-
What is Least Squares Estimation?
Explains Least Squares (LS) Estimation with two examples: 1. line-fitting a data set, and 2. digital communications. Derives the LS equation and shows how it can be viewed as a pseudo inverse.
Related videos: (see http://iaincollings.com)
• What is Fisher Information? https://youtu.be/82molmnRCg0
• What is an Adaptive Step Size in Parameter Estimation? https://youtu.be/Nwm1cngRta8
• What is the Kalman Filter? https://youtu.be/OiUS2926nQM
• How are Matched Filter (MF), Zero Forcing (ZF), and MMSE Related? https://youtu.be/U3qjVgX2poM
• MIMO Communications https://youtu.be/TC19gMQ6azE
• What is Intersymbol Interference ISI? https://youtu.be/I087FUvW2ys
• Signal Model for MIMO and CDMA https://youtu.be/q9LuY-WQNhw
• What is a Decision Feedback Equalizer (DFE)? https://youtu.be/a5rDgnR5Kzs
For...
published: 15 Nov 2021
-
Linear Regression Using Least Squares Method - Line of Best Fit Equation
This statistics video tutorial explains how to find the equation of the line that best fits the observed data using the least squares method of linear regression.
Correlation Coefficient: https://www.youtube.com/watch?v=11c9cs6WpJU
Covariance and Correlation Coefficient:
https://www.youtube.com/watch?v=5wIiOFnXSYs
How To Calculate Covariance:
https://www.youtube.com/watch?v=rb2nU7YZV_I
Least Squares Method:
https://www.youtube.com/watch?v=P8hT5nDai6A
Averages and Uncertainty:
https://www.youtube.com/watch?v=CSJewgNUZKw
_____________________________
Introduction to Statistics:
https://www.youtube.com/watch?v=XZo4xyJXCak
Mean, Median...
published: 14 Jul 2020
-
The Main Ideas of Fitting a Line to Data (The Main Ideas of Least Squares and Linear Regression.)
Fitting a line to data is actually pretty straightforward.
For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/
If you'd like to support StatQuest, please consider...
Buying The StatQuest Illustrated Guide to Machine Learning!!!
PDF - https://statquest.gumroad.com/l/wvtmc
Paperback - https://www.amazon.com/dp/B09ZCKR4H6
Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC
Patreon: https://www.patreon.com/statquest
...or...
YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join
...a cool StatQuest t-shirt or sweatshirt:
https://shop.spreadshirt.com/statquest-with-josh-starmer/
...buying one or two of my songs (or go large and get a whole album!)
https://joshuastarmer.bandcamp.com/
...or just donating to StatQuest!
...
published: 22 May 2017
-
Deriving the least squares estimators of the slope and intercept (simple linear regression)
I derive the least squares estimators of the slope and intercept in simple linear regression (Using summation notation, and no matrices.) I assume that the viewer has already been introduced to the linear regression model, but I do provide a brief review in the first few minutes. I assume that you have a basic knowledge of differential calculus, including the power rule and the chain rule.
If you are already familiar with the problem, and you are just looking for help with the mathematics of the derivation, the derivation starts at 3:26.
At the end of the video, I illustrate that sum(X_i-X bar)(Y_i - Y bar) = sum X_i(Y_i - Y bar) =sum Y_i(X_i - X bar) , and that sum(X_i-X bar)^2 = sum X_i(X_i - X bar).
There are, of course, a number of ways of expressing the formula for the slope es...
published: 22 Mar 2019
-
Least Squares Estimators - in summary
This video describes the benefit of using Least Squares Estimators, as a method to estimate population parameters. Check out https://ben-lambert.com/econometrics-course-problem-sets-and-data/ for course materials, and information regarding updates on each of the courses. Quite excitingly (for me at least), I am about to publish a whole series of new videos on Bayesian statistics on youtube. See here for information: https://ben-lambert.com/bayesian/ Accompanying this series, there will be a book: https://www.amazon.co.uk/gp/product/1473916364/ref=pe_3140701_247401851_em_1p_0_ti
published: 28 May 2013
-
Introduction to residuals and least squares regression
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/ap-statistics/bivariate-data-ap/xfb5d8e68:residuals/v/regression-residual-intro
Introduction to residuals and least squares regression
published: 25 May 2017
-
Linear Least Squares Estimation
In this lesson, we introduce the fundamental concept of linear least-squares estimation for estimation problems in which the observation model is linear, and show how to determine the optimal estimator from the linear model and observations.
