STAT100: Statistics Midterm 2

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1
discreet vs continuous
finite vs infinite quantities, e.g. tails observed in 100 coin flip vs. possible test scores
2
standard normal distribution
normal symmetric distribution model in which the mean is 0 and SD is 1
3
sampling distribution
distribution for all possible values from a sample n
4
central limit theorem
regardless of distribution shape, the sample mean distribution becomes more normal as n increases. generally comparable to population if n > 30
5
population vs sample: mean, standard deviation, proportions
population: μ, σ, p
sample: x̄, s, p^
6
percentages of normal distribution
1 SD: 68% (34%)
2 SD: 95% (13.5%)
3 SD: 99.7% (2.35%)
outside edge: .15%
7
difference between p hat and x bar
p hat is for qualitative variables and x bar is quantitative
8
confidence interval is determined for
proportions (qualitative, p hat) and means (quantitative, x bar)
9
determining a confidence interval for p
90% - 1.645
95% - 1.96
99% - 2.575
critical value x square root (p(1-p)/n) = margin for error, E
10
determining confidence interval for means
n>30 for a known population SD, n>75 for unknown. if not, t critical values must be used
critical value x (standard deviation/square root (n))
11
hypothesis testing options
null: H0, no change
alt.: H1, change
12
statements of hypothesis
either reject the null or fail to reject the null
13
sampling and size restrictions for hypothesis
random sampling + np(1-p) > 10
14
tails of alt hypothesis
p unequal to p - two tailed
p < p - left tailed
p > p - right tailed
15
z test equation
(p hat - p)/ square root of ((p(p-1))/n)
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