pwiki - User contributions [en]

Monte Carlo Regression

2025-08-29T14:57:37Z

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Widget:Plotly

2025-08-29T14:56:41Z

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Monte Carlo Regression

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Monte Carlo Regression

2025-08-28T19:38:17Z

Wikiroot: Created page with "<style> body { font-family: Arial, sans-serif; margin: 40px; text-align: center; } .input-grid { display: grid; grid-template-columns: repeat(3, 1fr); gap: 15px; max-width: 900px; margin: 0 auto 30px; } .input-grid strong { font-size: 16px; grid-column: span 3; text-align: left; padding-top: 10px; } input[type="text"] { padding: 8px; font-size: 14px; widt..."

Widget:Monte Carlo Regression

2025-08-28T19:29:25Z

Wikiroot:

<div id="my-widget-container">

</div>

<style>
body {
font-family: Arial, sans-serif;
margin: 40px;
text-align: center;
}
.input-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 15px;
max-width: 900px;
margin: 0 auto 30px;
}
.input-grid strong {
font-size: 16px;
grid-column: span 3;
text-align: left;
padding-top: 10px;
}
input[type="text"] {
padding: 8px;
font-size: 14px;
width: 100%;
}
button {
padding: 10px 20px;
margin: 10px;
font-size: 16px;
background-color: #4CAF50;
color: white;
border: none;
border-radius: 4px;
cursor: pointer;
}
button:hover {
background-color: #45a049;
}
#plot {
width: 100%;
height: 75vh;
}
</style>

<div class="my-widget-container">
<h1>Monte Carlo Linear Regression with Confidence Band</h1>
<p>Paste your data from Excel into the boxes below. Includes both x and y errors.</p>

<div class="input-grid">
<div><strong>Axis Labels</strong></div><div></div><div></div>
<div style="grid-column: span 3;">
<p>You can use HTML like <code><sub></code> and <code><sup></code> (e.g., H<sub>2</sub>O → H<sub>2</sub>O).</p>
</div>
<input type="text" id="xLabel" placeholder="X Axis Label">
<input type="text" id="yLabel" placeholder="Y Axis Label">
<div></div>

<div><strong>X Values</strong></div><div></div><div></div>
<input type="text" id="xValues" placeholder="X Values (space-separated)">
<input type="text" id="xErrors" placeholder="X Errors (optional)">
<div></div>

<div><strong>Y Values</strong></div><div></div><div></div>
<input type="text" id="yValues" placeholder="Y Values">
<input type="text" id="yErrors" placeholder="Y Errors (optional)">
<div></div>
</div>

<button onclick="plotData()">Plot</button>
<button onclick="downloadPlot()">Download Chart</button>
<div id="plot"></div>
</div>

<script>
function parseValues(id) {
const val = document.getElementById(id).value.trim();
return val === "" ? [] : val.split(/\s+/).map(Number);
}

function plotData() {
const x = parseValues('xValues');
const y = parseValues('yValues');
const xErr = parseValues('xErrors');
const yErr = parseValues('yErrors');
const xLabel = document.getElementById('xLabel').value || 'X Axis';
const yLabel = document.getElementById('yLabel').value || 'Y Axis';

if (x.length !== y.length) {
alert('X and Y values must be the same length.');
return;
}

const N = 10000;
const slopes = [], intercepts = [];

function randn_bm() {
let u = 0, v = 0;
while (u === 0) u = Math.random();
while (v === 0) v = Math.random();
return Math.sqrt(-2.0 * Math.log(u)) * Math.cos(2.0 * Math.PI * v);
}

function linregress(xs, ys) {
const n = xs.length;
const xMean = xs.reduce((a, b) => a + b, 0) / n;
const yMean = ys.reduce((a, b) => a + b, 0) / n;
let num = 0, den = 0;
for (let i = 0; i < n; i++) {
num += (xs[i] - xMean) * (ys[i] - yMean);
den += (xs[i] - xMean) ** 2;
}
const slope = num / den;
const intercept = yMean - slope * xMean;
return { slope, intercept };
}

