Cache Lack Math & Stats Lectures
Cache Lack Math & Stats Lectures
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All of Linear Regression Analysis
This video is a review of all the topics covered in my lecture course, Linear Regression Analysis. It quickly covers standard topics like least squares estimation, hypothesis testing, residuals, outlier, polynomial regression, transformations, variable selection, ridge & lasso, and Logisitic regression.
My course notes can be found at sites.ualberta.ca/~kashlak/kashTeaching.html
มุมมอง: 871

วีดีโอ

Linear Regression Analysis 0: R Tutorial
มุมมอง 8552 ปีที่แล้ว
A short tutorial covering how to download R and R Studio, how to load data in to R, and how to fit basic linear models in R. The code used in this video can be downloaded at sites.ualberta.ca/~kashlak/data/rTutorial.r The data used in this video can be downloaded at sites.ualberta.ca/~kashlak/data/usaData.csv My lecture notes on linear regression analysis can be found at sites.ualberta.ca/~kash...
Design of Experiments, Lecture 11: 2^k Blocking and Variance
มุมมอง 2242 ปีที่แล้ว
We continue discussing full factorial designs by looking at blocking within a full factorial design while making sure we do not confound any important factors. Testing for homogeneity of variance is also discussed.
Design of Experiments, Lecture 14: 3k Full Factorial Designs
มุมมอง 1.4K2 ปีที่แล้ว
We discuss the 3^k full factorial design, which comes with more complications than the previously discussed 2^k designs. Polynomial contrasts are also discussed. Typed lecture notes can be found at sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 8: Multiple Testing with FWER
มุมมอง 942 ปีที่แล้ว
In our first lecture on multiple testing corrections, we introduce the problem of multiple testing and the concept of familywise error rate. The Bonferroni, Sidak, and Holms methods are discussed as well as more general step up and step down methods. Typed lecture notes can be found at sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 10: Full Factorial Design
มุมมอง 9112 ปีที่แล้ว
In this lecture, we introduce the full factorial design crossing k binary factors on a sample size of 2^k. We discuss main and interaction effects as well as Lenth's method for computing significance when the experiment is not replicated. Typed lectures notes can be found at sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 12: Fractional Factorial Design
มุมมอง 2572 ปีที่แล้ว
Now, we introduce the fractional factorial design where all 2^k treatments are not tested. The defining contrast subgroup is discussed. Typed lecture note can be found at sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 13: Dealiasing Fractional Designs
มุมมอง 1052 ปีที่แล้ว
In fractional factorial designs, aliasing is a potential problem. In this lecture, we discuss follow-up studies for de-aliasing terms of interest. We also discuss optimal design criteria when performing follow-up tests. Typed lecture notes can be found at sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 9: Multiple Testing with FDR
มุมมอง 852 ปีที่แล้ว
In this lecture, we discuss the modern approach to multiple testing correction based on controlling the false discovery rate. The Benjamini-Hochberg method is discussed as well as the Benjamini-Yekutieli method. Typed lecture notes can be found at sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 7: Nested Factors and ANCOVA
มุมมอง 3732 ปีที่แล้ว
Nested factors are those where one factor is nested within another like teachers and students being nested within the school that they attend. ANCOVA is ANOVA with covariates. Often, we need to adjust for covariates when running an ANOVA design. Typed lecture notes can be found at: sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 6: Balanced Incomplete Block Designs and Split Plots
มุมมอง 1.2K2 ปีที่แล้ว
Continuing on with multi-way ANOVA, we discuss the balanced incomplete block design (BIBD), which is used when we can't test all treatments within every block, and we discuss the split plot design, which is used when all factors can't be completely randomized. Both of these designs remind us that we cannot analyse data unless we know how that data was collected. Course Lecture Notes: sites.ualb...
Design of Experiments, Lecture 4: Randomized Block Design
มุมมอง 2812 ปีที่แล้ว
Our first lecture on multi-way ANOVA introduces the randomized block design. The aim is to group like subjects into blocks to reduce variability in the response variable. We also discuss how a paired two-sample t-test is a type of randomized block design. Course Lecture Notes: sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 5: Two Way ANOVA and Latin Squares
มุมมอง 5192 ปีที่แล้ว
We first discuss two-way ANOVA where two experiment factors are considered at once on the same subjects. Then, we introduce the Latin square design which is used to test one experimental factor with two blocking factors in an efficient manor i.e. we aim to keep the sample size small while still controlling for confounding factors. Course Lecture Notes: sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 3: Cochran's Theorem
มุมมอง 5022 ปีที่แล้ว
We discuss the question, why do we do F-tests when analysing ANOVA models? The rest of this lecture is dedicated to proving Cochran's theorem, the main mathematical tool for design of experiments. Course Lecture Notes: sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 2: Post-Hoc Tukey Test
มุมมอง 3002 ปีที่แล้ว
We look further at one-way ANOVA. Specifically, we discuss the post-hoc Tukey test for testing for significance for pairwise differences among groups. We also briefly discuss random effects and sample size computation. Course Lecture Notes: sites.ualberta.ca/~kashlak/kashTeaching.html
Design of Experiments, Lecture 1: One-Way ANOVA
มุมมอง 1.7K2 ปีที่แล้ว
Design of Experiments, Lecture 1: One-Way ANOVA
Probability and Measure, Lecture 13: The Ergodic Theorem
มุมมอง 2K2 ปีที่แล้ว
Probability and Measure, Lecture 13: The Ergodic Theorem
Probability and Measure, Lecture 11: The Strong Law of Large Numbers
มุมมอง 1K2 ปีที่แล้ว
Probability and Measure, Lecture 11: The Strong Law of Large Numbers
Probability and Measure, Lecture 12: The Central Limit Theorem
มุมมอง 7672 ปีที่แล้ว
Probability and Measure, Lecture 12: The Central Limit Theorem
Probability and Measure, Lecture 10: Convergence of Measures
มุมมอง 1.5K2 ปีที่แล้ว
Probability and Measure, Lecture 10: Convergence of Measures
Probability and Measure, Lecture 9: Lp spaces and Inequalities
มุมมอง 1.2K2 ปีที่แล้ว
Probability and Measure, Lecture 9: Lp spaces and Inequalities
Time Series Analysis, Lecture 24: The GARCH Process
มุมมอง 6292 ปีที่แล้ว
Time Series Analysis, Lecture 24: The GARCH Process
Time Series Analysis: Review Lecture
มุมมอง 1882 ปีที่แล้ว
Time Series Analysis: Review Lecture
Time Series Analysis, Lecture 23: Exponential Smoothing
มุมมอง 3562 ปีที่แล้ว
Time Series Analysis, Lecture 23: Exponential Smoothing
Time Series Analysis, Lecture 19: Spectral Density and Distribution
มุมมอง 4K2 ปีที่แล้ว
Time Series Analysis, Lecture 19: Spectral Density and Distribution
Time Series Analysis, Lecture 22: Estimating the Spectral Density Part III
มุมมอง 3062 ปีที่แล้ว
Time Series Analysis, Lecture 22: Estimating the Spectral Density Part III
Time Series Analysis, Lecture 21: Estimating Spectral Density Part II
มุมมอง 2852 ปีที่แล้ว
Time Series Analysis, Lecture 21: Estimating Spectral Density Part II
Time Series Analysis, Lecture 20: Estimating the Spectral Density
มุมมอง 7222 ปีที่แล้ว
Time Series Analysis, Lecture 20: Estimating the Spectral Density
Time Series Analysis, Lecture 17: Seasonal ARIMA in R Studio
มุมมอง 4382 ปีที่แล้ว
Time Series Analysis, Lecture 17: Seasonal ARIMA in R Studio
Time Series Analysis, Lecture 18: Periodic Processes and the DFT
มุมมอง 7432 ปีที่แล้ว
Time Series Analysis, Lecture 18: Periodic Processes and the DFT

