SUMMARY and GLOSSARY
This is an attempt at an outline or summary of the online LONCAPA lab. If it seems useful then the student can keep this page open as a guide. None of the material on this page is required reading.
There are
9 parts to the lab and the student should visit each part
at least once 


4 of the parts require
answers either based on material you should master or results from the
requested analysis 


5 informational pages with
assignments 



One Excel spread sheet must
be built as you work through the material 




Contains the following work
sheets 





straight line 





fit 





non linear 





non linear fit 





logarithms 

Lab parts
information & assignments 

information & assignments 

Answers to be submitted 

Answers to be submitted 

information & assignments 

information & assignments 

Answers to be submitted 

Answers to be submitted 

information & assignments 
Review your understanding of functions, variables and parameters 

function 
Relationship between quantities. How quantities depend on each other. 
variables 
Measurable quantities that vary in an experiment. 
parameters 
Fixed quantities: coefficients in functions, physical constants (g), and other quantities that define functions (powers or exponents). 


Review how you determine values for the quantities of interest in an experiment. Here we want to highlight that some quantities are directly measured (length), some quantities are simple combinations of directly measured quantities (velocity= dist./time) and some quantities require a sophisticated analysis of the data (slope of a straight line fit [x vs t] to find a velocity). 

direct measurement 
The process where a quantity of interest is measured by an instrument that provides the result. An example is measuring length with a ruler. 
indirect measurement 
When several direct measurements and other indirect measurements are combined to yield the result. 
reference 
Using data from a book, publication or internet site. For example, using the value g=9.8 as provided by your text book 
Coffee filter experiment is a good illustration because the terminal velocity that one uses in the final analysis is determined by a somewhat complex analysis of the data from the falling filters while the masses of the filters are directly measured. 



In looking at models for data sometimes we have a specific model that we are testing and other times we examine a more general model. Here again the coffee filter experiment is relevant. One model for how terminal velocity is reached allows for only one quantity to be adjusted (parameter C), while a more general model doesn’t require that the functional relationship be restricted to velocity squared so that there are two parameters that need to be determined (B, a). 



Review of the straight line function using an EXCEL spread sheet. 

slope 
Straight line parameter that determines the tilt of the line, rise/run 
intercept 
Value of the function when evaluated at zero. 


Change a line by manually adjusting slope and intercept to see how one can match a line to data. 

manual fit 
self adjusted data and line 


Examine how to evaluate if the line matches the data 

student based quality factor 
your statement as to how one judges when the line best matches the data 


crude chi squared or quality factor 
somewhat intuitive definitionè A cumulative assessment of the difference between the data and the curve. The distance away from the curve is evaluated for each data point and an overall judgment made based on all these distances. 


Fitting data using a straight line function. 



general functions 

polynomial functions 
Sum of terms each term has a coefficient and the independent variable raised to an integer power._{} 
exponential function 
functions that involve e raised to a power that depends on the independent variable _{} 


General curve fitting: Fit data to a function. 



Logarithms 







