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1Cate vs 1 Quantit
data analysis
Question | Answer |
---|---|
useful graphs | comparative boxplot or comparative histogram |
useful numbers | mean and standard deviation for each group |
formula for mean | x ̅=1/N ∑_((i=1))^N▒xi preferable for approximately normal data |
formula for standard deviation | s=√(1/(N-1) ∑_(i=1)^N▒〖(xi-x)〗^2 ) preferable for approximately normal data |
an outlier is | more than 1.5 x IQR lower than Q1 more than 1.5 x IQR higher than Q3 |
linear transformation | transformation of a variable from x to xnew |
examples of linear transformation use | change of units use of normal assumption therefore to find 'z' scores |
formula for linear transformation | xnew=a+bx |
formula for mean after linear transformation | xnew=a+bx |
formula for standard deviation after linear transformation | snew=bs |
density curves | area under the curve in any range of values is the proportion of all observations that fall within that range for a quantitative variable = like a smoothed out histogram describes probabilistic behaviour |
total area under a density curve equals? | 1 |
normality assumption | normal curve can be used if a histogram looks like a normal curve termed 'reasonable' must start at 0 and end at 0 |
normal quantile plot | if in a straight line, or close to it, then normal and assumption is reasonable |
68-95-99.7% rule | 68% of results will be within 1 standard deviation of the mean 95% of results will be within 2 standard deviations of the mean 99.7% of data will be within 3 standard deviations of the mean |
symbol for mean of a density curve | μ |
symbol for the standard deviation of a density curve | σ |
normal distribution short hand | X = random variable N = normal distribution first number in brackets = mean second number in brackets = standard deviation |
standard normal variable | Z corresponds to the area under the curve of the corresponding region will always be to the left |
standard normal distribution table | to find P: Z found along x and y axis to find Z: P found in table ordered from smallest to largest |
reverse standard normal distribution table | P(Z<c) c = right of Z |
X is | N(μ,σ) |
standardising transformation | Z= (X-μ)/σ used when distribution is N(0,1)(is normal but needs proportions changed) |