for (let i = 0; i < N; i++) {
const xSim = x.map((xi, j) => xi + randn_bm() * (xErr[j] || 0));
const ySim = y.map((yi, j) => yi + randn_bm() * (yErr[j] || 0));
const { slope, intercept } = linregress(xSim, ySim);
if (isFinite(slope) && isFinite(intercept)) {
slopes.push(slope);
intercepts.push(intercept);
}
}

const xRange = [];
const xmin = Math.min(...x), xmax = Math.max(...x);
const steps = 100;
const step = (xmax - xmin) / steps;
for (let i = 0; i <= steps; i++) {
xRange.push(xmin + i * step);
}

const lower = [], upper = [], meanLine = [];
for (let xi of xRange) {
const ySamples = slopes.map((m, i) => m * xi + intercepts[i]);
ySamples.sort((a, b) => a - b);
const lo = ySamples[Math.floor(0.025 * ySamples.length)];
const hi = ySamples[Math.floor(0.975 * ySamples.length)];
const avg = ySamples.reduce((a, b) => a + b, 0) / ySamples.length;
lower.push(lo);
upper.push(hi);
meanLine.push(avg);
}

const mean = arr => arr.reduce((a, b) => a + b, 0) / arr.length;
const std = arr => {
const m = mean(arr);
return Math.sqrt(arr.reduce((s, v) => s + (v - m) ** 2, 0) / (arr.length - 1));
};
const slopeStat = { mean: mean(slopes), std: std(slopes) };
const interceptStat = { mean: mean(intercepts), std: std(intercepts) };

const annotationText = `y = (${slopeStat.mean.toExponential(3)} ± ${slopeStat.std.toExponential(3)})x + (${interceptStat.mean.toExponential(3)} ± ${interceptStat.std.toExponential(3)})`;

const data = [];

// Original data points with error bars
data.push({
x: x,
y: y,
mode: 'markers',
type: 'scatter',
name: 'Data',
marker: { color: 'black', size: 7, symbol: 'x-thin-open' },
error_x: xErr.length === x.length ? {
type: 'data',
array: xErr,
visible: true
} : undefined,
error_y: yErr.length === y.length ? {
type: 'data',
array: yErr,
visible: true
} : undefined
});

// Confidence band
data.push({
x: [...xRange, ...xRange.slice().reverse()],
y: [...upper, ...lower.slice().reverse()],
fill: 'toself',
fillcolor: 'rgba(255, 0, 0, 0.2)',
line: { color: 'transparent' },
name: '95% Confidence Band',
type: 'scatter',
showlegend: false
});

// Mean regression line
data.push({
x: xRange,
y: meanLine,
mode: 'lines',
type: 'scatter',
name: 'Mean Fit',
line: { color: 'red', width: 2 }
});

const layout = {
title: '',
xaxis: { title: xLabel },
yaxis: { title: yLabel },
showlegend: false,
annotations: [{
x: 0.05,
y: 0.95,
xref: 'paper',
yref: 'paper',
text: annotationText,
showarrow: false,
font: { color: 'black', size: 14 }
}]
};

Plotly.newPlot('plot', data, layout);
}

function downloadPlot() {
Plotly.downloadImage('plot', { format: 'png', filename: 'monte_carlo_regression' });
}
</script>

Widget:Monte Carlo Regression

2025-08-28T19:19:40Z

Wikiroot: Monte Carlo Regression

<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"/>
<title>Monte Carlo Linear Fit with Confidence Band</title>
<script src="https://cdn.plot.ly/plotly-latest.min.js"></script>
<style>
body {
font-family: Arial, sans-serif;
margin: 40px;
text-align: center;
}
.input-grid {
display: grid;
grid-template-columns: repeat(3, 1fr);
gap: 15px;
max-width: 900px;
margin: 0 auto 30px;
}
.input-grid strong {
font-size: 16px;
grid-column: span 3;
text-align: left;
padding-top: 10px;
}
input[type="text"] {
padding: 8px;
font-size: 14px;
width: 100%;
}
button {
padding: 10px 20px;
margin: 10px;
font-size: 16px;
background-color: #4CAF50;
color: white;
border: none;
border-radius: 4px;
cursor: pointer;
}
button:hover {
background-color: #45a049;
}
#plot {
width: 100%;
height: 75vh;
}
</style>
</head>
<body>
<h1>Monte Carlo Linear Regression with Confidence Band</h1>
<p>Paste your data from Excel into the boxes below. Includes both x and y errors.</p>

