Lessons 1-4 Quiz Review: Terminology Flashcards

1
Q

Numerical (Quantitative) Data

A

Data in the form of a number; numerical data are either continuous or discrete

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2
Q

Continuous Data

A

Can have any value within a range

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3
Q

Continuous Data can include what

A

Homework time (time in general), height, weight

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4
Q

Discrete Data

A

Can only have specific values, usually whole numbers.

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5
Q

Continuous Data Graph Type

A

Histogram (Intervals-Bars Touch)

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6
Q

Discrete Data can include what

A

Tickets sold, # of teaspoons, AP scores, shoe size

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7
Q

Discrete Data Graph Type

A

Bar Graph

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8
Q

Categorical (Qualitative) data

A

Data that can be sorted into distinct groups or categories;
Categorical data can be either ordinal or nominal

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9
Q

Ordinal Data

A

Qualitative data that can be ranked (ordered)

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10
Q

Ordinal Data can include what

A

Level of agreement (good, fair, poor)

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11
Q

Ordinal Data Graph Type

A

Bar Graph (easier to see order)

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12
Q

Nominal Data

A

Cannot be ranked

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13
Q

Nominal Data can include what

A

Favourite sport, favourite snack, etc…

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14
Q

Nominal Data Graph Type

A

Bar graph, circle graph (pie chart)

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15
Q

Census Sample

A

Survey the entire population

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16
Q

Census Example

A

Lucy surveys all community members (students and staff)

17
Q

Simple Random

A

Randomly choose a specific number of people

18
Q

Simple Random Example

A

Lucy randomly selects 100 people to survey (for example, puts all names into a hat; assigns each member of the population a number and use a
random number generator.

19
Q

Systematic

A

Put the population in an ordered list and choose people at regular intervals; Start with a random selection.

20
Q

Systematic Example

A

Lucy surveys every 6th person from a list of
community members after choosing a
random starting point; Note: We survey every 6th person because 100/600 = 1/6 of the population

21
Q

Stratified

A

Divide the sample into groups with the same proportions as those groups in the population.

22
Q

Stratified Example

A

Lucy randomly chooses one sixth of each
division:
● 1/6 x 215 = 36 students from Junior School
● 1/6 x 130 = 22 students from Middle School
● 1/6 x 175 = 29 students from Senior School
● 1/6 x 80 = 13 staff members

23
Q

Cluster

A

Divide the population into groups,
randomly choose a number of the
groups, and sample each member of
the chosen groups

24
Q

Cluster Example

A
  1. Lucy divides the school into grade and
    staff groups and randomly chooses
    about 5-6 groups to survey
    (depending on the group size).
  2. She then surveys all members of each
    chosen group.
25
Q

Multistage

A

Divide the population into a hierarchy
and choose a random sample at each
level
- Similar to stratified sample,
but proportions aren’t
necessarily maintained

26
Q

Multistage Example

A
  1. Lucy randomly chooses two divisions
    from JS, MS, SS, and staff.
  2. From the selected divisions, she
    randomly selects two subgroups
    within.
  3. She then surveys 25 members of each
    subgroup chosen in Step 2.
27
Q

Convenience

A

Choose individuals from the
population who are easy to access

28
Q

Convenience Example

A

Lucy surveys 100 people as they enter the
dining hall to collect their lunch.

29
Q

Voluntary

A

Allow participants to choose whether
or not to participate

30
Q

Voluntary Example

A

Lucy creates a Google Form and sends her
survey questions to the school community via
email. Some community members choose to
complete the form.

31
Q

Response Bias

A

When respondents change
their answers to influence the results, to
avoid embarrassment, or to give the answer
they think the questioner wants

32
Q

Response Bias Example

A

Mrs. Warner asks students who are enjoying
data management to raise their hand.

33
Q

Sampling Bias

A

When the sample does not
closely represent the population

34
Q

Sampling Bias Example

A

You ask your friends a question when you
need the opinion of the whole school.

35
Q

Measurement Bias

A

when the collection
method is such that the characteristics are
consistently over- or under-represented

36
Q

Measurement Bias Example

A

Leading questions, offering limited choices,
etc.

37
Q

Non-response Bias

A

When the opinions of
respondents differ in meaningful ways from
those of non-respondents (common with voluntary surveys)

38
Q

Non-response Bias Example

A

A sports survey sent to the whole school may
get the majority of responses from athletes.