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Psych research methods exam 2 flashcards

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1
Q

What are common ways of establishing reliability?

A
  1. Alternate form reliability:
  2. Test-retest reliability
  3. Measures of internal consistency
  4. Interrater reliability
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2
Q

Alternate form reliability

A

When you develop 2 versions of a measure, give them both to the same group of people, then correlate them.

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3
Q

Test-retest reliability

A

When you have one version of exam, give it to the same group of people a
2 different intervals

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4
Q

Measures of internal consistency

A

Measures of much items correlate with one another

Split-half reliability
Cronbach’s alpha

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5
Q

Split-half reliability

A

data collected is split randomly in half and compared, to see if results taken from each part of the measure are similar

ex: Test split in half, class take each half and the results are correlated

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6
Q

Cronbach’s alpha

A

Average of all the ways you can split half an exam

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7
Q

Inter-rater reliability

A
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8
Q

Kappa

A

determine how much raters agree with each other

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9
Q

Reliability coefficient of ways to establish reliability

A

Reliability of coefficient of at least 0.7 for all the methods of reliability except for kappa

Kappa: 0.4-0.75 is good for reliability

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10
Q

Population

A

Collection of units to which we want to generalize a set of findings or a statistical model too

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11
Q

Representative sample

A

Smaller collection of units from a population used to determine truths about that population

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12
Q

Random selection

A

Randomly select people from a population

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13
Q

Random sample

A

Each individual of the population has an equal chance of being selected

In a random sample, the probability of people have to stay the same

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14
Q

Parameter

A

A value, usually a numerical value, that describes the entire population

The value is derived from measurements of the individuals in the population

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15
Q

Statistic

A

A value, usually a numerical value, that describes a sample

Derived from measurements of the individuals in the sample

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16
Q

Statistical notation

A

Scores are referred to as X and Y

Collecting data on age and number of Facebook friends, you label age as X and friends as Y

N refers to the number of scores in a population

n is the number of scores in a sample

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17
Q

Sigma (summatation)

A

Add a set of scores from the sample

Summatation
Done after operations
- in parenthesis
- Squaring
- multiplication
- division

Summation is done before
Addition
Subtraction

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18
Q

What is a frequency distribution table

A

Representation that tells the frequency of different scores in your sample

Function: Organizes all the data so that the complete distribution can be viewed all at once

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19
Q

What are examples of frequency distribution tables and what are they used for?

A

Polygon or histogram for continuous data

Bar graph for categorical data

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20
Q

How to differentiate between a bar graph and histogram

A

Bar graph has spaces between them and is only used for categorical data
while histograms are used for continuous data

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21
Q

Statistical notation

A

Scores referred to as x and y

N refers to number of scores in a population

n is the number of scores in a sample

Σ stands for summation stand for summation and is when the set of scores are added up

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22
Q

Summation

A

Represented by Σ

Done after PEMD
Done before AS

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23
Q

What are the measures of internal consistency

A

Split-half reliability
Coefficient/Cronbach’s alpha

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24
Q

Bar graph

A

graph that presents categorical data with rectangular bars with heights proportional to the values that they represent.