published: 15 Jan 2019
-
Least squares approximation | Linear Algebra | Khan Academy
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/linear-algebra/alternate-bases/orthogonal-projections/v/linear-algebra-least-squares-approximation
The least squares approximation for otherwise unsolvable equations
Watch the next lesson: https://www.khanacademy.org/math/linear-algebra/alternate_bases/orthogonal_projections/v/linear-algebra-least-squares-examples?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Missed the previous lesson?
https://www.khanacademy.org/math/linear-algebra/alternate_bases/orthogonal_projections/v/linear-alg-projection-is-closest-vector-in-subspace?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Linear Algebra on Khan Academy: Have you ever wondered what the differ...
published: 10 Nov 2009
-
Level 2 - Quantitative Methods & Derivatives
published: 19 Aug 2024
-
Least squares using matrices | Lecture 26 | Matrix Algebra for Engineers
Definition of the least-squares problem for fitting a line through noisy data.
Join me on Coursera: https://imp.i384100.net/mathematics-for-engineers
Lecture notes at http://www.math.ust.hk/~machas/matrix-algebra-for-engineers.pdf
Paperback at https://www.amazon.com/Matrix-Algebra-Engineers-Mathematics/dp/B0BJYMGT6S/
Subscribe to my channel: http://www.youtube.com/user/jchasnov?sub_confirmation=1
published: 10 Jul 2018
14:31
What is Least Squares Estimation?
Explains Least Squares (LS) Estimation with two examples: 1. line-fitting a data set, and 2. digital communications. Derives the LS equation and shows how it ca...
Explains Least Squares (LS) Estimation with two examples: 1. line-fitting a data set, and 2. digital communications. Derives the LS equation and shows how it can be viewed as a pseudo inverse.
Related videos: (see http://iaincollings.com)
• What is Fisher Information? https://youtu.be/82molmnRCg0
• What is an Adaptive Step Size in Parameter Estimation? https://youtu.be/Nwm1cngRta8
• What is the Kalman Filter? https://youtu.be/OiUS2926nQM
• How are Matched Filter (MF), Zero Forcing (ZF), and MMSE Related? https://youtu.be/U3qjVgX2poM
• MIMO Communications https://youtu.be/TC19gMQ6azE
• What is Intersymbol Interference ISI? https://youtu.be/I087FUvW2ys
• Signal Model for MIMO and CDMA https://youtu.be/q9LuY-WQNhw
• What is a Decision Feedback Equalizer (DFE)? https://youtu.be/a5rDgnR5Kzs
For a full list of Videos and Summary Sheets, goto: http://iaincollings.com
https://wn.com/What_Is_Least_Squares_Estimation
Explains Least Squares (LS) Estimation with two examples: 1. line-fitting a data set, and 2. digital communications. Derives the LS equation and shows how it can be viewed as a pseudo inverse.
Related videos: (see http://iaincollings.com)
• What is Fisher Information? https://youtu.be/82molmnRCg0
• What is an Adaptive Step Size in Parameter Estimation? https://youtu.be/Nwm1cngRta8
• What is the Kalman Filter? https://youtu.be/OiUS2926nQM
• How are Matched Filter (MF), Zero Forcing (ZF), and MMSE Related? https://youtu.be/U3qjVgX2poM
• MIMO Communications https://youtu.be/TC19gMQ6azE
• What is Intersymbol Interference ISI? https://youtu.be/I087FUvW2ys
• Signal Model for MIMO and CDMA https://youtu.be/q9LuY-WQNhw
• What is a Decision Feedback Equalizer (DFE)? https://youtu.be/a5rDgnR5Kzs
For a full list of Videos and Summary Sheets, goto: http://iaincollings.com
- published: 15 Nov 2021
- views: 23018
15:05
Linear Regression Using Least Squares Method - Line of Best Fit Equation
This statistics video tutorial explains how to find the equation of the line that best fits the observed data using the least squares method of linear regressio...
This statistics video tutorial explains how to find the equation of the line that best fits the observed data using the least squares method of linear regression.
