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AP Statistics > Unit 1: Exploring One-Variable Data > Flashcards

Unit 1: Exploring One-Variable Data Flashcards

1
Q

Statistics

A

The science of reasoning from data (Dealing with Data)

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2
Q

Population

A

The entire group of people/things that you want to investigate.

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3
Q

Sample

A

Smaller portion of the population that you want to gather information about

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4
Q

Data

A

Actual values of the variables you find from sampling (Ex. the number of people who like certain sports the best)

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5
Q

Parameter

A

Data about a population (numerical characteristic)

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6
Q

Statistic

A

Data about a sample (numerical characteristic)

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7
Q

Variable

A

Element, feature, or factor that’s liable to vary or change

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8
Q

Convenience Sampling

A

A type of sampling that is NOT random and involves using a population that is READILY AVAILABLE

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9
Q

Quota Sampling

A

Using a sample that is selected to match the population with respect to some specific characteristic(s)

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10
Q

Cluster Sampling

A

Dividing the population into groups, then randomly selecting some of the groups

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11
Q

Systematic Sampling

A

Randomly selecting a starting point in a list of names and taking every nth piece of data from a listing of the population (a special subset of cluster samples)

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12
Q

Stratified Sampling

A

Dividing the population into groups, and then taking your sample from a proportionate number from each group

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13
Q

Observational Units

A

The person or thing to which the number or category is assigned

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14
Q

Datum

A

One piece of data

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15
Q

Variability

A

The phenomenon of a variable taking on different values or categories from observational unit to observational unit

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16
Q

Quantitative Variable

A

Measures a numerical characteristic such as height

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17
Q

Categorical Variable

A

Records a group designation such as gender

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18
Q

Binary Variables

A

Categorical variables with only two possible categories, for example, male and female

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19
Q

Bar Graph

A

Displays the distribution of a categorical variable

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20
Q

Distribution

A

The distribution of a variable refers to its pattern of variation. With a categorical variable, distribution means the variable’s possible categories and the proportion of responses in each.

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21
Q

Statistical Tendency

A

Refers to observational units in one group being more likely to a certain category or to have higher values than those in another group

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22
Q

Consistency

A

Refers to how variable, or how spread out, the values in a dataset are for a quantitative variable

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23
Q

Representative

A

If the sample is selected carefully, it is has similar characteristics of the population

24
Q

Sample Size

A

The number of observational units studied in a sample

25
Q

Sampling Bias

A

If a sampling procedure tends systematically to over-represent certain segments of the population and underrepresent others

26
Q

Voluntary Response Variables

A

Refers to samples collected in such a way that members of the population decide for themselves whether or not to participate in the study

27
Q

Nonresponse Variables

A

When people do not reply to the survey

28
Q

Sampling Frame

A

The list used to decide the subjects

29
Q

Explanatory Variable

A

The variable whose effect you want to study; X value, input

30
Q

Response Variable

A

The variable that you suspect is affected by the other variable; Y value, Output

31
Q

Observational Study

A

Establishes an association or relationship between the explanatory and response variables, but you cannot draw a cause-and-effect conclusion between the explanatory and response variables

32
Q

Lurking Variables

A

Variables that are unaccounted for that could affect the response variable

33
Q

Confounding Variable

A

Lurking variable whose effects on the response variable are indistinguishable from the effects of the explanatory variable

34
Q

Ordinal Data

A

Numbers which are categorical

35
Q

Categorical Graphs

A

Bar graph, segmented bar graph, and pie chart

36
Q

Extrapolating

A

Making a guess based on data outside of your data set

37
Q

Shape

A

Normal(bell), skewed left/right, variability (uniform)

38
Q

Center

A

Mean(normal), median(skewed), mode

39
Q

Spread

A

Range, IQR (75-25), standard deviation

40
Q

Causal

A

Only 1 variable changes

41
Q

Casual

A

Association

42
Q

Prospective & Retrospective

A

2 types of observational studies

43
Q

Prospective Study

A

Have an idea, but haven’t recorded it yet

44
Q

Retrospective Study

A

Data has already been collected

45
Q

Simple Random Sampling (SRS)

A

Give every member of the population the same chance of being selected for the sample. It must ensure that every possible sample has an equal chance of being the sample ultimately selected

46
Q

Table of Random Digits

A

Table is constructed so that each position is equally likely to be occupies by any one of the digits, and so that the value in any one position has no impact on the value in any other position

47
Q

Unbiased

A

If the values of the statistic from different random samples are centered at the actual parameter value

48
Q

Sampling Variability

A

Refers to the fact that the values of sample statistics vary from sample to sample

49
Q

Precision

A

Refers to how much the values vary from sample to sample.

(Precision is related to sample size: sample statistics from larger samples are more precise and closer together than those from smaller samples. Statistics from larger random samples, therefore, provide a more accurate estimate of the corresponding population parameter.)

50
Q

Anecdotal Evidence

A

Refers to situations that come to mind easily and are of little value in scientific research.

51
Q

Third Quartile

A

The median of the stat values that are to the right of the median in the ordered list

52
Q

Quartiles

A

The quartiles divide the ordered data set into four groups having roughly the same number of values. Arrange data from smallest to largest to find it

53
Q

First Quartile

A

The median of the stat values that are to the left of the median in the ordered list

54
Q

Resistant

A

A statistical measure is a resistant if it isn’t sensitive to extreme values

55
Q

Discrete Variable

A

A quantitative variable that takes a fixed set of possible values with gaps between them

56
Q

Continuous Variable

A

A quantitative variable that can take any value in an interval on the number line

AP Statistics (1 decks)

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