Background 1. Interpolation of a Data Set
When might you want to interpolate a set of data?
For example, if you wished to divide I(q) for a concentrated suspension by I(q) for a dilute suspension 
to obtain S(q), you need to think about how to do it properly.

I(q)conc might have been measured at 15 q values while I(q) dil at 12,
and the actual q values at which data was taken might all be different (or atleast some might be different).

Figure out how to do a linear interpolation of your data (in Mathematica),
so that all your data is converted to a set of y values at one set of evenly spaced x values.

Background 2. Read up on the structure factor.

Question 1 : This is a warm-up exercise for Question 2.
x1        y1=f(x1)
0.0        0.01
0.5        1.13
1.0        3.98
1.5         8.93
2.0        16.30
2.5        24.67

x2        y2=g(x2)
0.3        0.11
0.5        0.24
1.0        1.04
1.6        2.50
2.3        5.26
2.5        6.33
2.7        7.21

Do a linear interpolation of both data sets so they can be evaluated at a single set of evenly spaced x values. Then plot the function y3=f(x)/g(x) vs x.

Question 2: For this question you will need to download the data on the Course Materials page (Glatter_data.xls).
Please note a subtle point about the normalization of the intensities in the data - each curve I(q) is normalized with respect to I(q=0.009 1/nm) i.e. the numbers given are I(q)/I(q=0.009 1/nm). Save your data analysis in a file. I might wish to see it.
(a) Assuming identical spheres, write down the form factor. Fit the data at lowest volume fraction (5%) to the form factor. Comment on the goodness of fit.

(b) Use ALL the data in the Excel file. Do any linear interpolations necessary, and plot S(q) vs q for ALL BUT ONE concentration using only the data and no form factor. I prefer all S(q)'s on one plot.

(c) Plot the first peak of the structure factor vs. concentration.