(Graphs already made, Provide interpretation of results) 2- Make time series sca
ID: 343842 • Letter: #
Question
(Graphs already made, Provide interpretation of results)
2- Make time series scatter plots ofall five varables (five graphs) Insert trend line, equation, and R-squared. Observe graphs and provide interpretation of results. Time Series Plot of DEMAND 0.1173x+14.3 R2-0.47752 25 20 10 10 15 20 25 30 Time Period (EXPLANATION) Time Series Plot of ADV 0.0916x+5.8024 R: 0.66302 10 15 Time Period 20 25 35 (EXPLANATION) Time Series of DIFF y = 0.0163x-0.0552 R2=0.18164 0.8 0.6 0.4 0.2 35 0.2 -0.4 0.6 0.8 Time Period (EXPLANATION)Explanation / Answer
Graph A – Demand
The slope of regression line (b) is positive, thus there is positive or direct relationship between period and demand. The plot also shows seasonality in demand.
Coefficient of determination, R2 = 0.47752, Explains likelihood of future data points or demands that fall within the results of predicted outcomes. Thus, for given data 47.75% of added sample data points will fall within the results predicted outcome from the regression line.
Graph B – ADV
The slope of regression line (b) is positive, thus there is positive or direct relationship between period and ADV. The plot also shows seasonality and randomness both in ADV values.
Coefficient of determination, R2 = 0.66302, Explains likelihood of future data points or demands that fall within the results of predicted outcomes. Thus, for given data 66.30% of added sample data points will fall within the results predicted outcome from the regression line.
Graph C – DIFF
The slope of regression line (b) is positive, thus there is positive or direct relationship between period and DIFF. The plot also shows randomness in DIFF values.
Coefficient of determination, R2 = 0.1816, Explains likelihood of future data points or demands that fall within the results of predicted outcomes. Thus, for given data 18.16% of added sample data points will fall within the results predicted outcome from the regression line. The relationship is weak.
Graph C – AIP
The slope of regression line (b) is positive, thus there is positive or direct relationship between period and AIP. The plot also shows randomness in AIP Values.
Coefficient of determination, R2 = 0.08425, Explains likelihood of future data points or demands that fall within the results of predicted outcomes. Thus, for given data 8.43% of added sample data points will fall within the results predicted outcome from the regression line. The relationship is very weak.
Graph E – Price
The slope of regression line (b) is negative, thus there is negative or indirect relationship between period and price. The plot also shows steadiness in price values.
Coefficient of determination, R2 = 0.14743, Explains likelihood of future data points or demands that fall within the results of predicted outcomes. Thus, for given data 14.74% of added sample data points will fall within the results predicted outcome from the regression line. The relationship is weak.
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