W2: RQ for Associations (Page 1-22) Flashcards

1
Q

What does a good research question contain:

A
  1. ) A question
  2. ) All constructs being investigated
  3. ) The study population
  4. ) A verb that indicates the type of relationship among constructs being proposed (Associations, Predictions, Difference)
    * Most important
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What is a population and a sample? How many are there?

A

Population

  • Complete set of all individuals relevant to our research question (often defined by psychological construct)
  • Only one relevant to the RQ

Sample

  • Subset of individuals selected by some sampling scheme from the population, and assumed to be representative of that population
  • Many samples drawn from the population, but typically use one in research
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Random varable and random samples. What are the types? How is it typically done?

A

Random Variable

  • Each value has an associated probability of ocurrence

Continuous

  • Any numerical value within a defined interval (e.g. 0 to 100, -infinity to +infinity)

Discrete

  • Finite number of distinct values (e.g. integers 1,2,3,4,5)

Random Sample

  • Each member of the population has an equal probability of being selected.
  • Typically done using a uniform probability distribution
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Construct, Measures and Scores

A

Construct

Unobservable attributes to explain human behavior

Measure

Method to measure people on a construct to obtain a construct score

Scores

Numerical value on construct measure assigned to an individual

  • Raw
  • Deviation
  • Z
  • Standardised
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

What is a raw/observed score and what are they generally indicated by

A

Values obtained directly from construct measure.

Capital letter (X,Y), a variable containing a set of values

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What is a deviation score and what are they generally indicated by.

A

X - mean(x) = x

  • Lower case letter (x,y)
  • Mean subtracted from individual score
  • Mean: 0
  • SD: Same as SD from Raw Scores
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

What is a z score. What is the formula, mean and sd of z scores

A

Particular kind of standardized score by dividing a deviation score by standard deviation

z = x / sd(x)

  • Mean = 0
  • SD = 1
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What is a standardized score (Generally speaking). Give an example.

A
  • Raw scores that have been transformed such that that have a predefined mean and a predefined scaling for each unit standard deviation.
    • IQ = 100 + 15*z
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What do score transformation change?

A

Changing raw scores into deviation, z or standardised scores:

  • Will ONLY change scaling of the variable
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

If both measures are continuous/categorical, what do we use?

A

2 Continous

Correlation

2 Categorical

Contingency Tables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

How do we quantify a relationship between 2 variables?

A

By calculating a relevant summary characteristic over all observed scores

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What is summary characteristics. What kinds are there?

A

Aggregation undertaken on individual values to produce a single quantity informative about values (e.g. mean, standard deviation, correlation)

  • Sample Statistics
    • Aggregated summary characteristic of individual scores calculated in a single sample drawn from a population
    • Can be many values for a sample statistic, one for each sample drawn from the same population
  • Population Parameters
    • Aggregated summary characteristic of individual scores derived from all members of a population
    • Only one, which is unknown
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is a Sample and Population Distribution?

A

Sample Distribution

  • If we measure individuals in a single sample drawn from the population, then the set of scores form a sample distribution
  • Many possible distributions

Population Distribution

  • If we measure everyone in the population on a construct, then the set of scores form a population distribution.
  • One possible distribution
    • Which will be much larger than any single sample distribution but the size of the population is unknown in most cases…
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Scatterplot vs Correlation Plot

A

While associations between multiple variables can be observed in both, it is much easier to discern patterns in correlation plots

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What is a Pearson Correlation

A

Measure of linear symmetric association between two continous variables.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What defines association strength?

A

The absolute value of a correlation indicates the strength of (linear) association. Ignore whether it is positive or negative in value

17
Q

What is the population correlation coefficient and sample correlation coefficient?

A

Population Correlation Coefficient

  • p (rho)
  • Correlation calculated on everybody in a population
  • Value almost certainly unkown

Sample Correlation Coefficient

  • r
  • Correlation calculated on sample
    • Differs from one sample to the next
  • Use this known sample value to estimate unkown population value
18
Q

What are the effects of having a larger sample size

A
  • Reduces variability of the sampling distribution
    • More Narrow
    • Smaller Standard Error
19
Q

What is a sampling distribution. Why is it relevant?

A

A distribution of values of a sample statistic obtained from a large number of repeated samples taken from a population

  • Anytime we have a distribution of values, we can calculate summary characteristics of those values (e.g. mean)
  • Any kind of sample statistic (e.g. correlation coefficient) will have a corresponding sampling distribution
  • Under certain conditions, it can be shown that the mean of a sampling distribution will get closer to the unknown population parameter value as the number of repeated samplings increases
    • Standard error (SD of sampling distribution) can be estimated from ONE sample statistic
    • Note: Range will be more variable…
20
Q

Why and What is a confidence interval. What does it have.

A

Research: One Sample.

We cannot construct sampling distributions but using a confidence interval gives us a good idea of the likely value of the unkown population parameter

Confidence Intervals

Range of plausible values of an unknown population parameter based on the

  • (1) value of SINGLE sample statistic
  • (2) its standard error.
21
Q

Will the population distribution be larger/smaller than a sample distribution

A

Much Larger

22
Q

What does it mean by “symmetry” in a Pearson Correlation

A

Correlation of X and Y = Correlation of Y and X

23
Q

What is the correlation value always between

A

-1 to +1

24
Q

Will any kind of sample statistic have a corresponding sampling distribution. What happens when sampling increases (under conditions)

A

In Theory, yes. - Anytime we have a distribution of values, we can calculate summary characteristics.

Under conditions, as Sampling increases, 1.) Mean of sampling distribution will get closer to unknown population parameter value 2.) SD can be calculated (known as Standard Error)

25
Q

How many types of scores are there

A
  • Raw Score
  • Deviation Score
  • Z-Score
  • Standardised Score
    • Deviation, Z and Standardized Scores are transformations of Raw Score
    • Changes scaling only