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Data Analytics > Methods I > Flashcards

Methods I Flashcards

1
Q

What type of study is the following: Fuel consumption of pizza delivery motorbike

A

Descriptive

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2
Q

What type of study is the following: Vote intention for the next elections

A

Descriptive

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3
Q

What type of study is the following: Sales rate by sex.

A

Correlational

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4
Q

What type of study is the following: Reading comprehension by age.

A

Correlational

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5
Q

What type of study is the following: Test scores improved by new educational program?

A

Causal

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6
Q

What type of study is the following: Ad click rate increased by new interface design.

A

Causal

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7
Q

What is meant with the study type ‘descriptive’?

A

Statistics on that what exists: factual gathered information.

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8
Q

What is meant with the study type ‘Correlational’?

A

Studying the relationship between multiple things.

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9
Q

What is meant with the study type ‘causal’?

A

Determine if one thing causes (an effect on) the other.

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10
Q

What are independent variables (IV)?

A

Variables that are manipulated by the researcher or nature.

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11
Q

What are dependent variables (DV) ?

A

Variables that are presumably affected by the Independent Variables.

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12
Q

In the process chart, how do we classify IV’s?

A

As (un)controllable factors on the process.

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13
Q

In the process chart, how do we classify DV’s?

A

As a response of the factors (IV’s).

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14
Q

What kind of variables are controllable factors?

A

IV’s

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15
Q

What kind of variables are uncontrollable factors?

A

IV’s

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16
Q

What kind of relationship do we expect from numerical vs numerical?

A

positive vs negative

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17
Q

What kind of relationship do we expect from categorial vs categorial?

A

count differences

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18
Q

What kind of relationship do we expect from numerical vs categorial (or vise versa) ?

A

differences across groups

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19
Q

What is sought after with causality (or causation)?

A

When we can say that one aspact causes change in another aspect -> we find the IV and DV respectively.

20
Q

What do require to establish causation (causality) ?

A

Correlation between IV and DV, The change in IV happens before the change in DV, No other explaination possible.

21
Q

Does correlation mean there is also causallity?

A

No, relation does not mean one causes the other.

22
Q

Does causality mean there is correlation?

A

Yes, this is required

23
Q

What is the main reason that it is hard to establish a single explaination in causality?

A

Unknown (and often uncontrollable) factors.

24
Q

What is the third variable problem?

A

That there are (un/)known variables at play that influence our data without our knowledge.

25
Q

What are lurking variables?

A

A type of third variable; Unkown to us, they can cause changes in DV’s and IV’s

26
Q

What is often the cause for lurking variables in your data?

A

Poor planning

27
Q

What are confounding variables?

A

Type of third variable; Known to us, They cause change in only DV’s. But their effect cannot be destinguished from that of any other IV.

28
Q

What is often the cause for confounding variables in your data?

A

Poor design of research

29
Q

What are mediating variables?

A

Third variable problem: Variables that facilitate the relationship between two other variables.

30
Q

What are moderating variables?

A

Third variable problem: They have an effect on the relationship between two other variables.

31
Q

What is the description of sampson’s paradox?

A

When the effect between two groups dissapears/reverses when looking at the subgroups.

32
Q

What does sampson’s paradox imply?

A

That there is a third variable to group by, either (un)controllable and (un)known.

33
Q

What is the description of Inspection Paradox?

A

The perceived observations or results are skewed from the truth due bias. (e.g. arrival time between trains feels longer than factually true.)

34
Q

What paradox is this? : The average classroom size according to students is larger than it actually is, because students are more likely to get (randomly) placed in larger classrooms.

A

Inspection

35
Q

What are quantriative variables?

A

Numerical variables such as age or testscores: measured quantity

36
Q

What are qualitative variables?

A

Not numerical variables or the numerical value is meaningless.

37
Q

What is meant with: levels of a variable should be exhaustive and mutually exlusive?

A

Exhaustive: Should contain all possible levels, Mutually exclusive: There should be a clear destinction between each level, and only one possible at a time.

38
Q

What are the different types of levels of measurements?

A

Nominal, ordinal, interval, ratio

39
Q

What level of measuremnt are variables of the type nominal?

A

Qualitative: sex, nationality, company (usually categorial variables)

40
Q

What level of measuremnt are variables of the type ordinal?

A

Qualitative, There is order, but no sense of magnitude: difficulty (none < some < much), agreement (totally > partially > slightly).

41
Q

What level of measuremnt are variables of the type interval?

A

Quantitative, There are magnitudes (equally spaced) but there is no zero or ground: Dates, age range, or temperatire (IN C OR F !)

42
Q

What level of measuremnt are variables of the type ratio?

A

Quantitative, sense of magnitude where the zero has a meaning: mass, temperature in kelvin, length, duration.

43
Q

Is it sensible to compute the median of ordinal variables?

A

Yes, ordinal variables are categorial.

44
Q

Is it sensible to compute the mean of ordinal variables?

A

No, the mean is meaningless as ordinal variables have no sense of magnitude or scale. (categorial)

45
Q

What is the main difference between ratio and interval variables?

A

Ratio variables have a (meaningfull) zero, where intervals are just magnitudes without a sens of scale.

46
Q

What is the difference between thurstone and lickert?

A

Thurstone is agree/disagree without neutral, where lickert offers multiple magnitudes and neutral options.

47
Q

What are indexes?

A

Quantitative (numerical) scores that combine multiple variables and reflect a single, general construct: e.g. an economical index may include dept, residence and purchasing power.

Data Analytics (9 decks)

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