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f(x) = − 0.08 x + 168.44
R² = 0.79
September Sea Ice Extent (1,000,000 sq km)
Year
September Sea Ice Extent (1,000,000 sq km)
2. Plot a scatter plot of the data. In your own words, describe the data.
The data seems to be on a down trend.
3. Fit a linear trend to the dataset. Based on the linear trend, what is the rate of change of the
Arctic sea ice? What is the intercept? What is the R2 value for this trend?
The rate of change is -8.12*10^-2 (1,000,000 sq km) per year.The intercept is 168.44. The R-
squared value is .7935
4. Based on the rate calculated in question 3. When do you think that Arctic Sea Ice area will
reach zero? Discuss any issues that may occur with these types of models (is it realistic? Why
or why not?)
Based on the model, the artic sea ice area will reach zero in 2074. I believe the model is realistic
if no action is taken to control the loss. This is a good model to show us what will happen if
action isn't taken soon.
5. Using the "Regression" function (instructions provided in assignment 4) calculate an error
on the slope and the intercept
.
The standard error on the intercept is 12.9 and the standard error on the slope is 6.47*10^-3
6. Calculate the predicted data and the residuals from your fit. Plot the residuals on a scatter
plot. What do you observe about the residuals? Comment on the goodness of fit. Provide the
graph in your write up.
The residual seem to be scattered which indicated that the equation is a good fit for this data.