Name: graphs, curve fit, and standard deviation
Uploaded: 2020-03-26T07:22:24.000Z
Duration: 4 min 34 s
Channel: JoVE

K12 Standards

Texas Essential Knowledge and Skills

High School

Chemistry

CHEM.1

CHEM.1.D

Scientific Measurement and Lab Skills

La traduction des résultats expérimentaux de points de données en représentations visuelles, comme des graphiques, est essentielle pour déterminer la relation entre deux ou plusieurs propriétés. Ces propriétés sont appelées variables. Lorsqu’il y a deux variables, un graphique créé à partir des données est dit bidimensionnel. Le graphique a deux axes. La variable indépendante est tracée sur l’axe des abscisses, et la variable dépendante est tracée sur l’axe des ordonnées.
Prenons, par exemple, cet exemple de données pour la température et le volume d’un gaz. Le volume du gaz dépend de la température. Ainsi, nous tracerions la température mesurée sur l’axe des x et le volume sur l’axe des y.
Lorsqu’il y a plusieurs points de données avec la même valeur x, par exemple si nous mesurons le volume plusieurs fois à une même température, nous calculons également l’écart-type de ces mesures. L’écart-type est une valeur statistique, qui indique la quantité de variation présente dans un ensemble de valeurs.
L’écart-type est calculé à l’aide de cette formule, où n est le nombre de points de données, x bar est la valeur moyenne des points de données et xi représente chaque point de données individuel. Vous pouvez calculer l’écart-type à la main, ou un tableur peut le calculer automatiquement. Plus l’écart-type est proche de 0, plus les points de données sont proches de la valeur moyenne. Si l’écart type est égal à 0, tous les points de données saisis ont la même valeur.
Regardons les valeurs moyennes et les écarts-types des mesures de volume à chaque température de notre ensemble de données. Nous pouvons résumer chaque ensemble de points de données comme la moyenne plus ou moins l’écart-type. Nous déterminons les valeurs significatives pour chaque moyenne à partir des mesures correspondantes et arrondissons les valeurs moyennes en conséquence.
L’écart-type de chaque groupe doit avoir le même nombre de décimales que la moyenne, nous arrondissons donc chaque écart-type au centième. Pour déterminer graphiquement la relation entre deux variables, nous pouvons ajuster les données avec une fonction de meilleur ajustement.
La fonction est générée automatiquement par un tableur et peut prendre la forme d’une ligne de tendance linéaire, d’une fonction polynomiale ou d’une fonction exponentielle ou logarithmique. Dans le cas de nos données de température et de volume, la relation est linéaire. Ainsi, les points de données sont ajustés par la régression linéaire des moindres carrés. Votre tableur renverra l’équation de la droite la mieux ajustée et une valeur r au carré. Plus la valeur du r au carré est proche de 1, meilleur est l’ajustement des données.
Ensuite, vous pouvez utiliser votre tableur pour trouver les écarts-types de la pente, l’ordonnée à l’origine et la valeur y calculée. Pour déterminer les chiffres significatifs des valeurs de l’équation, nous suivons une règle simple. Le dernier chiffre significatif de chaque valeur correspond à la première décimale significative de son écart-type.
Ainsi, nous arrondissons la pente au millième près et l’ordonnée à l’origine aux dixièmes près, et nous arrondissons les écarts-types pour correspondre. Notre pente est de 0,167 +/- 0,003 litre par Kelvin, et notre ordonnée à l’origine est de -40,6 +/- 1,2 litres. Toute valeur y calculée sera arrondie au dixième de seconde et sera de +/- 0,8 litre. Cette équation décrit la relation entre la température et le volume d’un gaz.
Dans cet atelier, vous allez créer un ensemble de données de variables dépendantes et indépendantes en mesurant le diamètre et la circonférence de différentes tailles de béchers. Vous allez ensuite utiliser ces données pour créer un nuage de points et effectuer une régression linéaire, en gardant à l'esprit l'importance des chiffres significatifs. Vous mettrez également en pratique des compétences de laboratoire, comme le filtrage et la mesure du volume à l'aide de pipettes, en prêtant attention à l'incertitude des mesures et de l'analyse.