<div class="input-grid">
<div><strong>Axis Labels</strong></div><div></div><div></div>
<div style="grid-column: span 3;">
<p>You can use HTML like <code><sub></code> and <code><sup></code> (e.g., H<sub>2</sub>O → H<sub>2</sub>O).</p>
</div>
<input type="text" id="xLabel" placeholder="X Axis Label">
<input type="text" id="yLabel" placeholder="Y Axis Label">
<div></div>

<div><strong>X Values</strong></div><div></div><div></div>
<input type="text" id="xValues" placeholder="X Values (space-separated)">
<input type="text" id="xErrors" placeholder="X Errors (optional)">
<div></div>

<div><strong>Y Values</strong></div><div></div><div></div>
<input type="text" id="yValues" placeholder="Y Values">
<input type="text" id="yErrors" placeholder="Y Errors (optional)">
<div></div>
</div>

<button onclick="plotData()">Plot</button>
<button onclick="downloadPlot()">Download Chart</button>
<div id="plot"></div>

<script>
function parseValues(id) {
const val = document.getElementById(id).value.trim();
return val === "" ? [] : val.split(/\s+/).map(Number);
}

function plotData() {
const x = parseValues('xValues');
const y = parseValues('yValues');
const xErr = parseValues('xErrors');
const yErr = parseValues('yErrors');
const xLabel = document.getElementById('xLabel').value || 'X Axis';
const yLabel = document.getElementById('yLabel').value || 'Y Axis';

if (x.length !== y.length) {
alert('X and Y values must be the same length.');
return;
}

const N = 10000;
const slopes = [], intercepts = [];

function randn_bm() {
let u = 0, v = 0;
while (u === 0) u = Math.random();
while (v === 0) v = Math.random();
return Math.sqrt(-2.0 * Math.log(u)) * Math.cos(2.0 * Math.PI * v);
}

function linregress(xs, ys) {
const n = xs.length;
const xMean = xs.reduce((a, b) => a + b, 0) / n;
const yMean = ys.reduce((a, b) => a + b, 0) / n;
let num = 0, den = 0;
for (let i = 0; i < n; i++) {
num += (xs[i] - xMean) * (ys[i] - yMean);
den += (xs[i] - xMean) ** 2;
}
const slope = num / den;
const intercept = yMean - slope * xMean;
return { slope, intercept };
}

for (let i = 0; i < N; i++) {
const xSim = x.map((xi, j) => xi + randn_bm() * (xErr[j] || 0));
const ySim = y.map((yi, j) => yi + randn_bm() * (yErr[j] || 0));
const { slope, intercept } = linregress(xSim, ySim);
if (isFinite(slope) && isFinite(intercept)) {
slopes.push(slope);
intercepts.push(intercept);
}
}

const xRange = [];
const xmin = Math.min(...x), xmax = Math.max(...x);
const steps = 100;
const step = (xmax - xmin) / steps;
for (let i = 0; i <= steps; i++) {
xRange.push(xmin + i * step);
}

const lower = [], upper = [], meanLine = [];
for (let xi of xRange) {
const ySamples = slopes.map((m, i) => m * xi + intercepts[i]);
ySamples.sort((a, b) => a - b);
const lo = ySamples[Math.floor(0.025 * ySamples.length)];
const hi = ySamples[Math.floor(0.975 * ySamples.length)];
const avg = ySamples.reduce((a, b) => a + b, 0) / ySamples.length;
lower.push(lo);
upper.push(hi);
meanLine.push(avg);
}

const mean = arr => arr.reduce((a, b) => a + b, 0) / arr.length;
const std = arr => {
const m = mean(arr);
return Math.sqrt(arr.reduce((s, v) => s + (v - m) ** 2, 0) / (arr.length - 1));
};
const slopeStat = { mean: mean(slopes), std: std(slopes) };
const interceptStat = { mean: mean(intercepts), std: std(intercepts) };

const annotationText = `y = (${slopeStat.mean.toExponential(3)} ± ${slopeStat.std.toExponential(3)})x + (${interceptStat.mean.toExponential(3)} ± ${interceptStat.std.toExponential(3)})`;

const data = [];

