Preview of the Data

The data on the first chart, Nominal Price vs. CSD Sales, will not yield a meaningful linear or logarithmic equation, because the data curves over the Y-axis, which cannot be accurately approximated by either line (or any function of quantity). Therefore, the results from this chart will not be well explained by the line and the R2 value will be low. Further, the upward slope of the data does not conform to the law of demand and thus cannot accurately represent reality. However, the second chart, CSD Sales vs. Real Price, does follow a downward pattern that the linear and logarithmic lines can approximate. Further, because it does not appear to be a hyperbolic concave line, the linear equation will likely be more accurate.

Based on the industry and the fact that the data represent time, both charts do make sense. The first chart hooks up and to the left because the industry raised prices, causing a decline in demand from 10,239,400,000 to 9,364,500,000; however, this did move did not approximate a slide because the prices were becoming more inflated for every consecutive data point. The second chart compensates for this by plotting the inflation-adjusted real price against quantities to reveal a realistic line representing industry demand. This can be seen in the way that the latter price increases caused a slide to the left on the demand curve. Also note that the more recent data points fall under the previous demand line, which could mean that the demand curve for the industry has shifted downward due to the damaging trend towards healthier beverages.

Industry Quantity vs. Nominal Price Regression Regression Statistic | Value | Significance | Sign of the Coefficient | Positive | Not Significant | To conform to the Law of Demand, the slope coefficient of demand must be negative. This is because the quantity that customers demand