mesure scientifique et compétences de laboratoire

Graphes bidimensionnels
Certaines expériences de chimie prennent la forme de la modification directe d’une propriété du système que vous étudiez, également connue sous le nom de variable indépendante, comme la température, et de la mesure des effets sur une autre propriété, également connue sous le nom de variable dépendante, comme le volume. Une fois les données collectées, l’interaction entre les deux paramètres doit être quantifiée – ou convertie sous une forme qui peut être évaluée – et comparée à d’autres relations.
Les graphes bidimensionnels peuvent être utilisés pour dériver certains types de relations mathématiques entre deux propriétés ou pour établir qu’une telle relation n’existe pas entre elles. L’analyse déterminera finalement comment la variable dépendante change en réponse à la variable indépendante. Dans l’exemple de l’ajustement de la température d’un liquide ou d’un gaz et de la surveillance des changements de son volume, la température est la variable indépendante et le volume est la variable dépendante.
Pour créer un graphique bidimensionnel, chaque point de données doit avoir une valeur connue sous le nom de coordonnée pour les variables dépendantes et indépendantes. La variable indépendante est tracée sur l’axe des abscisses, et la variable dépendante est tracée sur l’axe des ordonnées. Ces tracés sont facilement réalisés dans un tableur, qui peut également être utilisé pour analyser les données tracées.
Ajustement de la courbe
Une fois qu’un ensemble de données a été tracé sur un graphique bidimensionnel, l’ajustement de courbe peut être utilisé pour générer une équation, ou fonction, pour la variable dépendante en fonction de la variable indépendante. Les fonctions représentent un modèle mathématique qui modélise le mieux les données à partir desquelles il est dérivé. L’ajustement de courbe est la technique qui consiste à trouver une fonction qui produit une ligne qui correspond bien au modèle de points de données. Les tableurs disposent de divers outils d’ajustement des courbes, ce que l’on appelle le « meilleur ajustement ». Il s’agit généralement d’une analyse de régression linéaire des moindres carrés, bien que la plupart des logiciels proposent également une régression non linéaire des moindres carrés.
La précision de l’équation linéaire la mieux ajustée peut être vérifiée en insérant les valeurs x des points de données et en comparant les résultats « théoriques » de l’équation aux valeurs y réelles des points de données. Les tableurs calculent généralement la valeur du coefficient de détermination (R2) de la fonction, ce qui indique dans quelle mesure la fonction correspond aux points de données. Plus la valeur de R2 est proche de 1, meilleur est l’ajustement pour une régression linéaire. D’autres fonctions ont des méthodes plus spécialisées pour déterminer dans quelle mesure l’ajustement de la fonction est aux données.
Déterminer l’incertitude des valeurs dépendantes calculées à partir de la fonction la mieux ajustée nécessiterait des techniques compliquées de « propagation des erreurs ». Cependant, il est possible de calculer l’incertitude dans l’équation sous la forme de l’écart-type pour la pente et l’ordonnée à l’origine d’une fonction de meilleur ajustement. Cela se fait généralement avec un outil différent de celui utilisé pour générer un tracé bidimensionnel.
écart type
L’écart-type décrit la quantité de variation présente dans un ensemble de valeurs. L’écart-type de la population (σ) est utilisé lorsqu’il existe des données de chaque membre d’une population finie, telles que la masse de chaque bille dans un sac de billes. L’écart-type (s) de l’échantillon est utilisé pour tous les autres cas et constitue le calcul de l’écart-type par défaut dans le tableur. 1 Vous pouvez supposer que l'« écart-type » fait référence à l’écart-type de l’échantillon.
