Jason Cairns

2022-09-13

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

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!

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

- Again: population vs. sample
- probability, odds

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

- Response, Explanatory Variables
- Conditioning

See also R Graph Gallery

Histogram

Scatter plot

Barplot

Pie chart

Denmark | New Zealand | |

No Remit | 67 | 120 |

Remit | 133 | 80 |

- Bias, assumptions
- Correlation (vs. causation)

```
> cor(yearsStudy, remittance)
[1] 0.2038152
```

- Hypothesis testing
*H*_{0},*H*_{1} - p-value, critical value
*α* - Confidence Interval, significance

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

*χ*^{2}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
```