Features of Normal distribution (how the graph looks, type of data)
What adds to 1 in Normal distribution
In normal distribution, area under the graph = 1
Normal distribution: p(x=n) ?
For continuous values, p(x=n)=0, because the value would be infinitesimally small
Normal distribution: Where are the points of inflection on the graph?
Points of inflection = μ ± σ (mean ± one standard deviation)
Normal distribution: How much data is within 1, 2, and 3 standard deviations of the mean? (percentage rule)
1σ = 68%
2σ = 95%
3σ = 99.7%
The normal distribution model format
X ~ N ( μ, σ² )
where μ = mean
and σ = standard deviation
What is the standard normal distribution model?
Z ~ N (0 , 1²)
What is the coding formula for standard normal distribution?
Z = (X - μ) / σ
where Z is number of standard deviations from mean (the value gained from the standard normal model [Z ~ N (0 , 1²)]
μ is the mean
σ is th standard deviation
X is the variable that we want to find the Z value of
What is a Z value in standard normal distribution?
Using phi (Φ) to represent standard normal probabilities
Φ (a) = p (Z < a)
Normal distribution: How to find μ and σ when given probabilities are given
What are the conditions that allow binomial distributions to be approximated as normal distributions?
Approximating binomial distributions as normal distributions: how to find mean (μ) and standard deviation (σ)
X~B (n, p) —-> Y~N (μ, σ²)
μ = n x p n=trials p=probability
σ² = np(1-p)
Approximating binomial distributions as normal distributions: continuity corrections
ex. p(x>5) = p(x≥6) = p(x≥5.5)
What is the p value for a two tailed hypothesis test?
2 x probability found