// Original data points with error bars
data.push({
x: x,
y: y,
mode: 'markers',
type: 'scatter',
name: 'Data',
marker: { color: 'black', size: 7, symbol: 'x-thin-open' },
error_x: xErr.length === x.length ? {
type: 'data',
array: xErr,
visible: true
} : undefined,
error_y: yErr.length === y.length ? {
type: 'data',
array: yErr,
visible: true
} : undefined
});

// Confidence band
data.push({
x: [...xRange, ...xRange.slice().reverse()],
y: [...upper, ...lower.slice().reverse()],
fill: 'toself',
fillcolor: 'rgba(255, 0, 0, 0.2)',
line: { color: 'transparent' },
name: '95% Confidence Band',
type: 'scatter',
showlegend: false
});

// Mean regression line
data.push({
x: xRange,
y: meanLine,
mode: 'lines',
type: 'scatter',
name: 'Mean Fit',
line: { color: 'red', width: 2 }
});

const layout = {
title: '',
xaxis: { title: xLabel },
yaxis: { title: yLabel },
showlegend: false,
annotations: [{
x: 0.05,
y: 0.95,
xref: 'paper',
yref: 'paper',
text: annotationText,
showarrow: false,
font: { color: 'black', size: 14 }
}]
};

Plotly.newPlot('plot', data, layout);
}

function downloadPlot() {
Plotly.downloadImage('plot', { format: 'png', filename: 'monte_carlo_regression' });
}
</script>
</body>
</html>

Main Page

2021-11-30T16:11:44Z

Wikiroot:

<big>'''Vanier College Physics Wiki'''</big>

Consult the [http://meta.wikimedia.org/wiki/Help:Contents User's Guide] for information on using the wiki software.

== Getting started==
* [http://www.mediawiki.org/wiki/Manual:Configuration_settings Configuration settings list]
* [http://www.mediawiki.org/wiki/Manual:FAQ MediaWiki FAQ]
* [https://lists.wikimedia.org/mailman/listinfo/mediawiki-announce MediaWiki release mailing list]

==IMPORTANT DOCUMENTS==
Find your textbook, study guides and lab skills handbook here:
*[[STUDY DOCS]]



== MECHANICS ==
=== Introduction ===
* [http://stefan.bracher.info/files/physics/mechanics/mechanics_overview.pdf Mechanics Concept Overview]
* [http://stefan.bracher.info/files/physics/Formulas_and_Constants_for_College_Physics.pdf Stefan's Formulas for College Physics]
* [https://www.youtube.com/playlist?list=PLpDR89URs0h-zf-cHLTBNHUXOPYIEpWAg Stefan's Youtube Playlist for Mechanics]

=== Math review ===
==== Theory ====
* [http://stefan.bracher.info/files/physics/mechanics/Math_Review.pdf Stefan's Lecture Note on Math Review]

=== Measurement, Uncertainty, and Units ===
==== Videos ====
* [https://youtu.be/Kfy_Sd3jSCk Video: Introduction to uncertainties]
* [https://youtu.be/9YriBMqMx7c Video: Estimating the uncertainty of a measurement - Example: the length of a cat]
* [https://youtu.be/gHLzzzDohdE Video: Using the Min-Max Method to calculate the uncertainty of a measurement - Example: the length of a cat]
* [https://youtu.be/2ld3uFfRVt0 Video: Using the Average and Standard Deviation to calculate the uncertainty of a measurement - Example: the length of a cat]
* [https://youtu.be/e-Eb2wdZ-Qk Video: Accurate vs. Precise]
* [https://youtu.be/7Q-zuT9cbeo Video: Calculations with uncertainty - Simple cases]
* [https://youtu.be/Lrkd6yHjTRI Video: Calculations with uncertainty - Complicated cases]
* [https://youtu.be/dumXDlANJA8 Video: Unit Conversion with dimensional analysis]
* [https://youtu.be/CLPjNelMLIs Video: Unit Conversion example: km/h to m/s]
* [https://youtu.be/7Vv7ExV87MU Video: SI-Prefixes]