On suppose que l’erreur de mesure aléatoire suit une distribution à peu près « normale », où environ 68 % d’un ensemble de valeurs se situent dans une plage d’un écart-type de chaque côté de la moyenne, 95 % des valeurs se situent dans deux écarts-types de chaque côté de la moyenne et 99,7 % des valeurs se situent dans trois écarts-types de chaque côté de la moyenne. Ainsi, l’écart-type est un moyen utile de décrire l’erreur et l’incertitude.
L’équation de l’écart-type de l’échantillon est la suivante :
<img src="https://www.jove.com/CDNSource/lm/labs/42/42_Concepts_1.jpg%C2%A0%C2%BB%20/&gt;&lt;/p&gt;%0A&lt;p&gt;Dans%20cette%20%C3%A9quation,%20N%20est%20le%20nombre%20de%20valeurs%20;%20&lt;img%20src=" https:> est la moyenne (ou moyenne) des valeurs ; et xi représente chaque valeur individuelle. Ainsi, pour calculer l’écart-type à la main, calculez la moyenne de l’ensemble des valeurs, soustrayez la moyenne de chaque valeur, mettez chaque différence au carré, additionnez les différences au carré, divisez la somme totale par un de moins que le nombre de valeurs et prenez la racine carrée du quotient. Plus s est proche de zéro, moins il y a de variation entre les valeurs. Si les valeurs sont saisies dans un tableur, l’écart-type peut être calculé à partir du logiciel.
Le nombre de chiffres significatifs dans un écart-type dépend des valeurs qu’il concerne. Lors de la déclaration de l’écart-type pour un groupe de points de données pris dans les mêmes conditions, il faut d’abord déterminer le nombre approprié de chiffres significatifs dans la valeur moyenne. L’écart-type est ensuite arrondi au même nombre de décimales que la moyenne. Pour un ensemble de volumes comportant quatre chiffres significatifs, une moyenne de 15,361 mL et un écart-type de 0,2313, la moyenne et l’écart-type seraient déclarés comme suit : 15,36 mL ± 0,23 mL.
Lors de la déclaration de l’écart-type de la moyenne et de l’ordonnée à l’origine pour une fonction de meilleur ajustement déterminée par l’analyse des moindres carrés, qui est la méthode habituelle pour les tableurs, la première décimale de l’écart-type est le dernier chiffre significatif de la moyenne ou de l’ordonnée à l’origine. Ainsi, l’écart-type doit être arrondi à une décimale significative, et la pente ou l’ordonnée à l’origine doit être arrondie à la décimale correspondante. Par exemple, si la pente est de 0,1691 L·K-1 et qu’elle a un écart-type de 0,00512, la pente doit être indiquée comme 0,169 L·K-1 ± 0,005 L·K-1.
Si l’écart-type de la pente ou de l’ordonnée à l’origine est tellement plus petit que sa valeur correspondante que le respect de cette règle donnerait à la pente ou à l’ordonnée à l’origine plus de valeurs significatives que les données de mesure d’origine ne le permettaient, alors déterminez plutôt les valeurs significatives de la pente ou de l’ordonnée à l’origine à partir des valeurs x et y et arrondissez l’écart-type à un chiffre significatif. Ainsi, pour une pente de 0,1691 L·K-1, un écart-type de 0,0000512 et des valeurs x et y avec quatre chiffres significatifs, la pente doit être déclarée comme 0,1691 L·K-1 ± 0,00005 L·K- 1. Dans ce cas, il est possible que la valeur calculée et son écart-type aient un nombre de décimales différent. Gardez à l’esprit que la méthode des moindres carrés utilise à la fois les valeurs x et y pour calculer la pente et l’ordonnée à l’origine.
Lorsque vous déclarez l’écart-type sous la forme d’une plage d’incertitude, assurez-vous de noter spécifiquement que l’incertitude représente un écart-type. Cela indique au lecteur qu’il y a environ 68 % de chances que la valeur réelle d’une mesure se situe dans cette plage de la moyenne, en supposant une distribution normale. Il peut souvent être plus approprié de déclarer l’incertitude comme deux écarts-types par rapport à la moyenne, car cela augmente la probabilité à environ 95 %. Pour ce faire, il suffit de multiplier l’écart-type par deux avant de l’arrondir au nombre approprié de chiffres significatifs.
références
<ol style="taille-de-police :17px">
	<li style="font-size :17px">Harris, D.C. (2015). Analyse chimique quantitative. New York, NY : W.H. Freeman et compagnie.</li>
</ol>

