Mind map
Conditions
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Conditions
one-sample mean
- normal sampling distribution
- SRS with replacement
- Known sigma SD
- SRS with replacement
- normal sampling distribution
one-sample proportion
- binomial
- SRS with replacement
- normal
- np-hat >= 15, nq-hat >=15
- normal
- SRS with replacement
- binomial
two-sample paired sample means
- BOTH samples distributions are normal
- makes the difference sampling distribution normal
- BOTH samples were SRS w replacement
- BOTH samples distributions are normal
independent two-sample means
- both samples SRS w replacement
- both normal sampling distributions
- pops both normal or both samples CLT
- df=min(n1-1, n2-1)
- pops both normal or both samples CLT
- both normal sampling distributions
- both samples SRS w replacement
two-sample proportions
- Independent
- both sampling distributions are NORMAL
- both samples are SRS w replacement
- >= 5 failures AND >= successes
- both sampling distributions are NORMAL
- Independent
multiple means
- All samples are independent
- ALL samples were taken via SRS or Randomized Design
- Population distribution are approx. Normal
- Constant variance across populations
- df=K-1, N-K
- scatterplot or residual plot (same as constant variance of Y across X of regreesion condition
- or strip chart
- QQ plot of residuals
- Constant variance across populations
- Population distribution are approx. Normal
- ALL samples were taken via SRS or Randomized Design
- All samples are independent
regression
- Y observations are independent
- Linear relationship between Y and X
- Y follows a Normal distribution for EACH x
- Constant variance of Y across X
- scatterplot show equal points randomly spread above and below horizontal (residual)
- random 'scatter' or band of residuals (i.e. the same 'good' residual plot will meet both the linearity assumption and the constant variance assumption).
- df=n-2
- scatterplot show equal points randomly spread above and below horizontal (residual)
- QQ plot of residuals
- Constant variance of Y across X
- look if least squares regression line is good predictor , Scatterplot or residual plot
- Y follows a Normal distribution for EACH x
- SRS with replacement, one y doesn't affect another
- Linear relationship between Y and X
- Y observations are independent
binomial
- 2 outcomes
- Independent trials
- fixed number of trials
- fixed probability of success
- SRS with replacement ensures
- fixed probability of success
- fixed number of trials
- Independent trials
- 2 outcomes
sampling distribution
- Normal population
- sample >=50 (CLT)
Z confidence intervals
- SRS with replacement
- normal sampling distribution
- known sigma SD
- normal sampling distribution
- SRS with replacement
t confidence intervals
- SRS with replacement
- normal sampling distribution
- df=n-1
- normal sampling distribution
- SRS with replacement
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- Mind Map on Conditions, created by d t on 13/04/2018.
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- d t
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