==== Theory ====
* [http://gauss.vaniercollege.qc.ca/pwiki/index.php/Measurement_and_Data_Analysis Measurement and Data Analysis]
* [http://gauss.vaniercollege.qc.ca/pwiki/index.php/Uncertainties_in_Measurement Uncertainties in Measurement]
* [http://stefan.bracher.info/files/physics/mechanics/measurement_and_uncertainty.pdf Stefan's Lecture Note on Measurement and Uncertainty]

==== Book References ====
* [https://cnx.org/contents/1Q9uMg_a@13.38:bG-_rWXy@10/Introduction OpenStax University Physics Volume 1: Chapter 1.1-1.4]
* [https://cnx.org/contents/Ax2o07Ul@17.3:EC6WBNqn@13/1-2-Physical-Quantities-and-Units OpenStax College Physics: Chapter 1.2-1.3]

=== Vectors ===
==== Videos ====
* [https://youtu.be/pDPOcpsdOXs Video: Drawing Vectors]
* [https://youtu.be/v2Cd4C7JXPY Video: Find the direction and the components of a vector]
* [https://youtu.be/OrryaQqcvk8 Video: Adding Vectors Graphically : Head to Tail Method]

==== Theory ====
* [[Vectors]]
* [http://stefan.bracher.info/files/physics/mechanics/Vectors.pdf Stefan's Lecture Note on Vectors]

==== Book References ====
* [https://cnx.org/contents/1Q9uMg_a@13.38:CEzSxrSw@8/Introduction Openstax University Physics Volume 1 - Chapter 2:Vectors]
* [https://cnx.org/contents/Ax2o07Ul@17.3:S9i77L2i@12/3-2-Vector-Addition-and-Subtraction-Graphical-Methods OpenStax College Physics - Chapter 3.2: Vector Addition and Subtraction: Graphical Methods]

=== Kinematics ===
*[[Basic Concepts]]

=====1 D Motion=====

====== Videos ======
* [https://youtu.be/g4s1j9nCyi4 Video: Introduction to Position-Time graphs]
* [https://youtu.be/YXrLMZb5uBA Video: Introduction to Velocity-Time graphs]
* [https://youtu.be/wArPnyyZCFg Video: Drawing the Position-Time graph from the Velocity-Time Graph]
* [https://youtu.be/wyZZn6sri5U Video: Kinematics Definitions, displacement, distance traveled, velocity and speed.]
* [http://stefan.bracher.info/files/physics/kinematics_formulas.htm Videos: Formulas for motion with constant acceleration]

* [https://youtu.be/-8eGB1WH0jw Video: Example - v-t, a-t and s-t graphs]
* [https://youtu.be/dKe0XFzSc6g Video: Example - Free-Fall]
* [https://youtu.be/q-TDxttAtLk Video: Example - Throwing an object in the air : Part 1]
* [https://youtu.be/nE5ePfnAyk8 Video: Example - Throwing an object in the air : Part 2]

* [https://youtu.be/22N1kAFx0L8 Video: Catch-up problems]

====== Theory ======
*[[Motion Along a Straight Line: Graphical Representation]] 
*[[Equations of Motion]]
* [[Free Fall]]

====== Simulation and practice ======
* [https://phet.colorado.edu/en/simulation/legacy/moving-man Simulation: Graphs]
* [https://www.geogebra.org/m/pdNj3DgD Geogebra: Create x-t and a-t graphs for various v-t graphs]
* [https://www.mathcelebrity.com/kinematic.php MathCelebrity: Kinematics Equations Calculator]

====== Book References ======
* [https://openstax.org/books/university-physics-volume-1/pages/3-introduction OpenStax University Physics Volume 1 - Chapter 3: Motion Along a Straight Line]
* [https://openstax.org/books/college-physics/pages/2-introduction-to-one-dimensional-kinematics OpenStax College Physics - Chapter 2: Introduction to One-Dimensional Kinematics]