Mesure scientifique et compétences de laboratoire

Graphes bidimensionnels
Certaines expériences de chimie prennent la forme de la modification directe d’une propriété du système que vous étudiez, également connu sous le nom de ...

Education

Enseignement

JoVE Lab Manual

Chimie

graphs, curve fit, and standard deviation

Two-dimensional graphs help students compare an independent variable with a dependent variable in science data. In a chemistry example, temperature is the independent variable and volume is the dependent variable. After data are collected, the relationship between the two measurements must be quantified so it can be evaluated and compared with other relationships. A graph can also show when no relationship exists between the two variables.

To make a two-dimensional graph, each data point needs a coordinate for both variables. The independent variable is plotted on the x-axis, and the dependent variable is plotted on the y-axis. These plots are often made in spreadsheet software, which can also be used to analyze the data. This helps show how the dependent variable changes in response to the independent variable.

Once the data are plotted, curve fitting can turn the pattern into an equation, or function. A function is a mathematical model that best matches the data it comes from. Curve fitting looks for a line or curve that fits the data points well. In many cases, spreadsheet tools use a best-fit method based on linear least-squares regression, although nonlinear least-squares regression is also available in most software.

The quality of a best-fit line can be checked by comparing the x values in the equation with the actual y values from the data. Spreadsheet software usually reports the coefficient of determination, or R squared, which shows how well the function matches the plotted points. A value closer to 1 means a better fit for linear regression. Finding uncertainty for values calculated from the equation can be more complicated, but standard deviation can be used to describe the uncertainty in the slope and y-intercept of a best-fit line.

Standard deviation shows how much values vary in a set. Population standard deviation, written as sigma, is used when data are available for every member of a finite population, such as the mass of each marble in a bag. Sample standard deviation, written as s, is used in all other cases and is the default in spreadsheet software. For that reason, standard deviation usually means sample standard deviation. Random measurement error is assumed to follow a roughly normal distribution, where about 68% of values fall within one standard deviation of the mean, 95% fall within two, and 99.7% fall within three.

The sample standard deviation can also be calculated by hand. First find the mean. Then subtract the mean from each value, square each difference, add the squared differences, divide by one less than the number of values, and take the square root. The closer s is to zero, the less variation there is in the data. Spreadsheet software can also calculate standard deviation directly.

When reporting standard deviation, the number of significant figures depends on what it describes. For a group of measurements taken under the same conditions, the standard deviation is rounded to the same number of decimal places as the mean. For example, 15.361 mL with a standard deviation of 0.2313 should be reported as 15.36 mL ± 0.23 mL. When reporting the standard deviation of a slope or y-intercept from least-squares analysis, the first decimal place of the standard deviation becomes the last significant figure of the value. So 0.1691 L·K-1 with a standard deviation of 0.00512 is reported as 0.169 L·K-1 ± 0.005 L·K-1.

If the standard deviation is much smaller than the slope or y-intercept, this rule can give more significant figures than the original x and y data allow. In that case, use the significant figures from the data and round the standard deviation to one significant figure. For example, 0.1691 L·K-1 with a standard deviation of 0.0000512 and x and y values with four significant figures is reported as 0.1691 L·K-1 ± 0.00005 L·K-1. It is important to state whether the uncertainty represents one standard deviation. One standard deviation gives about a 68% chance that the true value lies within that range. Two standard deviations may be a better choice when a wider uncertainty range is needed, since that raises the chance to about 95%.

Graphs, Curve Fit, and Standard Deviation

lab techniques

Measuring with Accuracy in the Lab

Measuring with accuracy in the lab starts with careful records, the right tools, and correct reading of data. Scientists use lab notebooks to record how an experiment was done. These notes include the amounts of materials used and each step of the procedure. Without that record, an experiment cannot be repeated in the same way. Balances and glassware are used to measure solids and liquids for experiments. The precision of a measurement depends on the equipment used. Digital balances show the...

scientific measurement and lab skills

Two-dimensional graphs help students compare an independent variable with a dependent variable in science data. In a chemistry example, temperature is the independent variable and volume is the dependent variable. After data are collected, the relationship between the two measurements must be quantified so it can be evaluated and compared with other relationships. A graph can also show when no relationship exists between the two variables. To make a two-dimensional graph, each data point needs...

stoichiometry, product yield, and limiting reactants

stoichiometry-product-yield-and-limiting-reactants

Balancing Equations and Reactant Limits

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redox reactions

Oxidation States in Redox Reactions

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ideal gas law

Gas Laws Behind the Ideal Gas Equation

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acid and base concentrations

