Week 1 - What is data Flashcards

1
Q

________ data can be counted, measured, and expressed using numbers.

A

Quantitative

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2
Q

_________ data - is descriptive and conceptual. This data can be categorized based on traits and characteristics.

A

Qualitative

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3
Q

3 major things we can do with statistics:

A

Describe, decide and predict

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4
Q

Average

A

Mean

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5
Q

Centre of dsitribution

A

Median

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6
Q

The value that appears the most

A

Mode

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7
Q

_________ _________ is a term that refers to a central or typical value for a set of data or a probability distribution.

A

Central tendency

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8
Q

Observational design can infer causation TRUE or FALSE

A

False, you typically need experimental but still need to be cautious when inferring causation.

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9
Q

4 ways to measure variables.

A

Nominal , ordinal , interval and ratio scale.

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10
Q

. Each value of the variable represents something different. For
example, we might ask people for their country of birth, and then code those
as numbers: 1 = “Australia,” 2 = “Austria,” 3 = “Azerbaijan” and so on.

A

Nominal scale
A nominal variable satisfies the criterion of identity, such that each value of the variable represents something different, but the numbers simply serve as qualitative labels

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11
Q

. Each value can be ordered in terms of their magnitude. For
example, we might ask a person how good their sleep is, using a 1- 7 numeric
scale. Differences between values are not necessarily equal in magnitude.

A

Ordinal scale
An ordinal variable satisfies the criteria of identity and magnitude, such that the values can be ordered in terms of their magnitude. For example, we might ask a person with chronic pain to complete a form every day assessing how bad their pain is, using a 1-7 numeric scale.

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12
Q

. An _____scale has all of the features of an ordinal scale, but
in addition, the intervals between units on the measurement scale can be
treated as equal. The scale can also take on negative values. A standard
example is physical temperature measured in Celsius.

A

Interval
An interval scale has all of the features of an ordinal scale, but in addition the intervals between units on the measurement scale can be treated as equal. A standard example is physical temperature measured in Celsius or Fahrenheit; the physical difference between 10 and 20 degrees is the same as the physical difference between 90 and 100 degrees, but each scale can also take on negative values.

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13
Q

A _____ scale has all the features of an interval scale, with the
difference being that the ratio scale variable has a true zero point. A standard
example is physical height.

A

Ratio
A ratio scale variable has all four of the features: identity, magnitude, equal intervals, and absolute zero. The difference between a ratio scale variable and an interval scale variable is that the ratio scale variable has a true zero point. Examples of ratio scale variables include physical height and weight, along with temperature measured.

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14
Q

Ordinal scale =

A

Identity and magnitude

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15
Q

Interval scale =

A

Identity, magnitude and equal intervals

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16
Q

Ratio scale =

A

Identity, magnitude, equal intervals and absolute zero

17
Q

Features of the variable (4)

A

Identity, magnitude, equal intervals and absolute zero

18
Q

_______ refers to the consistency of our measurements.

A

Reliabilty

19
Q

______ refers to the degree to which we are measuring the construct that we
think we are measuring.

A

Validity

20
Q

Central Tendency = provide an index of the way typical participants respond on a measure - 3 most common measures:

A

Mean = average
Median = centre of distribution
mode = the value that appears most

21
Q

A discrete measurement is one that takes one of a finite set of particular values. These could be qualitative values (for example, different breeds of dogs) or numerical values (for example, how many friends one has on Facebook). Importantly, there is no middle ground between the measurements; it doesn’t make sense to say that one has 33.7 friends.
True or False

A

True

22
Q

A continuous measurement is one that is defined in terms of a real number. It could fall anywhere in a particular range of values, though usually our measurement tools will limit the precision with which we can measure it; for example, a floor scale might measure weight to the nearest kg, even though weight could in theory be measured with much more precision.
True or False

A

True

23
Q

Reliability refers to the consistency of our measurements. One common form of reliability, known as “test-retest reliability”, measures how well the measurements agree if the same measurement is performed twice
True or False

A

True

24
Q

There are many different types of validity that are commonly discussed; what are three of them.

A

Face validity - does the measure make sense
Construct validity - Is the measurement related to other measurements in an appropriate way?
Predictive validity. If our measurements are truly valid, then they should also be predictive of other outcomes.

25
Q

Scales of measurement (4)

A

Identity: Each value of the variable has a unique meaning.
Magnitude: The values of the variable reflect different magnitudes and have an ordered relationship to one another – that is, some values are larger and some are smaller.
Equal intervals: Units along the scale of measurement are equal to one another. This means, for example, that the difference between 1 and 2 would be equal in its magnitude to the difference between 19 and 20.
Absolute zero: The scale has a true meaningful zero point. For example, for many measurements of physical quantities such as height or weight, this is the complete absence of the thing being measured

26
Q

Nominal scale =

A

Identity

27
Q

Binary =
0 v 1
discrete
Would you like cake yes or no

A
28
Q

Integers = whole numbers
Discrete
How many ppl at the birthday party

A
29
Q

Real numbers = how much did the cake weigh
Decimal component
Continuous

A