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Formulas: science and society, grade 12 (3 units)

A quadratic model

  • A quadratic model – a<0\displaystyle a<0: it has a highest point, a>0\displaystyle a>0: a lowest point
    y=ax2+bx+c\displaystyle y=ax^{2}+bx+ca≠0\displaystyle a\neq0
  • The vertex’s x\displaystyle x – the axis of symmetry
    x=−b2a\displaystyle x=-\frac{b}{2a}
  • The vertex’s x\displaystyle x – midway between two values of x\displaystyle x with the same y\displaystyle y
    x=x1+x22\displaystyle x=\frac{x_1+x_2}{2}
  • The quadratic formula for ax2+bx+c=0\displaystyle {ax^{2}+bx+c}={0} – the zeros
    x1,2=−b±b2−4ac2a\displaystyle x_{1,2}=\frac{-b\pm\sqrt{b^{2}-4ac}}{2a}

Other models

  • A linear relation – the differences in the table are equal
    y=mx+b\displaystyle y=mx+b
  • An exponential relation – the ratio of two neighbouring values in the table is fixed, b\displaystyle b
    y=a⋅bx\displaystyle y=a\cdot b^{x}

The normal distribution

  • The standard deviation of n\displaystyle n data – xˉ\displaystyle \bar{x} their mean
    σ=(x1−xˉ)2+(x2−xˉ)2+⋯+(xn−xˉ)2n\displaystyle \sigma=\sqrt{\frac{(x_1-\bar{x})^{2}+(x_2-\bar{x})^{2}+\dots+(x_n-\bar{x})^{2}}{n}}
  • In a normal distribution – μ\displaystyle \mu the mean, σ\displaystyle \sigma the standard deviation: about 68% of the data within one standard deviation of the mean (34% on each side)
    P(μ−σ<x<μ+σ)≈68%\displaystyle P(\mu-\sigma<x<\mu+\sigma)\approx68\%
  • About 95% within two standard deviations of the mean (another 13.5% on each side)
    P(μ−2σ<x<μ+2σ)≈95%\displaystyle P(\mu-2\sigma<x<\mu+2\sigma)\approx95\%
  • About 2.5% above μ+2σ\displaystyle \mu+2\sigma, and about 2.5% below μ−2σ\displaystyle \mu-2\sigma
    P(x>μ+2σ)≈2.5%\displaystyle P(x>\mu+2\sigma)\approx2.5\%
  • How many of n\displaystyle n data are p\displaystyle p percent of them
    n⋅p%\displaystyle n\cdot p\%

The standard score

  • The standard score of the value x\displaystyle x – how many standard deviations it is above the mean (or below it, when z<0\displaystyle z<0)
    z=x−μσ\displaystyle z=\frac{x-\mu}{\sigma}
  • The value whose standard score is z\displaystyle z
    x=μ+z⋅σ\displaystyle x=\mu+z\cdot\sigma