Acids, Bases, and pH in Titration

Acids, bases, and pH explain how acidic or basic a solution is. An Arrhenius acid releases hydrogen ions when it dissolves in water, while an Arrhenius base releases hydroxide ions. These reactions also create conjugate partners: an acid forms a conjugate base after losing hydrogen, and a base forms a conjugate acid after losing hydroxyl. Every acid has a conjugate base, and every base has a conjugate acid. pH measures the amount of hydrogen ions in a solution. The pH scale runs from 0 to 14...

buffers

Buffer pH and the Common Ion Effect

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enthalpy of reaction

Reaction Heat, Hess’s Law, and Calorimetry

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solubility

Solubility in Water and Other Solvents

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metal flame emission

Flame Test Metal Color Clues

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balmer series

Hydrogen Emission Lines

Hydrogen emission lines show how electrons move between fixed energy levels in the Bohr model. Niels Bohr proposed this model for the hydrogen atom in 1913. In this model, an electron can only occupy certain orbits, and it cannot exist between them. These energy states are labeled with the quantum number n. The ground state is n = 1. Higher values, such as n = 2, 3, 4, and so on, are excited states. An electron changes state only by absorbing or emitting energy equal to the difference between...

beer's law

Absorbance Spectra and Beer-Lambert Analysis

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concentration dependence

Reaction Order and Rate Constants

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temperature dependence

Reaction Rate, Arrhenius, and Catalysts

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galvanic cells

Battery Power from Redox Reactions

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electrolytic cells

Electroplating with Electrolytic Cells

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proper lab notebook keeping

Recording a Reproducible Lab Experiment

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basic organic chemistry techniques

Organic Lab Glassware and Safe Handling

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melting points

How Impurities Change Melting Points

Melting point helps identify an organic compound by showing the temperature where a solid turns into a liquid at 1 atmosphere of pressure. It is a physical property, like solubility, density, color, and electronegativity. Because the exact start of melting is hard to measure, the result is reported as a range. The lower end is when the first drops of liquid appear. The upper end is when the last solid has melted. Scientists compare this range with literature values to help identify a compound. <br...

boiling points

Boiling Point and Vapor Pressure

Boiling point and vapor pressure are key physical properties of a liquid. For a pure compound, the boiling point can help identify the substance. In experiments, the boiling point is usually recorded as a range because exact values are hard to measure and may differ by a few degrees from the literature value. Vapor pressure explains why a liquid boils. In a sealed container, some molecules at the liquid surface gain enough energy to escape into the gas phase. At the same time, some gas...

recrystallization

Purifying Crystals by Solubility

Purifying crystals by solubility is a key organic chemistry technique. Recrystallization uses differences in solubility to separate a desired solid product from starting materials, solvent, and impurities. It is one of the three standard purification methods, along with distillation and extraction. Solubility is the maximum amount of a substance that can dissolve in a fixed volume of solvent at a given temperature. Different solutes dissolve in different solvents, and their behavior can vary...

extraction

Separating Mixtures with Solvent Extraction

Solvent extraction is a common way to separate and isolate a target compound in organic chemistry. In this process, a solute moves from one phase to another so it can be separated from unreacted starting materials or impurities. Extraction is also useful when a product is dissolved in a reaction solvent that is hard to remove by evaporation, such as a solvent with a high boiling point. There are three main types of extraction. In solid-liquid extraction, the solute moves from a solid phase...

simple distillation

Separating Liquids by Boiling Point

Separating liquids by boiling point is the goal of distillation. A miscible mixture contains liquids that mix evenly, and it can be heated so that the more volatile liquid evaporates first. Volatility is a liquid’s tendency to vaporize, and boiling begins when bubbles form in the liquid phase. In a closed container, liquid and vapor can reach equilibrium, which means the rate of vaporization equals the rate of condensation. The pressure from the vapor above the liquid is called vapor pressure.

steam distillation

Steam Distillation and Low-Boiling Separation

Steam distillation is a separation method for temperature-sensitive organic compounds. It works best when the organic compound is immiscible in water, meaning the two liquids do not mix. The method helps remove the organic molecule from a non-volatile contaminant without using the higher temperatures needed for many other separations. In steam distillation, the immiscible mixture is heated until both water and the volatile organic compound distill together. The vapor rises to a condenser,...

