Math Problem Statement
Fit trend line to the following time series by the least square method.
Year(t)
2009
12
2010
20
2011 2012
28
32
2013
50
Production (in lakh tons)
Obtain the trend value of production for 2018.
91.89
a
b
15927.8
C
90.00
d
32203.2
Solution
To fit a trend line to the given time series data by the least squares method and obtain the trend value for 2018, we need to follow these steps:
-
**Organize the dataTo fit a trend line to the given time series data by the least squares method and obtain the trend value for 2018, we need to follow these steps:
-
**Organize the **
- Years () and Production ():
Year (t) Production (P) 2009 12 2010 20 2011 28 2012 32 2013 50 -
Define the trend line equation: The trend line can be defined as: where is the production, is the year, is the intercept, and is the slope.
-
Calculate the necessary sums for the least squares method:
Let's denote:
Given:
Calculate these sums:
-
Calculate the coefficients and :
Using the formulas:
Calculate :
Calculate :
-
Trend line equation:
-
Calculate the trend value for 2018:
So, the trend value of production for 2018 is approximately lakh tons.
Do you want more details or have any questions?
Here are five questions you might ask:
- How do you determine the best fit line in the least squares method?
- Can you show how to calculate the sums in more detail?
- What other methods can be used to fit a trend line to time series data?
- How do you interpret the coefficients and in the trend line equation?
- Can this method be used for non-linear trends?
Tip: When fitting a trend line, always check if a linear model is appropriate for your data or if a different type of model might provide a better fit.
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Math Problem Analysis
Mathematical Concepts
Statistics
Linear Regression
Least Squares Method
Formulas
Linear regression equation: P = a + bt
Formula for slope (b): b = (n * ∑(t*P) - ∑t * ∑P) / (n * ∑(t^2) - (∑t)^2)
Formula for intercept (a): a = (∑P - b * ∑t) / n
Theorems
-
Suitable Grade Level
High School