AP Stat Study Guide Detailed Questions And
Expert Answers
Difference between Population and Sample - ANS Both can be measured by a
census.
Population is a group of the individuals you want information about.
Sample is a subset of individuals in the population that you actually collect data
from.
What do Samples allow you to do? - ANS Unlike Populations, the allow you to draw
conclusions about whole populations based on the sample.
Bias - ANS Anything that causes a sample to be not representative of the
population of interest.
- Need to articulate what bias is, why it should be considered bias, and how it
distorts results from what they might otherwise be.
Difference between Sampling Error and Sampling Bias - ANS Sampling Error is ____
, however Sampling Bias is using a method that favors some outcomes over
another.
How does a small sampling size affect the validity of the sample? - ANS A smaller
sampling size negatively affects the validity of the sample because the sampling
error increases.
,Types of Sampling Bias - ANS - Under-coverage Bais
- Non-response Bias
- Voluntary Response Bias
Under-coverage Bias - ANS Occurs when some members of the population are
inadequately represented in the sample.
- Often a problem in convenience samples
Non-response Bias - ANS Occurs when there is failure to obtain a measurement on
one or more study variables for one or more elements K selected for the survey.
Basically when someone does not answer the question.
- A form of non-observation present in most surveys
Voluntary Response Bias - ANS Occurs when sample members are self-selected
volunteers, as in voluntary samples.
- In survey sampling - voluntary
Types of Response Bias - ANS - Loaded Questions
- False Answers (Response Bias)
Sampling Bias - ANS A bias introduced by who was included in the sample.
, Response Bias - ANS A bias from what the sample says/ responds. The results.
Loaded Questions - ANS It is a trick question which presupposes an unverified
assumption that the person being questioned is likely to disagree or agree with.
Ex. "Why are you being so lazy".
- It presupposes that the person being questioned is lazy
False Answers - ANS Positive and Negative
Type 1 error - Positive, when you incorrectly reject the null hypothesis
- Leads you to believe that your hypothesis is true, when it really isn't
Type 2 error - Negative, opposite of positive
Simply - Then the response is intentionally provided to throw the results
unfavorably.
Simple Random Sample (SRS) - ANS A subset of individuals (sample) chosen from a
larger set (a population) where each individual is chosen randomly and entirely by
chance, such that each individuals have the same probability of being chosen for
the sample at any point.
Systematic Random Sample - ANS A method involving the selection of elements
from an ordered sampling frame
Ex. Equi-probability method, progression through a list is treated circularly, so the
last goes to the begging of the list when the end is passed in the list
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