ความคิดเห็น

  • @FieldDebby-o5h
    @FieldDebby-o5h 3 วันที่ผ่านมา

    Smith Dorothy Harris Gary Davis Sandra

  • @martinsanchez-hw4fi
    @martinsanchez-hw4fi 8 วันที่ผ่านมา

    Shouldn't the denominator in the partial sum in 1:09:26 be (1-\theta) and not (1-\theta^2)?

  • @amorphous8826
    @amorphous8826 18 วันที่ผ่านมา

    👍

  • @Amirhosein_Farahmand
    @Amirhosein_Farahmand หลายเดือนก่อน

    is there any full course from you on the topic?

  • @njitnom
    @njitnom หลายเดือนก่อน

    at the proof at 55:13, why cant we just take epsilon = 0 from the beginning?

  • @viajeespacial5391
    @viajeespacial5391 2 หลายเดือนก่อน

    No entendí la varianza de la ultima sumatoria, por que queda elevado a "2j" ?

  • @siavashk100
    @siavashk100 2 หลายเดือนก่อน

    Infinite thanks to you. I was desperately looking for a good material to learn time series analysis basics. The topics are explained amazing.

  • @tochoXK3
    @tochoXK3 2 หลายเดือนก่อน

    Too much theoretical stuff, too much complex notation. I'd prefer a straightforward explanation how SARIMA works (like "here are all the relevant formulas, here's an example-based explanation of the formulas).

