Final answer:
The Consumer Price Index (CPI) for the years 2004, 2008, and 2011 is 188.9, 215.3, and 224.9 respectively. The given regression model can be evaluated by adding these data points and assessing the correlation coefficient (r = 0.9018). The Bureau of Labor Statistics implements several methods to avoid biases in the CPI.
Step-by-step explanation:
To calculate the Consumer Price Index (CPI) for each year, you will typically divide the cost of a fixed basket of goods and services in the year of interest by the cost of the same basket in a base year, then multiply by 100 to convert it to an index. However, in this case, we are provided the CPI values directly. For the years 2004, 2008, and 2011, the CPI values are 188.9, 215.3, and 224.9 respectively.
To see how additional data points affect a regression model, you can insert these CPI values into a scatter plot and calculate the least-squares line as per instructions b). The given regression equation is ý = -4436 + 2.295x. By finding the correlation coefficient (r = 0.9018), we can assess the strength and direction of the linear relationship between the years and CPI values. A correlation coefficient close to 1 implies a strong positive linear relationship. You can then discuss the significance of r and how the fit changes with the addition of new data points.
The Bureau of Labor Statistics utilizes methods to avoid biases in the CPI measurement, such as frequently updating the basket of goods to reflect current consumption patterns, using geometric mean price calculations, and accounting for consumer substitution.
Finally, it's essential to differentiate among various price indices such as the CPI, PPI, International Price Index, Employment Cost Index, and GDP deflator, as each measures changes in the price level of a different set of goods and services and serves varied purposes.