1 - Intro

1 - Intro#

Types of regression:

  1. Single Linear Regression (SLR)

  2. Multiple Linear Regression (MLR)

  3. Logistic Regression

SLR and MLR have continuous response, but logistic regression has a binary (yes/no) response.

Statistics is the the art and science concerned with developing and studying methods for collecting, analyzing, interpreting, and presenting empirical data.

  • It is a discipline of learning from data and turning it into usable insights.

  • Two fundamental ideas in the field are uncertainty and variability.

Data#

  1. Collection - Random samples, statistical significance

  2. Exploration

  3. Model

  4. Decision-making - Draw insights from data (e.g., How does class size affect retention rate?, How does the unemployment rate affect the GDP growth rate?)

Statistical Analysis#

  1. Estimation (e.g., Quality of schools in area, Average price of housing in area)

  2. Association (e.g., Relationship between quality of schools and housing prices in area)

  3. Prediction (e.g., What affect will a school closure have on housing prices in the area?)

Types of Statistics#

  • Descriptive statistics (summary statistics)

    • Graphical summary

    • Numerical summary

      • Center: mean, median

      • Variability: variance, standard deviation

      • Relative standing: quartiles, percentiles

  • Inferential statistics (statistical inference): Infer population from sample

    • Confidence interval \((\bar X - t_{\alpha/2, n-1} \frac{s}{n}, \bar X + t_{\alpha/2, n-1} \frac{s}{n})\)

    • Hypothesis test

      • p-value

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