Correlation Coefficient: https://www.youtube.com/watch?v=11c9cs6WpJU
Covariance and Correlation Coefficient:
https://www.youtube.com/watch?v=5wIiOFnXSYs
How To Calculate Covariance:
https://www.youtube.com/watch?v=rb2nU7YZV_I
Least Squares Method:
https://www.youtube.com/watch?v=P8hT5nDai6A
Averages and Uncertainty:
https://www.youtube.com/watch?v=CSJewgNUZKw
_____________________________
Introduction to Statistics:
https://www.youtube.com/watch?v=XZo4xyJXCak
Mean, Median, Mode, & Range:
https://www.youtube.com/watch?v=A1mQ9kD-i9I
Arithmetic, Geometric, & Harmonic Mean:
https://www.youtube.com/watch?v=6G6i8vSa8Zs
Interquartile Range & Outliers:
https://www.youtube.com/watch?v=STSP8gTSdT8
Standard Deviation:
https://www.youtube.com/watch?v=IaTFpp-uzp0
_______________________________
Introduction to Probability:
https://www.youtube.com/watch?v=SkidyDQuupA
Probability Formulas:
https://www.youtube.com/watch?v=bddckR734aM
Conditional Probability:
https://www.youtube.com/watch?v=sqDVrXq_eh0
Probability Tree Diagrams:
https://www.youtube.com/watch?v=w4wKXVwtGac
Probability - Standard Normal Distributions:
https://www.youtube.com/watch?v=CjF_yQ2N638
https://wn.com/Linear_Regression_Using_Least_Squares_Method_Line_Of_Best_Fit_Equation
This statistics video tutorial explains how to find the equation of the line that best fits the observed data using the least squares method of linear regression.
Correlation Coefficient: https://www.youtube.com/watch?v=11c9cs6WpJU
Covariance and Correlation Coefficient:
https://www.youtube.com/watch?v=5wIiOFnXSYs
How To Calculate Covariance:
https://www.youtube.com/watch?v=rb2nU7YZV_I
Least Squares Method:
https://www.youtube.com/watch?v=P8hT5nDai6A
Averages and Uncertainty:
https://www.youtube.com/watch?v=CSJewgNUZKw
_____________________________
Introduction to Statistics:
https://www.youtube.com/watch?v=XZo4xyJXCak
Mean, Median, Mode, & Range:
https://www.youtube.com/watch?v=A1mQ9kD-i9I
Arithmetic, Geometric, & Harmonic Mean:
https://www.youtube.com/watch?v=6G6i8vSa8Zs
Interquartile Range & Outliers:
https://www.youtube.com/watch?v=STSP8gTSdT8
Standard Deviation:
https://www.youtube.com/watch?v=IaTFpp-uzp0
_______________________________
Introduction to Probability:
https://www.youtube.com/watch?v=SkidyDQuupA
Probability Formulas:
https://www.youtube.com/watch?v=bddckR734aM
Conditional Probability:
https://www.youtube.com/watch?v=sqDVrXq_eh0
Probability Tree Diagrams:
https://www.youtube.com/watch?v=w4wKXVwtGac
Probability - Standard Normal Distributions:
https://www.youtube.com/watch?v=CjF_yQ2N638
- published: 14 Jul 2020
- views: 1540485
9:22
The Main Ideas of Fitting a Line to Data (The Main Ideas of Least Squares and Linear Regression.)
Fitting a line to data is actually pretty straightforward.
For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/
If ...
Fitting a line to data is actually pretty straightforward.
For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/
If you'd like to support StatQuest, please consider...
Buying The StatQuest Illustrated Guide to Machine Learning!!!
PDF - https://statquest.gumroad.com/l/wvtmc
Paperback - https://www.amazon.com/dp/B09ZCKR4H6
Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC
Patreon: https://www.patreon.com/statquest
...or...
YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join
...a cool StatQuest t-shirt or sweatshirt:
https://shop.spreadshirt.com/statquest-with-josh-starmer/
...buying one or two of my songs (or go large and get a whole album!)
https://joshuastarmer.bandcamp.com/
...or just donating to StatQuest!
https://www.paypal.me/statquest
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
https://twitter.com/joshuastarmer
#statquest #regression
https://wn.com/The_Main_Ideas_Of_Fitting_A_Line_To_Data_(The_Main_Ideas_Of_Least_Squares_And_Linear_Regression.)
Fitting a line to data is actually pretty straightforward.
For a complete index of all the StatQuest videos, check out:
https://statquest.org/video-index/
If you'd like to support StatQuest, please consider...
Buying The StatQuest Illustrated Guide to Machine Learning!!!
PDF - https://statquest.gumroad.com/l/wvtmc
Paperback - https://www.amazon.com/dp/B09ZCKR4H6
Kindle eBook - https://www.amazon.com/dp/B09ZG79HXC
Patreon: https://www.patreon.com/statquest
...or...
