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Statistics DSBA 2021/2022 - История изменений
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2021-10-25T15:55:35Z
<p><span class="autocomment">Lecture notes</span></p>
<p><b>Новая страница</b></p><div>= About =<br />
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This page contains information about Statistics course at DSBA.<br />
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Actual syllabus can be found [https://www.dropbox.com/s/1rxg7910zxakznv/Syllabus%20for%20Statistics%20CS%20HSEv2.pdf?dl=0 here].<br />
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= Teachers and assistants =<br />
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{| class="wikitable" style="text-align:center"<br />
|-<br />
! Group!! БПАД201 !! БПАД202 !! БПАД203 !! БПАД204<br />
|-<br />
|| Teacher ||colspan="4"| [https://www.hse.ru/org/persons/14276760 Peter Lukianchenko] <br />
|-<br />
|| Assistant || Ivanov Anton || Varvara Erinova || Egor Nikitin || Kseniia Shilova<br />
|}<br />
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If you feel like something is missing from this page, please feel free to ping [https://t.me/axycity Axyniia].<br />
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= Communication =<br />
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We use Telegram messenger to share files and Zoom meetings links.<br />
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Link to course channel: [https://t.me/stathard20 click]<br />
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= Lecture notes =<br />
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'''[https://www.dropbox.com/s/9rfctx62918trey/1%20Lect%20Sept1_d.pdf?dl=0 Lecture 1]''' (01.09.2021). Welcome to Statistics!<br />
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'''[https://www.dropbox.com/s/ttiuqmi7nu9e641/Lecture%202.pdf?dl=0 Lecture 2]''' (08.09.2021). Axioms of probability. Basics of combinatorics. Geometric probability.<br />
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'''[https://www.dropbox.com/s/26t4yx47iijxmq9/3.%20Stat_3%20%28ppt%2097-2003%29_d.pdf?dl=0 Lecture 3]''' (15.09.2021). Random variable. Discrete pdf. Expectation and variance. Bernoulli distribution. Bayes rule.<br />
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'''[https://www.dropbox.com/s/41sobtq08y48947/4%20Lecture%20.pdf?dl=0 Lecture 4]''' (22.09.2021). Joint discrete distribution. Conditional probability. Covariance. Correlation.<br />
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'''[https://www.dropbox.com/s/1q0ac1abnpw9tne/5%20Statistics_Lect%20sept%2029_done%20%20-%20%20Compatibility%20Mode.pdf?dl=0 Lecture 5]''' (29.09.2021) Covariance. Correlation. Continuous distribution.<br />
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'''[https://www.dropbox.com/s/usyhdpte0uoakjf/6%20Lecture.pdf?dl=0 Lecture 6]''' (06.10.2021) Continuous distribution.<br />
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'''[https://www.dropbox.com/s/xvcmqibbyw22y7k/Lecture%207.pdf?dl=0 Lecture 7]''' (13.10.2021) Normal distribution. Standard normal distribution. Joint distribution. Uniform distribution.<br />
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'''[https://www.dropbox.com/s/ry3emtfy2f6z4md/8%20Lecture%20.pdf?dl=0 Lecture 8]''' (27.10.2021) Data representation. Exponential, Poisson, and Uniform distributions. Continuity correction.<br />
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'''[https://www.dropbox.com/s/s4gnj126k1qb2wt/9%2010%20Lecture.pdf?dl=0 Lectures 9-10]''' (2-3.11.2021) Law of large numbers. Distribution of a function of random variable. Distribution of sample proportion. Chi-squared distribution.<br />
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= Seminar notes =<br />
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= Hometask =<br />
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= Grading system =<br />
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Interim assessment (1 module)<br />
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0.7 * FallMock (October Midterm) + 0.3 * First module Home assignments<br />
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Interim assessment (4 module)<br />
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0.17 * 2nd-4th module Home assignments + 0.09 * FinalExam (June Exam) + 0.16 * Interim assessment (1 module) + 0.12 * SpringMock (Spring Midterm) + 0.3 * University of London exams (May Exam) + 0.16 * WinterExam (December Exam)<br />
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All marks are out of 100 points.<br />
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== Rules ==<br />
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*Homework submitted after the general deadline will not be accepted. <br />
*The common mistakes made in the homework will be discussed during the seminars. <br />
*Any fact of cheating or breach of academic integrity will result in receiving a "0" (zero) for this work.</div>
imported>Axyniia