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Sagot :
Answer:
Kindly check explanation
Step-by-step explanation:
Given the data :
t __1 2 3 4 5
yt_ 6 10 8 13 15
Using technology to produce a linear model :
The linear model obtained shows a positive linear pattern exist for the time series data :
The parameters for the line that minimizes MSE for the then series is :
y = 2.1t + 4.1
Where, slope = 2.1 ; intercept = 4.1
The mean squared error :
Sum of squared estimate of error = 9.1
Mean squared error = √9.1
Mean squared error = 3.02
Forecast for t = 6
y = 2.1t + 4.1
y = 2.1*6 + 4.1
y = 12.6 + 4.1
y = 16.7
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