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Textbook Notes for Luckny Zephyr

LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 3: Cumulative Frequency Analysis, Unimodality, Histogram

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7 Mar 2019
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 13: Bias Of An Estimator, Consistent Estimator, Confidence Interval

Cassandra Cowan5 Page
7 Mar 2019
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Chapter 13: inference about comparing two populations 5:42. Difference between two means: in order to test and estimate the difference between two popu
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 8: Random Variable, Standard Deviation, Continuous Or Discrete Variable

Cassandra Cowan4 Page
7 Mar 2019
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P(x=5), say: in a continuous setting (e. g. with time as a random variable), the probability the random variable of interest, say task length, takes ex
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 10: Bias Of An Estimator, Statistical Parameter, Point Estimation

Cassandra Cowan3 Page
7 Mar 2019
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 2: Level Of Measurement, Descriptive Statistics, Frequency Distribution

Cassandra Cowan2 Page
7 Mar 2019
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Introduction & re-cap : descriptive statistics involves arranging, summarizing, and presenting a set of data in such a way that useful information is p
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 1: Statistical Inference, Descriptive Statistics, Standard Deviation

Cassandra Cowan2 Page
7 Mar 2019
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 7: Probability Distribution, Random Variable, Coin Flipping

Cassandra Cowan4 Page
7 Mar 2019
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30. 10000000001 minutes?: analogy: integers are discrete, while real numbers are continuous. Probability notation: an upper-case letter will represent
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 6: Mutual Exclusivity, Frequency (Statistics), Conditional Probability

Cassandra Cowan3 Page
7 Mar 2019
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If an experiment has n possible outcomes, this method would assign a probability of 1/n to each outcome. It is necessary to determine the number of pos
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 11: Beta, Alpha, Type I And Type Ii Errors

Cassandra Cowan4 Page
7 Mar 2019
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 16: Simple Linear Regression, Regression Analysis, Linear Regression

Cassandra Cowan5 Page
7 Mar 2019
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It is the difference between the actual relationship and the estimated relationship: both beta values are population parameters which are usually unkno
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 12: Standard Error, Confidence Interval, Exponential Distribution

Cassandra Cowan3 Page
7 Mar 2019
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LAURENTIANSTAT-2066ELLuckny ZephyrFall

STAT-2066EL Chapter Notes - Chapter 4: Squared Deviations From The Mean, Quartile, Standard Deviation

Cassandra Cowan5 Page
7 Mar 2019
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