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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture Notes - Lecture 32: Null Hypothesis, Alternative Hypothesis, Jargon

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5 Nov 2018
0
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture Notes - Lecture 29: Shoe Size, Percentile Rank

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26 Oct 2018
0
Predicted tan length in sd for someone one sd above average for x. There is still a regression line for non-linear regressions, but it is not a good pr
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture 33: Stats 20 11-7-18

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7 Nov 2018
0
Hypothesis test: null hypothesis, alternative hypothesis, test statistic, p-value, conclusion. P > 5: cannot reject the null hypothesis, this looks lik
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture Notes - Lecture 10: Mutual Exclusivity

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10 Sep 2018
0
)(p)^k(1-p)^n-k is the binomial formula which is the same thing as (n/k) on calculator. N!= possible sequences. k=number of successes. p= probability o
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture Notes - Lecture 8: Mutual Exclusivity, Fair Coin

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7 Sep 2018
0
P(a or b) = p(a) + p(b) - p(a and b) P(a or b)= p(a) + p(b) - p(a and b) Two events are mutually exclusive if they can"t both happen. If a and b are mu
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture 26: stats 20 10-19-18 Regression Basics

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19 Oct 2018
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture Notes - Lecture 45: Null Hypothesis

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3 Dec 2018
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It is a built in flaw of using a p-value, it is wrong precisely 5% of the time when using the 5% threshold. Suppose 100 researcher each do an experimen
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture Notes - Lecture 23: Simple Random Sample, Sample Size Determination

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12 Oct 2018
0
It will cover everything from the midterm until monday except for confidence intervals. Se w/out replacement= se w/replacement x correction factor (c.
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture Notes - Lecture 42: Null Hypothesis, Statistical Hypothesis Testing

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27 Nov 2018
0
Quiz on wednesday based on chapter 26 and r simulation code similar to that of the hw. We will have makeup classes for the classes that were cancelled
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture Notes - Lecture 30: Fallacy

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29 Oct 2018
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Regression fallacy is the mistaken belief that there must be some other explanation for the phenomenon of the regression effect. An example of this is
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture 28: stats 20 10-24-18

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24 Oct 2018
0
Different kinds of scatter plots: others are points that are fat away from most of the data. Outliers need to be considered as long as they are feasibl
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BERKELEYSTAT 20Fletcher IbserFall

STAT 20 Lecture Notes - Lecture 27: Space Shuttle Challenger Disaster, Scatter Plot

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22 Oct 2018
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