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25
Histogram
chart that plots the distribution of a numeric variable's values as a series of bars
26
What are the four characteristics to look for in a frequency distribution
1. Shape 2. Location 3. Spread 4. Sample size
27
Types of shapes in a frequency distribution
Modality Symmetry Skew (positive or negative) Slope-Kurtosis (leptokurtic or platykurtic)
28
What is the location of a frequency distribution?
A measure of where the bulk of data sits on the number line and where the central tendency is
29
Central tendency
A statistical measure where a single score defines the center of a distribution
30
What is the purpose of the central tendency?
Describe the distribution by identifying its center Find the single score that best represents the entire group
31
What are the measures of central tendency?
Mean Median Mode
32
What happens to the mean when you change the value of a score or add/remove a value?
The mean changes unless the score added or removed is equal to the mean
33
What happens to the mean when you add or subtract a constant from each score
Changes the mean by the same constant
34
What happens to the mean when you multiply or divide each score by a constant?
The mean would also be multiplied or divided by that constant
35
Line graph
Graphical representation of information that changes over a period of time Used to show how something changes over time
36
George W. Bush's Tax cuts
Tax deduction passed in 2001 that stated 92 million Americans would receive an average tax reduction of 1083 However the median tax cut was $100
37
Median
Midpoint of distribution (defined by number of scores)
38
Mean
Balance point of a distribution
39
What is common between the mean and median
Both measure central tendency
40
Mode
Most frequent score/value in the dataset Only measure of central tendency that can be calculate categorical variables
41
Range
Difference between covered highest and lowest values Considered unreliable measure of variability as it is based only 2 scores
42
What are the Quartiles
Three values that split sorted data into four equal parts
43
What are the three quartiles
Lower quartile = median of lower half of data Second quartile = median Upper quartile = median of upper half of data
44
Interquartile range (IQR)
The range of the middle half of the data
45
What is a box plot and what can it effectively identify
Visualization of median and IQR Effectively identifies outliers
46
How is total error found
By adding up all the deviations
47
How is the Sum of Squared Errors found
1. Add deviation 2. Square each deviation 3. Add all the squared deviations
48
What is the Definitional Formula of Sum of Squared Errors
SS = Σ(X–μ)^2 Steps 1. Find each deviation score 2. Square each deviation score 3. Sum up the squared deviations
49
What is the computational formula of sum of squared errors
SS = Σx^2 - (ΣX)^2/N Steps 1. Square each score and sum them 2. Find sum of scores and square it, divide by N 3. Subtract the step #2 from the first step
50
Notation of Σ
Sum the scores
51
Notation of N
number of scores in population
52
Notation of n
number of scores in sample
53
Notation of X and Y
Each score is referred as X and Y
54
What is the variance
Statistical notation (s^2) Calculated by dividing SS
55
Notation of SS
Sum of Squared Errors
56
Variance of sample formula
S^2 = SS/n-1
57
Variance of population
s^2 = SS/n
58
Notation of s
Standard deviation
59
Standard deviation of sample formula
s = square root (SS/n-1)
60
Standard deviation of population formula
s = square root (SS/N-1)
61
What is standard deviation
An average for how far data points are from the mean A large derivative means more spread out (determines representation of data)
62
What are things SS, S^2 and S all represent
1. Fit of mean to data 2. How well mean represents observed data 3. Variability in the data 4. Error
63
How would adding or subtracting a score by a constant change SD
The SD would stay the same
64
How would multiplying or dividing a score by a constant change SD
Causes the standard deviation to be multiplied by the same constant
65
Positive skew
The tail is more pronounced on the right side Means skewedness is less than 0 since it is in the positive direction
66
Negative skew
The tail is more pronounced on the left side Means skewedness is less than 0 since it is in the negative direction
67
Kurtosis
Bell curve shape in distribution tables that describes distribution of observed data around the mean
68
Leptokurtic
Low kurtosis Characterized by broad peak and thin tails
69
Platykurtic
High kurtosis Characterized by high peak with thick tails
70
Skewness
Measure of the asymmetry of a distribution
71
What is a correlation?
Way of measuring the extend to which two variables are related
72
What are the characteristics of a correlation
Direction (negative or positive) Form (linear is most common) Strength
73
What are the three measures of variability
Range Interquartile range Standard deviation
74
What are the functions of measures of variability
Describes whether the scores are widely scattered or closely scattered Helps describe the location of individual scores Gives indication how well a measure of central tendency represents the whole group
75
What is the correlation coefficient
Variance shared by both variables/(total variance of both variables) = +1/-1 How much of total spread variance is shared between both variables
76
Correlation coefficient levels
0 = no relationship +/- 0.1
77
What is the coefficient of determination?
Proportion that each of the variables play r^2
78
Sum of products (SP)
Measures covariability between two variables SP = Summation (X- Mx)(Y-My)
79
Problems with covariability
1. Depends upon the units of measurement 2. One solution
80
Partial correlation
Measures the relationship between two variables, controlling for the effect that a third variable has on them both.
81
Z score
Standardizing a score with respect to the other scores in the group. Allows you to identify and describe location of every score in the distribution Computing a z-score is equivalent to asking where the score (X value) is located in the distribution.
82
Z score calculation
Z = X - (mean of sample)/ SD
83
What does the sign and number of the z score tell you
The sign tells whether the score is above or below the mean The number tells distance between score and mean in standard deviation units
84
What is a shape of a normal distribution?
- Symmetrical - Highest frequency in the middle - Frequencies taper off towards the extremes
85
Definition of probability
The likelihood that a specific outcome will actually occur
86
Probability formula
number of outcomes classified as A/total number of possible outcomes ex. 4 men, 15 women 4/19
87

Psych research methods (2 decks)

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