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Class Notes for Statistics at University of Manitoba

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STAT 1000 Lecture Notes - Lecture 22: Fair Coin, Sample Space, Probability Theory
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Lecture 22 - STAT 100 (1/11/2017) Probability Roll a die, toss a coin, or buy a lottery ticket with your lucky numbers. The outcome cannot be predicted ahead of time, but can nevertheless be described by ...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 34: Null Hypothesis, Confidence Interval, Standard Deviation
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Lecture 34 - STAT 1000 (1/12/2017) Testing of Hypothesis: 1. P-Value method a. If p-value = 0, reject Ho at = 0 2. Confidence Interval method: a. Requirement: i. ...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 28: Sampling Distribution, Random Variable, Central Limit Theorem
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Lecture 28 - STAT 1000 (17/11/2017) Example 1: STAT1000 - Basic Statistical Analysis I lecture notes Z = 0.44 from Table A ...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 27: Bias Of An Estimator, Simple Random Sample, Variance
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Lecture 27 - STAT 1000 (15/11/2017) Unit 7- Sampling Distribution Suppose that, rather being interested in probability calculations for some variable on a single individual, we are instead interested in t...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 35: Test Statistic, Dependent And Independent Variables, Twin Study
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Lecture 35 - STAT 1000 (4/12/2017) Example - Fast Food: A fast food restaurant claims that the average waiting time in their drive through is less than a minute. We record the drive thru waiting times for a...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 29: Random Variable, Standard Deviation, Central Limit Theorem
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Lecture 29 - STAT 1000 (20/11/2017) Example 1: Even though we dont know the form of the distribution of diameters, since the sample size is high, we know that the distribution of X is approximately n...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 26: Random Variable, Standard Deviation, Binomial Coefficient
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Lecture 26 - STAT 1000 (10/11/2017) Example 1 : The observations are fixed . . . there are 50. Whether or not one person has a boy does not influence what another person will have . . . i...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 33: Confidence Interval, Null Hypothesis
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Lecture 33 - STAT 1000 (29/11/2017) Example- Sonnets: x z = ...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 23: Sample Space, Venn Diagram, Empty Set
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Lecture 23 - STAT 100 (3/11/2017) Intersection Example : We can see that there are only two events that are in both A and B. S = {11, 12, 13, 14, 15, 16, 21, 22, 23, 24, 25, 26, 31, 32, 33, 34, 35, 36, 41,...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 30: Central Limit Theorem, Statistical Parameter, Binomial Distribution
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Lecture 30 - STAT 1000 (22/11/2017) According to the Manitoba Agriculture Website, 17% of the total number of farms in Manitoba are vegetable farms. In a SRS of 30 farms, what is the probability tha...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 31: Confidence Interval
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Lecture 31 - STAT 1000 (24/11/2017) Confidence Intervals What if we can set up an interval? How confident will be that the true population mean , , falls in the interval ? Recall the : I...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 32: Standard Deviation, Null Hypothesis, Confidence Interval
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Lecture 32 - STAT 1000 (27/11/2017) Sample Size Determination Note that the length of a confidence interval depends on the sample size,but not the population size! For a given sample size, our ...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 24: Sample Space
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Lecture 24 - STAT 1000 (6/11/2017) Independent Independent : observing the outcome of the first in no way alters the probability structure of the second. For example, the outcome of the roll of the fir...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture Notes - Lecture 25: Normal Distribution, Sample Space, Random Variable
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Lecture 25 - STAT 1000 (8/11/2017) Notice that the probability of each outcome is between 0 and 1. Also note that P(O) + P(A) + P(B) + P(AB) = 0.48 + 0.23 + 0.19 + 0.10 = 1 The pro...

Statistics
STAT 1000
Mohammad Nadimi
STAT 1000 Lecture 1: Lecture 1 - STAT 1000
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Statistics
STAT 1000
Mohammad Nadimi
Statistics - Reference Guides

This Guide provides an easy to follow summary of all basic principles that are the foundation to Statistics and Probabilities. Using a combination of charts and sample equations, the key concepts are developed and the esse...

Econometrics
ETC2430
All Professors

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