  • @arunabhoroy2033
    @arunabhoroy2033 2 หลายเดือนก่อน

    you have a type error on the notes in symmetric difference

  • @chimiwangmo1512
    @chimiwangmo1512 3 หลายเดือนก่อน

    Thank you so much for a great explanation. Can you please also discuss regarding Yekutieli-Benjamini approach which considers dependency between the tests?

  • @arunabhoroy2033
    @arunabhoroy2033 3 หลายเดือนก่อน

    Sir, what book do you recommend for studying probabilistic measure theory?

  • @polandturtle
    @polandturtle 3 หลายเดือนก่อน

    Direct link to lecture notes so you don’t have to search: sites.ualberta.ca/~kashlak/data/stat571.pdf

  • @AaBbCize
    @AaBbCize 3 หลายเดือนก่อน

    At 1:14:25, why does the second equality follow from the first? While intuitive (the RHS is based upon a partition of E), its not clear to me why writing u*(E) in this manner is rigorously justified. We haven’t shown that u* is countably (or even finitely) additive, so why are we allowed break up u*(E) in this manner? Any help would be much appreciated!

    • @AaBbCize
      @AaBbCize 3 หลายเดือนก่อน

      Moreover, it appears to me that the first term on the RHS implies that the intersection of B1 and B2 is u*-measurable - the very thing we are trying to prove! This is because if we define E to be the ambient space (which we are allowed to do since E is allowed to be any subset of the ambient space), then the first term is equal to u* evaluated at the intersection of B1 and B2 - but a numerical value can only be returned if this argument is contained within the domain of u*, which is what we are trying to prove??😓

  • @gulzameenbaloch9339
    @gulzameenbaloch9339 4 หลายเดือนก่อน

    Thank you so much 😊

  • @babakakbarzadeh1819
    @babakakbarzadeh1819 4 หลายเดือนก่อน

    You have bad handwriting :D but it is very useful content, Thank you.

  • @rogerchen3663
    @rogerchen3663 5 หลายเดือนก่อน

    Hi sir, I'm wondering why at around 1:17:00 we know we can extend nu to sigma(A2)? Doesn't this require that the measures are both sigma finite? I'm not sure whether that was assumed / clear

  • @amorphous8826
    @amorphous8826 5 หลายเดือนก่อน

    👍

  • @amorphous8826
    @amorphous8826 5 หลายเดือนก่อน

    👍

  • @mazharmertulukaya2091
    @mazharmertulukaya2091 5 หลายเดือนก่อน

    Thank you sir for the lecture

  • @mazharmertulukaya2091
    @mazharmertulukaya2091 5 หลายเดือนก่อน

    thank you very much for the lecture. How is the dickeyt fuller test conducted ?

  • @dacianbonta2840
    @dacianbonta2840 5 หลายเดือนก่อน

    @45:50 up to scaling, obviously

  • @konstantinosbanos
    @konstantinosbanos 6 หลายเดือนก่อน

    Hello Professor, can you tell me how your board application is called? Thank you in advance!

  • @mariamamirhassan
    @mariamamirhassan 6 หลายเดือนก่อน

    Thank you from Egypt

  • @voitikfamily2679
    @voitikfamily2679 6 หลายเดือนก่อน

    The asymptotic result for AR(1) and MA(1) is different from the book by sigma^2 on the variance (page 134). BTW, thank you so much for sharing this few lectures. I was reading the book multiple times but having trouble really understanding the idea on top of all the maths presented. You really bring the fundamental idea out with all the explanations. I greatly appreciate it.

  • @andi96kafunse
    @andi96kafunse 6 หลายเดือนก่อน

    Big thank you from Germany!! Your lecture series really saves me while preparing for my exam. Your deep undestanding of measure theory shows in very undestandable explanations. Didn't find any other similarly understandable videos on this level of detail and formal correctness.

  • @voitikfamily2679
    @voitikfamily2679 7 หลายเดือนก่อน

    Thank you!

  • @LDB-cz1wf
    @LDB-cz1wf 7 หลายเดือนก่อน

    I appreciate that you provide intuition for new definitions and gently introduce them. btw, "outer measure" is spelled with just one "t" (unless it's a Canadian spelling I'm unaware of).

  • @voitikfamily2679
    @voitikfamily2679 7 หลายเดือนก่อน

    Thank you so much.

  • @kumarrahul1328
    @kumarrahul1328 7 หลายเดือนก่อน

    Realy clever explanation❤❤❤

  • @helensol2485
    @helensol2485 7 หลายเดือนก่อน

    Finally I got the measure theory. Thank you so much! Can you do the same with the Functional Analysis?