YouTube Membership: https://www.youtube.com/channel/UCtYLUTtgS3k1Fg4y5tAhLbw/join
...a cool StatQuest t-shirt or sweatshirt:
https://shop.spreadshirt.com/statquest-with-josh-starmer/
...buying one or two of my songs (or go large and get a whole album!)
https://joshuastarmer.bandcamp.com/
...or just donating to StatQuest!
https://www.paypal.me/statquest
Lastly, if you want to keep up with me as I research and create new StatQuests, follow me on twitter:
https://twitter.com/joshuastarmer
#statquest #regression
- published: 22 May 2017
- views: 692280
12:13
Deriving the least squares estimators of the slope and intercept (simple linear regression)
I derive the least squares estimators of the slope and intercept in simple linear regression (Using summation notation, and no matrices.) I assume that the vie...
I derive the least squares estimators of the slope and intercept in simple linear regression (Using summation notation, and no matrices.) I assume that the viewer has already been introduced to the linear regression model, but I do provide a brief review in the first few minutes. I assume that you have a basic knowledge of differential calculus, including the power rule and the chain rule.
If you are already familiar with the problem, and you are just looking for help with the mathematics of the derivation, the derivation starts at 3:26.
At the end of the video, I illustrate that sum(X_i-X bar)(Y_i - Y bar) = sum X_i(Y_i - Y bar) =sum Y_i(X_i - X bar) , and that sum(X_i-X bar)^2 = sum X_i(X_i - X bar).
There are, of course, a number of ways of expressing the formula for the slope estimator, and I make no attempt to list them all in this video.
https://wn.com/Deriving_The_Least_Squares_Estimators_Of_The_Slope_And_Intercept_(Simple_Linear_Regression)
I derive the least squares estimators of the slope and intercept in simple linear regression (Using summation notation, and no matrices.) I assume that the viewer has already been introduced to the linear regression model, but I do provide a brief review in the first few minutes. I assume that you have a basic knowledge of differential calculus, including the power rule and the chain rule.
If you are already familiar with the problem, and you are just looking for help with the mathematics of the derivation, the derivation starts at 3:26.
At the end of the video, I illustrate that sum(X_i-X bar)(Y_i - Y bar) = sum X_i(Y_i - Y bar) =sum Y_i(X_i - X bar) , and that sum(X_i-X bar)^2 = sum X_i(X_i - X bar).
There are, of course, a number of ways of expressing the formula for the slope estimator, and I make no attempt to list them all in this video.
- published: 22 Mar 2019
- views: 244594
4:52
Least Squares Estimators - in summary
This video describes the benefit of using Least Squares Estimators, as a method to estimate population parameters. Check out https://ben-lambert.com/econometric...
This video describes the benefit of using Least Squares Estimators, as a method to estimate population parameters. Check out https://ben-lambert.com/econometrics-course-problem-sets-and-data/ for course materials, and information regarding updates on each of the courses. Quite excitingly (for me at least), I am about to publish a whole series of new videos on Bayesian statistics on youtube. See here for information: https://ben-lambert.com/bayesian/ Accompanying this series, there will be a book: https://www.amazon.co.uk/gp/product/1473916364/ref=pe_3140701_247401851_em_1p_0_ti
https://wn.com/Least_Squares_Estimators_In_Summary
This video describes the benefit of using Least Squares Estimators, as a method to estimate population parameters. Check out https://ben-lambert.com/econometrics-course-problem-sets-and-data/ for course materials, and information regarding updates on each of the courses. Quite excitingly (for me at least), I am about to publish a whole series of new videos on Bayesian statistics on youtube. See here for information: https://ben-lambert.com/bayesian/ Accompanying this series, there will be a book: https://www.amazon.co.uk/gp/product/1473916364/ref=pe_3140701_247401851_em_1p_0_ti
- published: 28 May 2013
- views: 138779
7:39
Introduction to residuals and least squares regression
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/ap-statistics/bivariate-data-ap/xf...
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/ap-statistics/bivariate-data-ap/xfb5d8e68:residuals/v/regression-residual-intro
Introduction to residuals and least squares regression
https://wn.com/Introduction_To_Residuals_And_Least_Squares_Regression
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/ap-statistics/bivariate-data-ap/xfb5d8e68:residuals/v/regression-residual-intro
Introduction to residuals and least squares regression
- published: 25 May 2017
- views: 616797
6:38
Linear Least Squares Estimation
In this lesson, we introduce the fundamental concept of linear least-squares estimation for estimation problems in which the observation model is linear, and sh...
In this lesson, we introduce the fundamental concept of linear least-squares estimation for estimation problems in which the observation model is linear, and show how to determine the optimal estimator from the linear model and observations.
https://wn.com/Linear_Least_Squares_Estimation
In this lesson, we introduce the fundamental concept of linear least-squares estimation for estimation problems in which the observation model is linear, and show how to determine the optimal estimator from the linear model and observations.
