Verified Documents at University of California - Berkeley
- Introduction to Probability and Statistics
- University of California - Berkeley
- Verified Notes
Browse the full collection of course materials, past exams, study guides and class notes for STAT 20 - Introduction to Probability and Statistics at University of California - …
PROFESSORS
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Fletcher Ibser
fall
30Shobhana Murali Stoyanov
fall
4Verified Documents for Fletcher Ibser
Class Notes
Taken by our most diligent verified note takers in class covering the entire semester.
STAT 20 Lecture Notes - Lecture 8: Mutual Exclusivity, Fair Coin
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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STAT 20 Lecture Notes - Lecture 10: Mutual Exclusivity
)(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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STAT 20 Lecture Notes - Lecture 11: Descriptive Statistics, Exploratory Data Analysis
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STAT 20 Lecture 12: stats 20 9-14-18
Download and then select the datasets and dplyr packages to use funcitons family=read. csv("~/desktop/family. csv") # get all data on everyone not over
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STAT 20 Lecture Notes - Lecture 13: Cisgender, Vulgate, Exploratory Data Analysis
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STAT 20 Lecture 14: stats 20 9-21-18
This goes along with roger purves in class files. For x=# of heads in 3 coin tosses x. X means random variable x means specific value. = p(x=0) the lon
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STAT 20 Lecture Notes - Lecture 15: Root Mean Square
He is still writing it and there will be more updates. We will have 50 minutes to complete the tes. Throughout lecture, underlined numbers refer to sec
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STAT 20 Lecture 16: stats 20 9-26-18
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STAT 20 Lecture 17: STAT 20 9-28-18 Definitions
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STAT 20 Lecture Notes - Lecture 18: Css Box Model, Writing Implement, Normal Distribution
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STAT 20 Lecture Notes - Lecture 20: Summary Statistics, Observational Error
First lets jump into an overview of concepts in chapters 17,18, 20. Chapter 19, 21 has similar concepts, but different. Statistic = parameter + chance
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STAT 20 Lecture Notes - Lecture 21: Simple Random Sample, Fivethirtyeight, Gerrymandering
Midterm is a good basis of determining where you are in the class. The final will have 2. 5x as many questions, but 3x + time. Fivethirtyeight has a lo
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STAT 20 Lecture 22: stats 20 10-10-18
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STAT 20 Lecture Notes - Lecture 23: Simple Random Sample, Sample Size Determination
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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STAT 20 Lecture Notes - Lecture 24: Confidence Interval
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STAT 20 Lecture Notes - Lecture 25: Statistical Hypothesis Testing
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STAT 20 Lecture 26: stats 20 10-19-18 Regression Basics
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STAT 20 Lecture Notes - Lecture 27: Space Shuttle Challenger Disaster, Scatter Plot
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STAT 20 Lecture 28: stats 20 10-24-18
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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STAT 20 Lecture Notes - Lecture 29: Shoe Size, Percentile Rank
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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STAT 20 Lecture Notes - Lecture 30: Fallacy
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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STAT 20 Lecture Notes - Lecture 31: Homoscedasticity, Scatter Plot, Root Mean Square
Rms error is the rms of prediction errors, volunteer prediction method is used. For example, if method is to always guess the everage, rms error =sdy.
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STAT 20 Lecture Notes - Lecture 32: Null Hypothesis, Alternative Hypothesis, Jargon
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STAT 20 Lecture 34: Stats 20 11-7-18
Hypothesis test: null hypothesis, alternative hypothesis, test statistic, p-value, conclusion. P > 5: cannot reject the null hypothesis, this looks
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STAT 20 Lecture 37: stats 20 11-14-18
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STAT 20 Lecture Notes - Lecture 42: Null Hypothesis, Statistical Hypothesis Testing
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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STAT 20 Lecture Notes - Lecture 43: Botulinum Toxin, Chapter 27, Treatment And Control Groups
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STAT 20 Lecture Notes - Lecture 44: Mexican Peso
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STAT 20 Lecture Notes - Lecture 45: Null Hypothesis
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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STAT 20 Lecture Notes - Lecture 46: Simple Random Sample, Confidence Interval, Continuity Correction
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