thin-layer chromatography

TLC Separation by Polarity

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column chromatography

Separating Mixtures by Polarity

Column chromatography separates compounds in an organic chemistry lab by using differences in physical properties. It is especially useful for microscale separations when less than 10 grams of material is available for analysis. The method can separate a mixture based on solubility, polarity, hydrophobicity, size, and charge. Any chromatography system has three main parts: the stationary phase, the mobile phase, and the sample mixture. In column chromatography, the stationary phase is usually...

hydrolysis of an ester

Soap Formation from Triglycerides

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synthesis of luminol

Luminol Chemiluminescence in Forensics

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esterification

Ester Formation and Everyday Fragrances

Esters are organic compounds with a carbonyl group attached to an oxygen that connects to another alkyl or aryl group. Their general formula is RCOOR'. They are often made by reacting a carboxylic acid with an alcohol in an esterification reaction. In this process, the hydroxyl group of the acid is replaced by an alkyl or aryl group. Many simple esters have familiar fruit and flower smells because their structures are small and less complex. Formic acid and methanol can combine to form methyl...

identification of unknown aldehydes and ketones

identification-of-unknown-aldehydes-and-ketones

Carbonyl Tests for Aldehydes and Ketones

Aldehydes and ketones are carbonyl compounds, which means they contain a C=O functional group. A ketone has two alkyl or aryl groups attached to the carbonyl carbon. Acetone is the simplest ketone, with two methyl groups. An aldehyde is similar, but it has at least one hydrogen attached to the carbonyl carbon. Formaldehyde is the simplest aldehyde, and acetaldehyde has one hydrogen and one methyl group. The carbonyl carbon in both aldehydes and ketones is electrophilic because the oxygen atom...

uv-vis spectroscopy of dyes

How Dyes Absorb Visible Light

Dyes absorb visible light because their molecular structure lets them interact with specific wavelengths. When light hits a substance, some light is absorbed and the rest is reflected or transmitted. The color we see depends on the wavelength that is reflected. A blue substance reflects blue light, around 430 to 480 nm, and absorbs the complementary orange region, around 590 to 630 nm. Compounds that do not absorb in the visible range appear colorless to the human eye. Light also has energy and...

identifying alcohols

Alcohol Tests for Primary, Secondary, and Tertiary

Alcohol tests can help sort alcohols by structure and reactivity. Alcohols are organic molecules with a hydroxyl group attached to an alkyl or aryl group, written as ROH. If the carbon with the hydroxyl group has one R group, the alcohol is primary. If it has two R groups, it is secondary. If it has three R groups, it is tertiary. Alcohols can also be aromatic when they contain a benzene ring. Phenol is the simplest aromatic alcohol. To identify an alcohol, chemists can use its chemical...

chemistry

Des vidéos complètes, axées sur le programme de cours pour les travaux pratiques de Chimie, adaptées à la fois aux professeurs et aux étudiants.

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Learn how to plot independent and dependent variables, use best-fit lines, and report standard deviation to describe uncertainty in science data.

Graphs, Curve Fit, and Standard Deviation | JoVE K12

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Scientific Laws and Theories

Scientific Laws

In science, a law is defined as a concise, verbal or mathematical, statement that summarizes a vast number of experimental observations. ...

The Scientific Method

Chemistry is an empirical science. Scientists often pose questions to understand the chemistry in everyday life and seek answers to these questions. To ...

CHEM.1.A

What is an Experiment?

An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two ...

Study Design in Statistics

A study design is a set of techniques that allow a researcher to collect and analyze data from different variables defined for a specific research ...

Observational Studies

Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not ...

Experimental Designs

An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are ...

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally ...

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in ...

Controls in Experiments

When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more ...

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected ...

Blinding

Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control ...

CHEM.1.B

Proper Personal Protective Equipment

Robert M. Rioux &#38; William A Elliott, Pennsylvania State University, University Park, PA
Hazards are many and varied in the laboratory, but the right ...

Emergency Eyewash and Shower Stations

Robert M. Rioux, Pennsylvania State University, University Park, PA
The Occupational Safety and Health Administration (OSHA) mandates that an emergency ...

Electrical Safety

Robert M. Rioux &amp; Suprita Jharimune, Pennsylvania State University, University Park, PA
Among the many hazards present in the laboratory, electrical ...