- published: 15 Jan 2019
- views: 6092
15:32
Least squares approximation | Linear Algebra | Khan Academy
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/linear-algebra/alternate-bases/ort...
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/linear-algebra/alternate-bases/orthogonal-projections/v/linear-algebra-least-squares-approximation
The least squares approximation for otherwise unsolvable equations
Watch the next lesson: https://www.khanacademy.org/math/linear-algebra/alternate_bases/orthogonal_projections/v/linear-algebra-least-squares-examples?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Missed the previous lesson?
https://www.khanacademy.org/math/linear-algebra/alternate_bases/orthogonal_projections/v/linear-alg-projection-is-closest-vector-in-subspace?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Linear Algebra on Khan Academy: Have you ever wondered what the difference is between speed and velocity? Ever try to visualize in four dimensions or six or seven? Linear algebra describes things in two dimensions, but many of the concepts can be extended into three, four or more. Linear algebra implies two dimensional reasoning, however, the concepts covered in linear algebra provide the basis for multi-dimensional representations of mathematical reasoning. Matrices, vectors, vector spaces, transformations, eigenvectors/values all help us to visualize and understand multi dimensional concepts. This is an advanced course normally taken by science or engineering majors after taking at least two semesters of calculus (although calculus really isn't a prereq) so don't confuse this with regular high school algebra.
About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.
For free. For everyone. Forever. #YouCanLearnAnything
Subscribe to KhanAcademy’s Linear Algebra channel: https://www.youtube.com/channel/UCGYSKl6e3HM0PP7QR35Crug?sub_confirmation=1
Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy
https://wn.com/Least_Squares_Approximation_|_Linear_Algebra_|_Khan_Academy
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/linear-algebra/alternate-bases/orthogonal-projections/v/linear-algebra-least-squares-approximation
The least squares approximation for otherwise unsolvable equations
Watch the next lesson: https://www.khanacademy.org/math/linear-algebra/alternate_bases/orthogonal_projections/v/linear-algebra-least-squares-examples?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Missed the previous lesson?
https://www.khanacademy.org/math/linear-algebra/alternate_bases/orthogonal_projections/v/linear-alg-projection-is-closest-vector-in-subspace?utm_source=YT&utm_medium=Desc&utm_campaign=LinearAlgebra
Linear Algebra on Khan Academy: Have you ever wondered what the difference is between speed and velocity? Ever try to visualize in four dimensions or six or seven? Linear algebra describes things in two dimensions, but many of the concepts can be extended into three, four or more. Linear algebra implies two dimensional reasoning, however, the concepts covered in linear algebra provide the basis for multi-dimensional representations of mathematical reasoning. Matrices, vectors, vector spaces, transformations, eigenvectors/values all help us to visualize and understand multi dimensional concepts. This is an advanced course normally taken by science or engineering majors after taking at least two semesters of calculus (although calculus really isn't a prereq) so don't confuse this with regular high school algebra.
About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.
For free. For everyone. Forever. #YouCanLearnAnything
Subscribe to KhanAcademy’s Linear Algebra channel: https://www.youtube.com/channel/UCGYSKl6e3HM0PP7QR35Crug?sub_confirmation=1
Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy
- published: 10 Nov 2009
- views: 548298
10:15
Least squares using matrices | Lecture 26 | Matrix Algebra for Engineers
Definition of the least-squares problem for fitting a line through noisy data.
Join me on Coursera: https://imp.i384100.net/mathematics-for-engineers
Lecture ...
Definition of the least-squares problem for fitting a line through noisy data.
Join me on Coursera: https://imp.i384100.net/mathematics-for-engineers
Lecture notes at http://www.math.ust.hk/~machas/matrix-algebra-for-engineers.pdf
Paperback at https://www.amazon.com/Matrix-Algebra-Engineers-Mathematics/dp/B0BJYMGT6S/
Subscribe to my channel: http://www.youtube.com/user/jchasnov?sub_confirmation=1
https://wn.com/Least_Squares_Using_Matrices_|_Lecture_26_|_Matrix_Algebra_For_Engineers
Definition of the least-squares problem for fitting a line through noisy data.
Join me on Coursera: https://imp.i384100.net/mathematics-for-engineers
Lecture notes at http://www.math.ust.hk/~machas/matrix-algebra-for-engineers.pdf
Paperback at https://www.amazon.com/Matrix-Algebra-Engineers-Mathematics/dp/B0BJYMGT6S/
Subscribe to my channel: http://www.youtube.com/user/jchasnov?sub_confirmation=1
- published: 10 Jul 2018
- views: 52347