Homework Answers
Equation of the best fit line is written as: y = mx + b.
Here m is the slope and b is the y-intercept.
Equation of plant growth for fertilizer 1 is: y = 3.11x + 1.0 -----Eq 1,
Equation of plant growth for fertilizer 2 is: y = 2.37x + 3.6 -----Eq 2
Slope (m) for equation 1 is higher than that of equation 2. This indicates that the rate of growth is higher when fertilizer 1 is used as compared to that of fertilizer 2 by a factor of 1.31.
Y-intercept (b) refers to measurement of growth at t(time) = 0. Comparison of y-intercepts of the two equations indicates that before the application of fertilizer, plants in the second experiment had higher growth than plants in the first experiment by a factor of 3.6.
R2 value for Eq 1 is 0.9935
R2 value for Eq 2 is 0.9155
R2 value for a best-fit equation indicates how close the data are to the fitted regression line. The comparison indicates that data is closely fit to the equation for the case of fertilizer 1 than that of fertilizer 2.
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The same data will be used for the next 3 short essay questions. The following table...
Consider the following time series data. Week 1 2 3 4 5 6 Value 17 13...
Consider the following time series data.
Week
1
2
3
4
5
6
Value
17
13
15
11
15
13
(a)
Choose the correct time series plot.
(i)
(ii)
(iii)
(iv)
- Select your answer -Graph (i)Graph (ii)Graph (iii)Graph
(iv)Item 1
What type of pattern exists in the data?
- Select your answer -Horizontal PatternTrend PatternItem
2
(b)
Develop a three-week moving average for this time series.
Compute MSE and a forecast for week 7.
If required, round your answers...
Consider the following time series data. Week 1 2 3 4 5 6 Value 16 14...
Consider the following time series data. Week 1 2 3 4 5 6 Value 16 14 16 11 17 14 Develop a three-week moving average for this time series. Compute MSE and a forecast for week 7. Week Value Forecast 1 16 2 14 3 16 4 11 5 17 6 14 MSE = Week 7 Forecast= Use trial and error to find a value of the exponential smoothing coefficient α that results in a smaller MSE than what you...
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Run a regression analysis on the following data set, where y is the final grade in...
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Problem 15-07 (Algorithmic) Refer to the gasoline sales time series data in the given table. 1...
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1. Problem 1. Given a data set (X, Y), use the least squares techniques to find the best ftting c...
1. Problem 1. Given a data set (X, Y), use the least squares techniques to find the best ftting curve y-/() within the exponential family v ab) where a,b ER. The data set is given by, where, χ-io, 0.2, 0.4, 0.6, 08, 09, 1, 12, 14, 1.6] y 2, 2.5, 3.1, 3.9, 4.8, 5.4, 6, 7.5, 9.3, 11.6] In particular: a) Going from the original data (x,Y) set to the transformed data set (X, Z) with z(Y)-In (Y), verify that...
Consider the following time series data.
Week
1
2
3
4
5
6
Value
17
13
15
11
15
13
(a)
Choose the correct time series plot.
(i)
(ii)
(iii)
(iv)
- Select your answer -Graph (i)Graph (ii)Graph (iii)Graph
(iv)Item 1
What type of pattern exists in the data?
- Select your answer -Horizontal PatternTrend PatternItem
2
(b)
Develop a three-week moving average for this time series.
Compute MSE and a forecast for week 7.
If required, round your answers...
2. Use the data provided to answer the following questions. Data for Last Week: Values LY POS Sales TY POS Sales LY POS Qty TY POS Qty LY Next Week Sales LY Next Week QTY LY Next 13 QTY $60,000 $56,250 11,625 10,901 $58,824 11,400 140,500 a. What is the average price for last year (LY), this year (TY)? b. What are the percent changes year-over-year (YOY) in sales and quantity? C. What would you suggest should be an expected...
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Problem 15-07 (Algorithmic) Refer to the gasoline sales time series data in the given table. 1 Week Sales (1000s of gallons) 17 2 20 21 11 14 22 a. Compute four-week and five-week moving averages for the time series. Round your answers to two decimal places. 4-Week 5-Week Moving Average Moving Average Week Sales 17 9 10 11 12 17 DE 23 21 C C 14 22 b. Compute the MSE for the four-week and five-week moving average forecasts. Round...
1. Problem 1. Given a data set (X, Y), use the least squares techniques to find the best ftting curve y-/() within the exponential family v ab) where a,b ER. The data set is given by, where, χ-io, 0.2, 0.4, 0.6, 08, 09, 1, 12, 14, 1.6] y 2, 2.5, 3.1, 3.9, 4.8, 5.4, 6, 7.5, 9.3, 11.6] In particular: a) Going from the original data (x,Y) set to the transformed data set (X, Z) with z(Y)-In (Y), verify that...
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