What are the three types of non-probability samples?
Convenience Sampling
Voluntary Response Sampling
Judgment Sampling
What is the size of a sample with a margin of error of 18%?
+/- 30%
How much data falls within +2 standard deviations in a normal distribution?
47.5%
What are the 5 types of probability samples?
Simple Random Sample (SRS)
Equal Probability Systematic Random Sampling
Stratified Simple Random Sampling
Cluster Sampling
Multistage Simple Random Sampling
What is the Margin of Error for a sample of 532?
+/- 4.3%
How much data falls within +/- 1 standard deviation of the mean in a normal distribution?
68%
True or false: A probability sampling plan entails everyone in a population having a calculated, specified chance of being apart of a sample?
True.
A statistic is to a _________, as a _____________ is to a population.
sample; parameter
The larger the sample, the __________ the prediction of the true population characteristics.
closer
What is the difference between a voluntary sample and a convenience sample?
What is the relationship between margin of error, sample size, and confidence intervals?
The smaller the MoE, the greater the sample size, the smaller the confidence intervals.
True or False: The following is a proper representation of a confidence statement.
"We are 95% confident that between 87% and 16% of all penguins who like ice will vote to make ice the currency of Antarctica. However, it is too close to conclude if the voting would go this way."
False.
What is the difference between a stratified sample and a cluster sample?
A stratified sample uses comparisons between subgroups called, "strata", whereas a cluster simply puts participants into clusters and then compares the clusters to each other.
Slytherin House and Gryffindor House, respectively, have a final House Cup percentage score of 181 and 176, with a margin of error of +/- 5% for each House. Is this a statistical tie?
What is the difference between bias and precision?
Bias – the extent to which a parameter estimate (statistic) is systematically too high or too low in repeated sampling
Precision – the extent to which there is little variability in a parameter estimate (statistic) from sample to sample