1990 are 661 676 555 892 679 556 760 716 585 733 867 893 520 913 648 639 908 707 608 725 675 748 893 1139 815 685 907 932 919 1230 720 658 737 837 731 1042 926 471 763 a) Plot the histogram and frequency histogram dividing the data into six equal class intervals. b) Investigate the effect of the number of class intervals using wider and narrower intervals. c) Plot the cumulative frequency distributions. d) Estimate the parameters for the central value of the annual precipitation. e) Estimate the parameters representing the dispersion of the data. f) Compute the skewness coefficient. Can the data be considered to be symmetrical?
2.1
Exhibit 1.1 18 13 10 16 14 13 17 15 13 11 14 14 11 10 12 12 11 13 15 9 12 13 16 8 15 Using the numbers in Exhibit 1.1, determine the inter quartile range? And why?
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i. ii. Table 1 iii. Top 15 countries with the highest wind power Country iv. Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 China United States Germany United Kingdom India Brazil Spain France Canada Sweden Italy Turkey Australia Netherlands Mexico Gigawatt hours (GWh) 467037.4 341818.0 132102.0 75369.1 63522.3 57050.0 56444.0 39791.9 35638.0 27526.0 18676 14304 please solve iv only by minitabe 12080 10607 b. Construct a 95% confidence interval on the mean wind power. Calculate the sample mean and variance. Write the appropriate confidence formula and the assumptions. Calculate the confidence interval manually. Perform the analysis by Minitab. Copy your output and insert it into your report (use the latest Minitab version and do not write/type the output). 8951 7 4