  • @voitikfamily2679
    @voitikfamily2679 7 หลายเดือนก่อน

    Excellent teaching. I am reading Stoffer’s book and hit a brick wall when it gets to spectral. You help me push through. Many thanks.

  • @AllanAngusADA
    @AllanAngusADA 8 หลายเดือนก่อน

    At around 1:26, you say mu-star "less than" but you write "greater than." I think you meant what you said. Yes?

  • @kamalhaider397
    @kamalhaider397 8 หลายเดือนก่อน

    It's interesting. Did you recommend any book in order to follow all playlist???

  • @fernandojackson7207
    @fernandojackson7207 8 หลายเดือนก่อน

    Prof Kashlak, excellent lecture. I believe at 40:27, it should be the union of [-i,-i-1]. Your union can be made disjoint if you use half-open intervals, [i,i+1), etc. , defining m([a,b})=m[[a,b]]=b-a. Thanks to you, your school for the great lecture, material. I know all this is obvious to you, guess yu just made a small mistake.

  • @theforeskinsnatcher373
    @theforeskinsnatcher373 8 หลายเดือนก่อน

    Wow these lectures are great! keep it up!

  • @parnzaa007
    @parnzaa007 8 หลายเดือนก่อน

    You're so clearly explained! Thank you so much for uploading this.

  • @welcometothemadhouse
    @welcometothemadhouse 9 หลายเดือนก่อน

    the best lectures on measure and probability theory I have seen, surprisingly because you give some varied proofs in your videos it pairs quite nicely with the springer textbooks in statistics "measure theory and probability theory" and the Oxford University lecture notes. The lectures are particularly good because you give some intuition into the subject which is needed sometimes, especially from a geometric point of view. These two things are not easy to come by with measure theory so therefore i appreciate that personally.

  • @actualBIAS
    @actualBIAS 9 หลายเดือนก่อน

    Your lectures are indeed viewed by people not in your class and I must say, you sir are a great lecturor.

  • @actualBIAS
    @actualBIAS 9 หลายเดือนก่อน

    Thank you so much! It's the first time that I understand what's going on!

  • @actualBIAS
    @actualBIAS 9 หลายเดือนก่อน

    WHAT A NICE INTRO. I will stay!

  • @fredxu9826
    @fredxu9826 9 หลายเดือนก่อน

    Hi, professor, any plan for further topics following probability and measure, such as stochastic process? I really enjoy your lectures!!

  • @seka8601
    @seka8601 9 หลายเดือนก่อน

    Il ilke the music in the beginning

  • @fernandojackson7207
    @fernandojackson7207 9 หลายเดือนก่อน

    Would there be a way of computing the order statistics for these t-statistics, re the tukey test?

  • @fernandojackson7207
    @fernandojackson7207 9 หลายเดือนก่อน

    Don't know that much about Canada, but , by being from a province, do you mean being born there? What if you move, at say, 2 years of age? Or move more than one? Maybe could do some sort of blocking in that regard? Or maybe assign to a person the province where they've lived the highest % of their lives?

  • @fernandojackson7207
    @fernandojackson7207 9 หลายเดือนก่อน

    Excelent lecture. In 16:11, by errors, it seems it would be residuals? If I may, pr ? of., a general question, if it makes sense, how to come up with the statistic to be used to do a given hypothesis test tests, e.g.,[ (n-1)^2*S_i]/Sigma^2 ? Or how did , e.g., Bartlett come up with his choice of statistic to test for equality of variances? Is there a general method do construct/define these statistics? Thank you.

  • @shayansalesi3851
    @shayansalesi3851 9 หลายเดือนก่อน

    Excellent! A bit on the longer side, but really helped to build intuition. Enjoyed all of it!

  • @tyfu223
    @tyfu223 9 หลายเดือนก่อน

    Excellent lecture! Thanks a lot.

  • @benjamindavid7371
    @benjamindavid7371 9 หลายเดือนก่อน

    I think for the inequality at 1:27:18 to hold we are assuming that the outer measure is continuous, which might still need some justification?

    • @JakeGameroff
      @JakeGameroff 13 วันที่ผ่านมา

      exactly why I'm browsing the comments as well

    • @JakeGameroff
      @JakeGameroff 13 วันที่ผ่านมา

      I figured it out, in case anyone else was confused. Monotonicity will suffice since B1^c cap B2^c cap ... Bn^c is a subset of B for every n.

  • @francoisl7663
    @francoisl7663 10 หลายเดือนก่อน

    Moved over to this new channel. Once again, awesome can't wait to get through all the DOE videos.

  • @francoisl7663
    @francoisl7663 10 หลายเดือนก่อน

    Man this channel is awesome. Can't wait to go through al the videos. Thank you!