Chapter 6: Generalizations

Question 1

Generalizations

Answer 1

based on fleeting experiences, impressions or anecdotes.

Often have weak evidence, but can be difficult to eject from our assortment of beliefs.

Question 2

Statistical Inference

Answer 2

inferences about a population based on a sample of data

Question 3

Statistical generalization

Answer 3

an inference made about a population based on features of a sample

moves outward from facts about a group to draw conclusion about the group at large

Question 4

Statistical Instantiation

Answer 4

an inference made about a sample based on features of a population

moved inward from a fact about the larger group to draw a conclusion about a sample

Question 5

Convenience Sample

Answer 5

a set of observations that is small and carelessly selected

Question 6

Sampling Bias

Answer 6

a selection effect in a sample created by the way in which we are sampling the population

Question 7

Sample Size Matters

Answer 7

Small samples provide insufficient evidence

Appropriate sample size leads to higher strength factor

i.e. probabilities of (E given H) and (E given not-H) are very different

Question 8

The Law of Large Numbers

Answer 8

The larger a sample, the more likely its proportions reflect the population as a whole

Question 9

How Big is Big Enough For a Sample?

Answer 9

Whether a sample is big enough depends on how narrow test’s margin of error needs to be

Question 9

Margin of Error

Answer 9

the size of the confidence on either side of the given value

Question 10

Confidence Interval

Answer 10

the margin in which true population percentage falls, with that degree of confidence

Question 11

Survey Pitfalls

Answer 11

a) participation biases
b) response bias

Language of survey can create these biases

Question 12

Measures of Centrality:

Answer 12

Arithmetic Mean: the average of values

Median: the midpoint on spectrum of collected values

Mode: the most common value

Question 13

Geometric Mean

Answer 13

Helps track changes in proportions of each value

Gives best “central” value

Question 14

Difference Between Arithmetic Mean and Geometric Mean

Answer 14

Arithmetic mean: adding up values and dividing by number of cases

Geometric mean: multiplying values and using number of cases as root

Question 15

Clear and True, But Misleading

Answer 15

Even true generalization can be misleading; they can inaccurately suggest a causal relationship

Question 16

Representativeness Heuristic

Answer 16

Cognitive pitfall that:

a) bypasses statistical relationship between features or groups

and instead

b) tests the strength of our mental association between them

Question 17

Representative (Sampling Method)

Answer 17

a sample that has the same sort of variety as its target population, in respects that might affect the probability of possessing the trait being studies

a representative samples has the right proportions of relevant subgroups

Question 18

Stratifying

Answer 18

ensuring that the proportions of relevant subgroups in your sample match those of the corresponding sub grounds within the population as a whole

The process of dividing members of the population into homogenous subgroups before sampling