Quarter 1 23 466 106 140 8273 119 165 912020 85 130 205 100Table shows UK sales of a particular model of car over three years (figures in 100,000 units)a)Use the technique of moving averages to find values for the trend component (T).b)Plot the original data and your trend values on a scatter diagram.20182019

Given the data of sales of a particular model of a car over three years in UK…

Answered: Quarter 12 2018 66 106 140 82 2019 73…

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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Perdisco Limited has shared their annual sales revenue over the last 6 financial years from 2010 to 2015. Year Sales ($ 000) 2010 4500 2011 5100 2012 4900 2013 5400 2014 5670 2015 6000 Using linear trend equation forecast the sales revenue of Perdisco Limited for 2016. Calculate the forecasted sales difference if you use 3-period weighted moving average designed with the following weights: 2013 (0.1), 2014 (0.3) and 2015(0.6). Please answer this question. this is not graded question. this is from book which is provided by my teacher for understanding concepts. Please solve this as i have finding difficulty in solving.
Fit a trend function y = A. B* to the following data. 2 3 4 5 y : 1.6 4.5 13.8 40 2 125.0
Give typed full explanation
The table lists weights (pounds) and highway mileage amounts (mpg) for seven automobiles. Use the sample data to construct a scatterplot. Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? Weight (lb) Highway (mpg) Which scatterplot below shows the data? A. 40- 20- 2000 5000 2795 3225 3470 32 34 28 Weight (lb) B. 40- 20+ 2000 D 5000 Weight (lb) 4085 4155 2225 25 23 38 C. ● 20+ 2000 ● ● ● ● 5000 Weight (lb) Is there a linear relationship between weight and highway mileage? A. No, there appears to be no relationship. B. Yes, as the weight increases the highway mileage decreases. C. No, there appears to be a relationship, but it is not linear. D. Yes, as the weight increases the highway mileage increases. 40- 20- 2000 3440 29 5000 Weight (lb)
The ordered pairs below give the winning times (in seconds) of a 100-meter freestyle swim race at a regularly-held competition from 1984 through 2012. (1984, 54.22) (2000, 52.13) (1988, 53.23) (2004, 52.14) (1992, 52.94) (2008, 51.42) (1996, 52.80) (2012, 51.30) (a) Sketch a scatter plot of the data. Let y represent the winning time (in seconds) and let t = 84 represent 1984. (b) Sketch the line that you think best approximates the data and find an equation of the line. (Round the slope and y-intercept to one decimal place.) y = (c) Use the regression feature of a graphing utility to find the equation of the least squares regression line that fits the data. (Round the slope and y-intercept to two decimal places.) y =
The table gives information about the number of people staying in a hotel each quarter in 2020 and in 2021.Calculate the 4-point moving averages for this information. year 2020 2021 quarter 1 2 3 4 1 2 3 4 people 261 353 372 290 193 309 292 202
Q. 16. step by stepsolutiomn please Scatter plots and Equations of Lines, Writing an Equation for a trend line Which graph shows the best trend line for the following data Practice (weeks) 6 8 10 12 14 16 18 Score 15.5 21.5 26.5 34 33 37 41
Given the graph below, what type of correlation would you predict there is between the variables? CAR PRICE DEPENDING ON AGE Price (dollars) 10000 9000 8000 7000 6000 5000 4000 3000 2000 1000- 4. 10 Age (years) O Positive correlation O Negative correlation O No correlation
Do all Please calculate: Parameters a and b Correlation coefficient Determination coefficient Write correlation equation Visualise data in Scatter chart Provide explanation of results Year Sales, MEUR (Yi) Employees with higher education (Xi) 2010 70 10 2011 90 12 2012 100 15 2013 80 13 2014 110 17 2015 120 20 2016 150 25 2017 200 25 2018 200 25
The ordered pairs below give the winning times (in seconds) of a 100-meter freestyle swim race at a regularly-held competition from 1984 through 2012. (1984, 55.12) (2000, 53.03) (1988, 54.13) (2004, 53.04) (1992, 53.84) (2008, 52.32) (1996, 53.70) (2012, 52.20) (a) Sketch a scatter plot of the data. Let y represent the winning time (in seconds) and let t = 84 represent 1984. (b) Sketch the line that you think best approximates the data and find an equation of the line. (Round the slope and y-intercept to one decimal place.) y = (c) Use the regression feature of a graphing utility to find the equation of the least squares regression line that fits the data. (Round the slope and y-intercept to two decimal places.) y = (d) Compare the linear model you found in part (b) with the linear model you found in part (c). The models are not similar.The models are similar.
Make box and whisker plot of average temperature of California in June, December, and march. Also, compare22 the results. year March (°C) June (°C) December (°C) 2004 7 22 -10 2005 8 23 -69 2006 10 24 -10 2007 9 23 -8 2008 8 25 -7 2009 10 26 -9 2010 27 -6 2011 11 29 -5 2012 16 29 -10 2013 17 29 -10 2014 13 29 -8 2015 14 25 -6 2016 17 28 -9 2017 15 27 -7 2018 18 29 -9 2019 14 26 -7 2020 13 26 -6
Life expectancy in the United States has been rising since the nineteenth century. The table shows the U.S. life expectancy in selected years. Year 1950 1960 1970 1980 1990 2000 Life expectancy at birth 68.2 69.7 70.8 73.7 75.4 77 a. Let t represent the number of years after 1950, and plot the data. Draw a line a best fit for the data points. 80+ 76- 5 10 15 20 25 30 35 40 45 50 Draw: 72+ 64- 60+ 56 52 48- 44 Clear All

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