=====2 D Motion=====
====== Videos ======
* [https://youtu.be/myHJ6_WS5OM Video: Introduction to 2D Kinematics]
* [https://youtu.be/_KyWgMUqP7k Video: Constant acceleration in 2D Kinematics]
* [https://youtu.be/tx8RMmVfy_E Video: Introduction to Projectile Motion]
* [https://youtu.be/x66EJxWhk8U Video: Projectile Motion Example - Angle and target location unknown]
* [https://youtu.be/vgUlurfyW0c Video: Projectile Motion Example - Maximal height and time to maximal height unknown]
* [https://youtu.be/qIi8-9rpRzU Video: Projectile Motion - Range and trajectory]
* [https://youtu.be/kwZ6_DAFFfE Video: Uniform Circular Motion - Centripetal Acceleration]

====== Theory ======
* [[Introduction to 2 D Motion]]
* [[Circular Motion]]
* [[Projectile Motion]]

====== Book References ======
* [https://openstax.org/books/university-physics-volume-1/pages/4-introduction OpenStax University Physics Volume 1 - Chapter 4: Motion in Two and Three Dimensions]
* [https://openstax.org/books/college-physics/pages/3-introduction-to-two-dimensional-kinematics OpenStax College Physics - Chapter 3: Introduction to Two-Dimensional Kinematics]

=====Rotational Kinematics=====
====== Videos ======
* [https://youtu.be/ZMZaO5mQLlE Video: Rotational Motion]
* [https://youtu.be/mwVww1NhIYk Video: Equations for constant angular acceleration]
* [https://youtu.be/3C4QfnlIQgM Video: Units of rotational motion (rpm)]
* [https://youtu.be/Nyv0SLEU2Aw Video: Rotational Kinematics Example]

====== Theory ======
* [[Rotational Motion]]


====== Book References ======
* [https://openstax.org/books/university-physics-volume-1/pages/10-introduction OpenStax University Physics Volume 1 - Chapter 10.1-10.3: Fixed-Axis Rotation]
* [https://openstax.org/books/college-physics/pages/10-introduction-to-rotational-motion-and-angular-momentum OpenStax College Physics - Chapter 10.1-10.2: Rotational Motion]

=== Dynamics ===
==== Videos ====
* [https://youtu.be/AUSXcozE_A0 Video: Introduction to Newton's Laws of Motion]
* [https://youtu.be/WzvhuQ5RWJE Video: Newton's 2nd Law of Motion]
* [https://youtu.be/cP0Bb3WXJ_k Video: Newton's 3rd Law of Motion]
* [https://youtu.be/dzdDzzRZm9U Video: Free Body Diagrams]
* [https://youtu.be/TLtGWls5F_I Video: Normal Forces Part 1]
* [https://youtu.be/JTeVBfUBdDs Video: Normal Forces Part 2]
* [https://youtu.be/t2RjGcvNSas Video: Tension Force]
* [https://youtu.be/dPSOs9lw90I Video: Simple Newton's Laws Problem Example]
* [https://youtu.be/ofeT2En6nz0 Video: Statics - Box on Surface]
* [https://youtu.be/R6ltYEMHuwc Video: Simple Dynamics Example]
* [https://youtu.be/pWsab45Httg Video: Two-body dynamics problem]
* [https://youtu.be/Y4FLaOTmklQ Video: Two boxes pushed along a surface]
* [https://youtu.be/JwEDFRDA5dc Video: Torque Shortcuts]
* [https://youtu.be/DMy6ree2sUA Video: Introduction to Rotational Equilibrium]
* [https://youtu.be/K1SxSdflCDA Video: Rotational and Translational Equilibrium - Beam with hanging mass]
* [https://youtu.be/XoAYWaDfs40 Video: Ladder leaning on the wall]
* [https://youtu.be/yC47CbcoWOE Video: Neil deGrasse Tyson: Einstein vs Newton - Who Was Right?]
* [https://youtu.be/lFgdmjmSxk0 Video: Newton's Universal Law of Gravity: Introduction]
* [https://youtu.be/xJqJ_UvBKiY Video: Newton's Universal Law of Gravity: Calculating the mass of the earth]
* [https://youtu.be/a-E28IqPVw8 Video: Newton's Universal Law of Gravity: Calculating the time it takes the moon to go around the earth]

==== Theory ====
*[[What is Dynamics?]]




