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SSR > Johnny, CH.1 - Intro to Statistical Reasoning > Flashcards

Johnny, CH.1 - Intro to Statistical Reasoning Flashcards

1
Q

Research Process

A
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2
Q

What are the steps in the Research Process?

A
  1. initial observation
  2. theory
  3. hypothesis (identify variables)
  4. prediction
  5. data collection (measure variables)
  6. data analysis

see picture 1!

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3
Q

Before going from your initial observation to your theory, what must you do first?

A

You must identify one or more Variables, in order to be able to collect data later on

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4
Q

What is a Theory?

A

An explanation/set of principles that has been substantiated by repeated testing’s and explains a broad phenomenon
- A theory is general, and not specific to your observations

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5
Q

What is a Hypothesis?

A

A proposed explanation for a fairly narrow phenomenon of observations
- A hypothesis is specific and theory driven, and attempts to explain what has been observed
- The step from “Hypothesis” to “Generate Predictions” is to transform your hypothesis (something unobservable) into a prediction (something osbervable)

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6
Q

What are the 2 types of Variables?

A
  • Predictor Variable (PV) (How Johnny calls the Independent Variable (IV)). It is thought to predict the outcome Variable
  • Outcome Variable (OV) (How Johnny calls the Dependent Variable (DV)). Changes as a function of changes in a predictor variable
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7
Q

What are the different types of variables?

A
  • categorical
    > binary (2 categories)
    > nominal (>2 categories)
    > ordinal (many ordered categories)
  • continuous
    > interval (equal intervals represent the same difference; no true 0)
    > ratio (equal intervals represent equal differences; true 0)
    see powerpoint!
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8
Q

Validity and Reliability

A
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9
Q

What is Validity?

A

Whether an instrument measures what it sets out to measure

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10
Q

What are the 4 types of Validity (mentioned by Johnny, not in general)?

A
  • Criterion Validity: How accurately a test measures the outcome it was designed to measure.
    ~ Concurrent Validity: The extent of agreement between two measures when data are recorded simultaneously
    ~ Predictive Validity: The ability of a test to predict a future outcome.
  • Content Validity: Degree to which test items represent the constructs being measured
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11
Q

What is Reliability?

A

Whether an instrument can be interpreted consistently across many studies

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12
Q

Research Designs

A
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13
Q

What are the two main research methods?

A
  • Correlational research method
  • Experimental method
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14
Q

What is the correlational research method?

A

Observing natural events and their correlations without manipulation

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15
Q

What are some problems with the correlational research method?

A
  • Doesn’t establish contiguity between two variables (which variable affects which)
  • Tertium Quid (3rd variable problem)
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16
Q

What is the experimental method?

A

Researcher manipulates the IV and observe the effects of that manipulation on the DV
- it establishes causality

17
Q

What are the different possible designs in an experimental research method?

A
  • Between-groups/subject design (or else, independent design): There are different groups with different people for each condition
  • Within-subject/repeated measures group: All participants are in all conditions
18
Q

What is Variance?

A

The statistical measure of Variability

19
Q

What are the 2 types of variance in an experimental research method?

A
  • Systematic: Due to manipulation
  • Unsystematic: Created by unknown (random) factors
20
Q

What can researchers do to maximize systematic and minimize unsystematic variance?

A

Randomize participants to conditions OR randomize the order in which participants receive conditions.
EXAMPLE: in repeated measures design, there are the following problems
- Practice effects: Participants perform differently in the 2nd condition because of familiarity with the situation and measures
- Boredom effects.
If we randomize this solves the above problems:
- Half of the participants: Condition 1, then Condition 2
- The other half: Condition 2, then condition 1

21
Q

Data Analysis - Distribution

A
22
Q

What are Histograms (or frequency distributions)?

A

A visual representation of the distribution of quantitative data. (See picture 2)

23
Q

What is the skew of a frequency distribution?

A

It’s the measure of asymmetry of a distribution
(See Picture 3 for different skews)

24
Q

What is the kurtosis of a frequency distribution?

A

A statistical measure used to describe the degree to which scores cluster in the tails or the peak of a frequency distribution
- Leptokurtic: too many scores in the tails (Kurtosis>0)
- Platykurtic: too little scores in the tails (Kurtosis<0)
- Mesokurtic: Normal Distribution (Kurtosis=0)
!!! Pointiness of distribution does not play a role !!!
(See picture 4 for examples of the above)

25
Q

What is the central tendency of a distribution?

A

Where the center of the distribution is

26
Q

How do we compute the central tendency of a distribution?

A

Using the mean, mode and median
- Median: Middle score (in the case of an even number of scores, e.g. 10, median equals the two middle scores divided by two: (5th + 6th)/2)
~ Unaffected by extreme scores at either end of the distribution

27
Q

What is the mode?

A
  • Mode: The score that occurs more frequently in the data
    ~ If there are two most frequent scores, the distribution is bimodal
    ~ If there are more than two most frequent scores, the distribution is multimodal
28
Q

What is the median?

A
  • Median: Middle score (in the case of an even number of scores, e.g. 10, median equals the two middle scores divided by two: (5th + 6th)/2)
    ~ Unaffected by extreme scores at either end of the distribution
29
Q

(Mean)

A

(No need to explain formula)
- Affected by extreme scores

30
Q

What is the dispersion of scores?

A

How spread out the scores are. Some measures of dispersion:
- x(largest) - x(smallest): Range of scores
- QUANTILES: Values that split the data into equal proportions, e.g.
~ Quartiles (4 equal parts)
~ Noniles (9 equal parts)
~ Percentiles (100 equal parts)
- Look at how spread out each score is from the center of the distribution: deviance (or error) = xi - x(mean)
~ Total Deviance: Sum of (xi - x(mean)
~ If Total Deviance = 0, we can use the Sum of Squared Errors: SS = Sum of (xi - x(mean))^2.

31
Q

What is a problem with the SS and what do we do in that case?

A
  • the size of SS depends on number of scores
  • Variance (S^2) = SS/(N-1)
    > problem: the measure is in units squared
  • square root of the variance -> the standard deviation (S).
  • As S increases, the distribution gets fatter (more leptokurtic)
32
Q

How do do different variables change how the distributions are presented?

A
  • Discrete/categorical Variables: p (proportion) = height of bar
  • Continuous Variable: p = area under curve
33
Q

What is a probability distribution?

A

It is like a histogram but without shapes or lines, instead with a curve.
- All in between values are possible
- When we convert any set of scores to a standard normal distribution (Mean of 0, SD of 1) we use z-scores.
~ Formula of z-scores: Z = [X - X(MEAN)]/SD
- If z of a certain score was below 0, that original score was below the mean
- If z of a certain score was above 0, that original score was above the mean

34
Q

What is a frequency distribution?

A

It can be either a table or chart that shows each possible score on a scale of measurement along with number of times that score occurred in the table

35
Q

Reporting Data

A
36
Q

What are some guiding, general principles when it comes to reporting data?

A
  • Choose a mode of presentation that optimizes the understanding of the data
  • If you present 3 or fewer numbers, try using one sentence to report that data
  • If you need to present 4-20 items, use something like a table
  • If you need to present >100 items, use something like a graph
37
Q

What are some other issues to be considered when reporting data?

A

How many decimal points you use when reporting numbers
- Fewer decimal points are better, the more we round up the better, but bear in mind the precision of the measure you’re reporting

38
Q
A

SSR (12 decks)

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