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

 P1 Introduction information & assignments P2 excel line plot information & assignments >P3 find slope and intercept from line plot < (2 parts) Answers to be submitted P4 Fit line (2 parts) Answers to be submitted P5 Fit line information & assignments P6 Plot non linear information & assignments P7-Which function Answers to be submitted P8 non linear fit Answers to be submitted P9 logarithms 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