Descriptive stats Flashcards

1
Q

What are the 3 research designs?

A

Deductive / inductive
Quantitative / qualitative
Design quality

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2
Q

What is deductive approach?

A

Start from a theory that will be tested

Th => Hyp => Obs => confirmation / rejection

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3
Q

What is inductive approach?

A

Data guides theory

Obs => pattern => Th

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4
Q

What is quantitative approach?

A

Manipulating data analyzed using mathematically based methods.

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5
Q

What is qualitative approach?

A

Results obtained are narrative / descriptive.

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6
Q

What is the difference between observation and experimentation?

A

Obs: measuring variables without intervention of the researcher.
Exp: Measuring manipulating at least 1 variable.

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7
Q

What are the 4 criteria of design quality?

A

Validity, Reliability, Replicability, Generalizability

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8
Q

What is Validity?

A

Do I measure what is supposed to be measured?

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9
Q

What is Reliability?

A

Does this research produce stable results?

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10
Q

What is Replicability?

A

If someone practices the same study exactly, will he find the same results?

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11
Q

What is Generalizability?

A

Does this experiment also occurs in the real life?

Is it possible to practice inference?

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12
Q

What are variables / indicators?

A

People or things from which data is collected.

Statistical units / cases.

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13
Q

What are the different types of variables?

A

Nominal / categorical (the less informative)
Ordinal
Interval / scale
Ratio (the most informative)

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14
Q

What is a nominal / categorical variable?

A

categories without order.

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15
Q

What is an ordinal variable?

A

2 or more categories that can be ordered.

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16
Q

What is an interval variable?

A

The difference between 2 values of this variable is meaningful.

17
Q

What is a ratio variable?

A

Each interval between 2 numbers is meaningful.

This allows to practice operations because there’s an absolute zero.

18
Q

What are the roles of variables?

A

Independent Variable (predictor / var predicted)
Dependent Variable
Each role leads to a different sort of analyses.

19
Q

What is an Independent Variable?

A

Variable manipulated / observed to observe the effect on the DV. It can be measured.

20
Q

What is a Dependent Variable?

A

What is measured.

21
Q

What are the 2 main fields for statistical analyses?

A

Sample => descriptive statistics

Population through informations obtained on the sample => inferential statistics

22
Q

What are the 2 possible inferential statistic methods?

A

Calculate a difference from 0 => p ratio.

Defining an interval in which the population is likely to be => the confidence interval. (Better)

23
Q

How are called statistics analyses regarding the number of variable involved?

A

1: Univariate
2 simultaneously: Bivariate
More than 2 simultaneously: Multivariate.

24
Q

What is the difference between parametric and non-parametric test?

A

Parametric tests are passed on the assumption of a normal distribution.
Non-parametric test can be used to test any distribution, even when it’s not normal.

25
Q

What are the 2 main attentions you have to give to the plan data before you start collecting data?

A

Sample carefully selected: randomly

Sample size: you must know the test before you gather data to choose the perfect size of sample.

26
Q

Outcome = ?

A

Outcome = model + error

=> Error = Outcome - model

27
Q

What does mean “calculating the parameters”?

A

Finding the values of the parameters that will minimize the error / deviation / residuals.

28
Q

What is used to calculate the parameters?

A

SSE = ⁿΣi=1(Obs-pred)²

It must be the lowest possible. This is the method of ordinary least squarer.

29
Q

What is the variance formula?

A

V = 1/N(ⁿΣi=1(obs-mean)²)