Working with Centrifuges

Source: Robert M. Rioux &amp; Suprita Jharimune, Pennsylvania State University, University Park, PA
Earth's gravitational force is capable of separating ...

Working with Hot and Cold Sources

Source: Robert M. Rioux &amp; Suprita Jharimune, Pennsylvania State University, University Park, PA
Working with extreme temperatures, both high and low, ...

guidelines-in-case-of-a-laboratory-emergency

Guidelines in Case of a Laboratory Emergency

Robert M. Rioux &amp; Zhifeng Chen, Pennsylvania State University, University Park, PA
The most common laboratory emergencies include chemical spills, ...

chemical-storage-categories-hazards-and-compatibilities

Chemical Storage: Categories, Hazards And Compatibilities

Source: Robert M. Rioux &amp; Taslima A. Zaman, Pennsylvania State University, University Park, PA
While the use of various chemicals in experimental ...

Safe Handling of Mineral Acids

Source: Robert M. Rioux &#38; Taslima A. Zaman, Pennsylvania State University, University Park, PA
A mineral acid (or inorganic acid) is defined as a ...

Handling Chemical Spills

Source: Robert M. Rioux &#38; Taslima Zaman, Pennsylvania State University, University Park, PA
Since chemicals are commonly used for laboratory research ...

Proper Use of Autoclaves

Robert M. Rioux &amp; Zhifeng Chen, Pennsylvania State University, University Park, PA
Autoclaving is one of the most commonly used methods in the ...

Fume Hoods and Laminar Flow Cabinets

Robert M. Rioux &amp; William A. Elliott, Pennsylvania State University, University Park, PA
Fume hoods and laminar flow cabinets are engineering controls ...

handling-air-and-water-sensitive-chemicals-using-a-schlenk-line

Handling Air- and Water-Sensitive Chemicals Using a Schlenk Line

Robert M Rioux, Ajay Sathe, Zhifeng Chen, Pennsylvania State University, University Park, PA
The use of reagents sensitive to oxidation or moisture ...

proper-operation-of-vacuum-based-equipment

Proper Operation of Vacuum Based Equipment

Source: Robert M. Rioux, Ajay Sathe &#38; Zhifeng Chen, Pennsylvania State University, University Park, PA
Vacuum is required for a number of laboratory ...

Operating the Glovebox

Robert M Rioux, Ajay Sathe, Zhifeng Chen, Pennsylvania State University, University Park, PA 
A glovebox is an isolated enclosure that is designed to ...

operation-of-high-pressure-reactor-vessels

Operation of High-pressure Reactor Vessels

Robert M Rioux, Pennsylvania State University, University Park, PA
The use of gases in a synthetic chemistry laboratory is essential for carrying out a ...

CHEM.1.C

Lab Techniques

Measurement Accuracy
The ability to repeat an experiment and get the same results, or reproducibility, is essential in scientific research. However, ...

Two-Dimensional Graphs
Some chemistry experiments take the form of directly changing one property of the system that you are studying otherwise known as ...

Proper Lab Notebook Keeping

Organic Lab Notebook Keeping
Record keeping is a vital skill in science and organic chemistry labs. Without proper notes, descriptions, quantities, or ...

Basic Organic Chemistry Techniques

Glassware in Organic Chemistry
There are standard pieces of glassware that are used in the organic chemistry lab. Beakers and Erlenmeyer flasks are ...

Measurement: Standard Units

Every measurement provides three kinds of information: the size or magnitude of the measurement (a number), a standard of comparison for the measurement ...

Measurement: Derived Units

The International System of Units or SI system, by international agreement, has fixed measurement units for seven fundamental properties: length, mass, ...

uncertainty-in-measurement-accuracy-and-precision

Uncertainty in Measurement: Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy ...

uncertainty-in-measurement-reading-instruments

Uncertainty in Measurement: Reading Instruments

Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such ...

CHEM.1.E

Scientific and engineering practices. The student, for at least 40% of instructional time, asks questions, identifies problems, and plans and safely conducts classroom, laboratory, and field investigations to answer questions, explain phenomena, or design solutions using appropriate tools and models. The student is expected to:

Graphs, Curve Fit, and Standard Deviation

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