{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 1. Keeping a Lab Notebook" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1.1 Introduction" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Keeping a lab notebook is a very important skill for a scientist. Your lab notebook should be a detailed record of what you did in the lab. It should explain what you measure and why. It should also include analysis of the measurements. Since no experiment is perfectly precise, you should account for uncertainties in your measurements, calculations, and comparisons. By refering to your notebook, you should be able to tell what you did weeks or months later. For more complicated experiments, the notebook will help you synthesize results from different days so that you can make progress. It is also a place to record ideas about how you will proceed. A good lab notebook is the basis for publishing your results. For the purpose of a class, the lab notebook should contain all of the information that you need to write a lab report. \n", "\n", "There are two somewhat competing goals when keeping a lab notebook. First, you should write down things as they occur so that you don't forget them. Second, your notebook needs to be reasonably neat and organized so that you can make sense of it later. The guidelines below will help you accomplish both of these goals." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1.2 Layout" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The entry for each lab should start with a descriptive title (not just the lab number), the names of group members, and the date. If the lab work extends over multiple days, the date should be indicated for each new day. \n", "\n", "Number each page. If you are using loose pages, this will help in the event that they get shuffled. Initially, only use the front side of each page. This will leave room on the back sides for additions. \n", "\n", "You may use a pencil, which allows you to make small corrections, but be sure not to write too lightly. However, you should not erase (or throw away) a large section that you think may be mistake. Instead, cross out the work and make a note about what you think is wrong. You may later find this information useful. It may keep you from making the same mistake again. \n", "\n", "The noteook should be organized by experiment (some labs will involve multiple experiments). For each experiment, there should be a procedure, data, and analysis." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.2.1 Procedure" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In your lab notebook, you should describe the procedure used in enough detail that you could repeat the experiment the same way much later without refering to anything else. Do not just record a bunch of data without explaining what you've done. Leave enough space that you can make additions or modifications to the procedure. \n", "\n", "You should describe the equipment used in the lab. As the saying goes, a picture is worth a thousand words. You should make a well-labeled diagram of how the equipment is set up. Usually, the diagram of the setup or an additional diagram should show what was measured. If a larger piece of equipment has a manufacturers name, model number, and serial number, those should be recorded. With the serial number, you can get the same equipment back if you need to repeat a measurementor track down a problem with with a piece of equipment. \n", "\n", "You should also describe how uncertainties are determined (see Ch. 2). Was a quantity measured multiple times so that the standard deviation can be calculated? If you made a single measurement of a quantity, how did you estimate its uncertainty? " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.2.2 Data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You should clearly record quantities that you measure directly. The data should be labeled and organized. Often, putting the data in a table is useful. It is helpful to use the same notation that was used in class. \n", "\n", "Be sure to include units for each measurement. If you are measuring a quantity a single time, you should give an estimate of its uncertainty." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 1.2.3 Analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Describe any processing of the data. This will typically include calculations and graphs (see Ch. 4). You should explain your work. In particular, you should give the equations that are used for calculations. Throughout the analysis, you should account for uncertainties (see Ch. 2 and 3). Usually, you will compare measured values with accepted values (measurements by others) or theoretical values, taking uncertainties into account. \n", " \n", "If possible, do the analysis immediately. That way, if there is a problem with your data, you'll be able to do something about it." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1.3 Checklist for Lab Notebook" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Use the following checklist to make sure that your lab notebook has the necessary elements. However, you should also be sure to include enough text to make sense of these pieces. \n", "\n", "**Layout:** \n", "   ◻ Descriptive title \n", "   ◻ Names \n", "   ◻ Dated (each day) \n", "   ◻ Pages numbered \n", "   ◻ Use fronts of pages initially \n", "\n", "**Procedure:** \n", "   ◻ Detailed description \n", "   ◻ Well-labeled diagrams \n", "   ◻ Manufacturer, model, serial number for large items \n", "   ◻ Description of how uncertainties are determined \n", "\n", "**Data:** \n", "   ◻ Organized and labeled \n", "   ◻ Units given \n", "   ◻ Uncertainties included for single (not mulitple) measurements \n", "\n", "**Analysis:** \n", "   ◻ Graphs with fits, if appropriate \n", "   ◻ Equations used \n", "   ◻ Calculations (including uncertatainties for multiple measurements) \n", "   ◻ Uncertainty propagation \n", "   ◻ Comparisons with accepted or theoretical values" ] } ], "metadata": { "kernelspec": { "display_name": "SageMath (stable)", "language": "sagemath", "name": "sagemath" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.15" } }, "nbformat": 4, "nbformat_minor": 1 }