*[[Inertia|The Concept of Inertia]] <br>
*[[Newton's Laws|Newton's Laws of Motion]] <br>
*[[Newton's Law of Universal Gravitation]]<br>
* [[Friction]]
*[[Dynamics of Circular Motion]]<br>
*[[Static and Dynamic Equilibrium]] <br>
*[[Torque]]


==== Book References ====
* [https://openstax.org/books/university-physics-volume-1/pages/5-introduction OpenStax University Physics Chapter 5: Newton's Laws of Motion]
* [https://openstax.org/books/university-physics-volume-1/pages/6-introduction OpenStax University Physics Chapter 6: Applications of Newton's Laws]
* [https://openstax.org/books/university-physics-volume-1/pages/10-6-torque OpenStax University Physics Chapter 10.6: Torque]
* [https://openstax.org/books/university-physics-volume-1/pages/10-7-newtons-second-law-for-rotation OpenStax University Physics Chapter 10.7: Newton's second law for rotation]

==== Simulations ====
* [https://phet.colorado.edu/en/simulation/forces-and-motion-basics Phet: Forces and Motion: Basics]
* [https://phet.colorado.edu/en/simulation/legacy/ramp-forces-and-motion Phet: Forces and Motion]
* [https://phet.colorado.edu/en/simulation/legacy/forces-and-motion Phet: Forces and Motion]
* [https://phet.colorado.edu/en/simulation/legacy/lunar-lander Phet: Lunar Lander]

=== Laws of Conservation ===
==== Videos - Energy ====
* [https://youtu.be/oDNAqnKhjZA Video: Introduction to Laws of Conservation (Conservation of Energy)]
* [https://youtu.be/a-4UISMSVpE Video: Conservation of Energy in Mechanics]
* [https://youtu.be/BEyZ60DHLnE Video: Mechanical Work]
* [https://youtu.be/y265HF0I1kg Video: Work required to lift an object (Discovery of Potential Energy)]
* [https://youtu.be/a5qhsUWiZjw Video: Work required to accelerate an object to velocity v (Discovery of Kinetic Energy)]
* [https://youtu.be/1XwxKKcn0ks Video: Conservative Forces and Potential Energy]
* [https://youtu.be/CiSmPI4eHp8 Video: The potential energy of a spring]
* [https://youtu.be/Jk9mYVAGHGk Video: Energy Example: Two connected blocks and a spring]
* [https://youtu.be/tGjZTRMSFBo Video: Energy Example: Calculating the escape velocity]
* [https://youtu.be/4HMXr7ExmBg Video: Pendulum Lab with Photogates - Conservation of Energy - Instructions]

==== Videos - Momentum ====
* [https://youtu.be/dNOthHSV0RM Video: Introduction to Linear Momentum]
* [https://youtu.be/I_RNxh8Eb-s Video: Conservation of Linear Momentum - Inelastic Collision]
* [https://youtu.be/ym2c6k09YY4 Video: Conservation of Linear Momentum - Example: 1D Inelastic Collision]
* [https://youtu.be/Fq7CasNQ_m0 Video: Conservation of Linear Momentum - Elastic Collision]
* [https://youtu.be/TArgOS55--I Video: Conservation of Linear Momentum - 2D Collision Example]
* [https://youtu.be/tXeQKIlxQEk Video: Conservation of Linear Momentum - Explosions]
* [https://youtu.be/zsMvyDSDPtI Video: Conservation of Linear Momentum - Rocket Equation (this is Rocket Science!)]
* [https://youtu.be/2FmyyHR47Xo Video: Conservation of Linear Momentum - Linear Momentum and Newton]
* [https://youtu.be/mqU9XBZ-jnw Video: Conservation of Angular Momentum - Introduction]
* [https://youtu.be/ULAar-EtJQI Video: Conservation of Angular Momentum - Changing the rotational inertia]
* [https://youtu.be/_RVe_ii-YJ4 Video: Conservation of Angular Momentum - A rotating platform]

==== Theory ====
* [[Work and Energy]]

* [[Potential Energy]]

* [[Conservative and Non-Conservative Forces]]

* [[Conservation of Energy]]

