No
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Main
subject |
More
description
(And videos on extra mathematical details beyond the basic
curriculum - Spring 2012)
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English
Lecture (from Spring 2010)
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1
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Introduction
Simple graphical methods |
What is statistics?
Why this course?
EXTRA MATH:
The derivation of the variance formula(7 minutes)
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48
minutes
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Software: R.
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How to get started?
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9 minutes
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2
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Discrete distributions
Binomial- and Poisson distr. |
Some basic probability
for systems
with categorical outcomes
EXTRA MATH:
The mean of a binomial distribution.(6 minutes)
EXTRA MATH:
The derivation of the variance formula(3 minutes)
EXTRA MATH:
The Variance of the binomial distribution(7 minutes)
EXTRA MATH:
The derivation of the poisson distribution (11 minutes)
EXTRA MATH:
The mean and variance of the Poisson distribution(6 minutes)
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61
minutes
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3
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Continuous distributions
The normal distribution
Uniform and log-normal distributions |
Some basic probability for systems
with quantitative continous outcomes
EXTRA MATH:
Mean and variance for the Uniform distribution (4.5 minutes)
EXTRA MATH:
Mean and variance for the Normal distribution (8 minutes)
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73
minutes
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4
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The exponential
distribution
E(aX+b) and Var(aX+b)
Normal plot
Transformations |
Some more basic
probability for systems
with quantitative continous outcomes
EXTRA MATH:
Mean and variance for the Exponantial distribution (6 minutes)
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59
minutes
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5
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Inference concerning the
mean
Random Samples
Sampling distributions
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Learning statistical
thinking related to
the intelligent use of a computed average.
Confidence interval for a mean.
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Part 1,
44 minutes
Part 2,
34 minutes
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6
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Test of hypothesis
Hypothesis concerning one mean |
Learn the basic concepts
of hypothesis testing
EXTRA MATH:
Introduction to likelihood theory (14 minutes)
EXTRA MATH:
Maximum likelihood estimation for the binomial model (6 minutes)
EXTRA MATH:
Maximum likelihood estimation for the poisson model (3.5 minutes)
EXTRA MATH:
Maximum likelihood estimation for the normal model (10 minutes)
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68
minutes |
7
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Tests and confidence
intervals
OC-curves
Inference concerning two means
Randomization and pairing |
Compare two means using
confidence bands and
hypothesis testing.
Paired and independent samples t-test.
EXTRA MATH:
Power and sample size formula (one sample case) (14 minutes)
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75
minutes
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8
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Inferences concerning
variances
Sampling distributions |
(Resume of lecture 5-6-7)
Quantifying the
uncertainty of a computed variance.
Comparing two variances.
EXTRA MATH:
Sums of random variables and moment generating functions(14 minutes)
EXTRA MATH:
Non-linear transformations of distributions (18 minutes)
EXTRA MATH:
Sampling distribution of the sample variance (11 minutes)
EXTRA MATH:
Derivation of the t-distribution (15 minutes)
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73
minutes
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9
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Inference for proportions
Chi-square tests
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Uncertainty and testing of one or more
proportions.
2x2 frequency tables
rxc frequency tables
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86
minutes
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10
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Statistics by simulation
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Simulation intro
(example: A=XY)(25 minutes)
Non-linear
error propagation (15 minutes)
Bootstrap
confidence limits, one-sample (21 minutes)
Bootstrap
confidence limits, two-sample (8 minutes)
Hypothesis
testing by simulation (permutation test)(17 minutes)
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11
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Regression analysis
Inferences based on LS
Correlation
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Learning statistical thinking related to the relation
between two sets of measurements
EXTRA MATH:
The basic handcomputational formulae (3 minutes)
EXTRA MATH:
Finding the least squares estimates(10 minutes)
EXTRA MATH:
The LS estimates are also Maximum Likelihood Estimates (5 minutes)
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84
minutes
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12
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Analysis of variance |
Comparing the means of several groups.
Randomized and randomized block experiments
EXTRA MATH:
Why is the F-statistic F-distributed? (8 minutes)
EXTRA MATH:
Parameter solutions in ANOVA models(12 minutes)
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86
minutes
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13
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Summary
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A summary of the entire course
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63
minutes |