Distance 6 in 12 in 18 in 24 in 30 in Intensity Distance 36 in 42 in 48 in 54 in 60 in Intensity Table 5.2 Using a program like Microsoft Excel, make a plot of the intensity measurements (in units of lux) versus the listance from the light bulb. Don't forget to clearly label each axis and add a title. Once ready, replace Figure 5.3 with your graph. Now we will apply statistical test called a linear regression to determine how close our data matches the inverse quare law. Using a spreadsheet program, we can quickly find the correlation coefficient, aka R2 value. A R2 = 1 means our data is perfectly linear, while R2 = 0 means there is no linear correlation . Recall that the intensity goes as I a 1/r2 ; how can we apply a linear regression to fit the data if the relationship is not linear? Instead of oplying a linear regression on (I vs r) we can define a new quantity that makes the previous equation "linear". Let be the inverse of the square distance, x = which makes the intensity linearly dependent on the variable x. I x x ill in table 5.3. (Hint: Put table 5.2 into Excel and you can quickly evaluate x.) Distance 6 in 12 in 18 in 24 in 30 in X= - 2 Distance 36 in 42 in 18 in $4 in 60 in 7 2 Table 5.3 lake plot of intensity vs . x. Include a linear regression line on the plot and record the R2 value . In Excel , if you click n a data point within a graph, you can choose an option called Add Trendline. Once you click, Add Trendline, hoose a Linear and check the boxes for Display Equation on Chart and Display R-squared value on chart. An quation and R2 value will appear on the graph. Once ready, replace Figure 5.3 with your graph. (Video showing how to fit a line to data in Microsoft Excel .)