* [[Rotational Kinetic Energy and Moment Of Inertia]]

* [[Conservation of Momentum|Conservation of Linear Momentum]] 
==== Book References ====
* [https://openstax.org/books/university-physics-volume-1/pages/7-introduction Openstax University Physics Volume 1: Chapter 7 (Work and Kinetic Energy)]
* [https://openstax.org/books/university-physics-volume-1/pages/8-introduction Openstax University Physics Volume 1: Chapter 8 (Potential Energy and Conservation of Energy)]
* [https://openstax.org/books/university-physics-volume-1/pages/9-introduction Openstax University Physics Volume 1: Chapter 9 (Linear Momentum and Collisions)]
* [https://openstax.org/books/university-physics-volume-1/pages/11-introduction Openstax University Physics Volume 1: Chapter 11 (Angular Momentum)]

=== Summary ===
* [https://youtu.be/3RnIH4_3E1U Video: Summary of Mechanics]

== STEFAN BRACHER'S LECTURES ==
*[http://stefan.bracher.info/physics_mechanics.php Stefan's Lecture notes for Mechanics]
<br>
== Interesting Articles on Mechanics ==

*[[My Daughter,the Physicist]]
:''by Stephen Cohen''

=====<span style="color:Red">Felix Baumgartner's Sky Dive</span>=====

[http://theengineerspulse.blogspot.ca/2012/10/mechanical-analysis-of-baumgartners.html Mechanical analysis of Baumgartner's sky dive]
<br>

[http://theengineerspulse.blogspot.ca/2012/10/mechanical-analysis-of-baumgartners_15.html Mechanical analysis of Baumgartner's sky dive-part 2]

<br><br>

== WAVES AND MODERN PHYSICS ==





*[[Waves and Modern Physics]] <br><br>

== ELECTRICITY AND MAGNETISM ==
*[[Electricity and Magnetism]]<br>






== SECONDARY 5 PHYSICS ==
*[[Secondary 5 Physics]]

== REMEDIAL ACTIVITIES FOR SECONDARY 4 ENVIRONMENTAL SCIENCE AND TECHNOLOGY ==
*[[Secondary 4 Physical Science]]

== KEVIN LENTON'S MECHANICS MODULES ==

== KRESHNIK ANGONI'S LECTURES ==

* [http://gauss.vaniercollege.qc.ca/~physics/KRESHNIK_LECTURES/NYA NYA] <br>
* [http://gauss.vaniercollege.qc.ca/~physics/KRESHNIK_LECTURES/NYB NYB] <br>
* [http://gauss.vaniercollege.qc.ca/~physics/KRESHNIK_LECTURES/NYC NYC] <br>
<br>

== LABS: USEFUL MATERIAL==

* [http://www.lon-capa.org/~mmp/applist/sigfig/sig.htm Significant Figures]<br>

* [http://www.learnerstv.com/animation/animation.php?ani=94&cat=physics Reading a Micrometer Scale]<br>

* [[Uncertainties in Measurement]]
:''by Kreshnik Angoni''


* [[Measurement and Data Analysis]]
:''by Kreshnik Angoni''

* [[Preparation for Labs]]
:''by Helena Dedic''


<br>

==ADDITIONAL RESOURCES==
* [[The Exponential Function and Its Applications in Science]]
*:''by Don Hetherington''

* [http://theengineerspulse.blogspot.com/p/for-physics-students.html Physics articles organized by course subject]
*:''by Stephen Cohen''

* [[Study Skills]]

* [https://www.youtube.com/channel/UCpVm6r2eaxwTcSznVPm51AA/playlists Videos by Learning Commons on Various Topics like referencing and use of Office365]

===Career-Related Articles===
* [[Things I wish I knew before my first job]]
*:''by Scott Redmond''

* [[Choosing the Right Career Path]]
*:''by Scott Redmond''

==PHYSICS <span style="color:Blue">'''''F</span><span style="color:Green">U</span><span style="color:Red">N</span>'''''==


*[[A Light in the Dark]]
<br>


== FOR TEACHERS ==

* [http://gauss.vaniercollege.qc.ca/twiki Teacher WIKI]
<br><br>