Intro

• Concepts in lecture, formulae in lab
• Plenty of vocabulary: pay attention, take notes
• Berkeley Glossary
• See Wikipedia Glossary as well

Motivation: Educational Migration and Remittance

Data: countryStudy, countryOrig, yearsStudy, remittance

• Describe the amount remitted by educational migrants
• Is the choice to remit independent of the country studied in?
• Do the total years spent studying in a country correlate with remittance?
• Further ramifications require theoretical understanding!

Initial Concepts

• Population, census, sample (size)
• Estimation
• Representative, weighting
• Data types: numerical, categorical
• Sources of data (GIGO)

Descriptive Statistics

• Again: population vs. sample
• probability, odds

Univariate

• Distribution, skew
• Central Tendency: Mean, median, mode
• Dispersion: Variance, standard deviation

Multivariate

• Response, Explanatory Variables
• Conditioning

Graphics

See also R Graph Gallery

Numerical

Histogram

Numerical-Numerical

Scatter plot

Numerical-Categorical

Barplot

Pie chart

Table of Counts

	Denmark	New Zealand
No Remit	67	120
Remit	133	80

Inferential Statistics

• Bias, assumptions
• Correlation (vs. causation)

> cor(yearsStudy, remittance)
[1] 0.2038152

• Hypothesis testing H₀, H₁
• p-value, critical value α
• Confidence Interval, significance

> confint(estRemittanceMean)
               2.5 %   97.5 %
(Intercept) 2435.021 3076.689

• χ² test

> chisq.test(remit, countryStudy)
        Pearson's Chi-squared test with Yates' continuity correction

data:  remit and countryStudy
X-squared = 27.155, df = 1, p-value = 1.878e-07