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Psych research methods > Psych research methods exam 2 flashcards > Flashcards

Psych research methods exam 2 flashcards

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
Q

Histogram

A

chart that plots the distribution of a numeric variable’s values as a series of bars

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26
Q

What are the four characteristics to look for in a frequency distribution

A
  1. Shape
  2. Location
  3. Spread
  4. Sample size
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27
Q

Types of shapes in a frequency distribution

A

Modality
Symmetry
Skew (positive or negative)
Slope-Kurtosis (leptokurtic or platykurtic)

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28
Q

What is the location of a frequency distribution?

A

A measure of where the bulk of data sits on the number line and where the central tendency is

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29
Q

Central tendency

A

A statistical measure where a single score defines the center of a distribution

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30
Q

What is the purpose of the central tendency?

A

Describe the distribution by identifying its center
Find the single score that best represents the entire group

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31
Q

What are the measures of central tendency?

A

Mean
Median
Mode

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32
Q

What happens to the mean when you change the value of a score or add/remove a value?

A

The mean changes unless the score added or removed is equal to the mean

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33
Q

What happens to the mean when you add or subtract a constant from each score

A

Changes the mean by the same constant

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34
Q

What happens to the mean when you multiply or divide each score by a constant?

A

The mean would also be multiplied or divided by that constant

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35
Q

Line graph

A

Graphical representation of information that changes over a period of time

Used to show how something changes over time

36
Q

George W. Bush’s Tax cuts

A

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
Q

Median

A

Midpoint of distribution (defined by number of scores)

38
Q

Mean

A

Balance point of a distribution

39
Q

What is common between the mean and median

A

Both measure central tendency

40
Q

Mode

A

Most frequent score/value in the dataset

Only measure of central tendency that can be calculate categorical variables

41
Q

Range

A

Difference between covered highest and lowest values

Considered unreliable measure of variability as it is based only 2 scores

42
Q

What are the Quartiles

A

Three values that split sorted data into four equal parts

43
Q

What are the three quartiles

A

Lower quartile = median of lower half of data

Second quartile = median

Upper quartile = median of upper half of data

44
Q

Interquartile range (IQR)

A

The range of the middle half of the data

45
Q

What is a box plot and what can it effectively identify

A

Visualization of median and IQR

Effectively identifies outliers

46
Q

How is total error found

A

By adding up all the deviations

47
Q

How is the Sum of Squared Errors found

A
  1. Add deviation
  2. Square each deviation
  3. Add all the squared deviations
48
Q

What is the Definitional Formula of Sum of Squared Errors

A

SS = Σ(X–μ)^2

Steps
1. Find each deviation score
2. Square each deviation score
3. Sum up the squared deviations

49
Q

What is the computational formula of sum of squared errors

A

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
Q

Notation of Σ

A

Sum the scores

51
Q

Notation of N

A

number of scores in population

52
Q

Notation of n

A

number of scores in sample

53
Q

Notation of X and Y

A

Each score is referred as X and Y

54
Q

What is the variance

A

Statistical notation (s^2)

Calculated by dividing SS

55
Q

Notation of SS

A

Sum of Squared Errors

56
Q

Variance of sample formula

A

S^2 = SS/n-1

57
Q

Variance of population

A

s^2 = SS/n

58
Q

Notation of s

A

Standard deviation

59
Q

Standard deviation of sample formula

A

s = square root (SS/n-1)

60
Q

Standard deviation of population formula

A

s = square root (SS/N-1)

61
Q

What is standard deviation

A

An average for how far data points are from the mean

A large derivative means more spread out

(determines representation of data)

62
Q

What are things SS, S^2 and S all represent

A
  1. Fit of mean to data
  2. How well mean represents observed data
  3. Variability in the data
  4. Error
63
Q

How would adding or subtracting a score by a constant change SD

A

The SD would stay the same

64
Q

How would multiplying or dividing a score by a constant change SD

A

Causes the standard deviation to be multiplied by the same constant

65
Q

Positive skew

A

The tail is more pronounced on the right side

Means skewedness is less than 0 since it is in the positive direction

66
Q

Negative skew

A

The tail is more pronounced on the left side

Means skewedness is less than 0 since it is in the negative direction

67
Q

Kurtosis

A

Bell curve shape in distribution tables that describes distribution of observed data around the mean

68
Q

Leptokurtic

A

Low kurtosis

Characterized by broad peak and thin tails

69
Q

Platykurtic

A

High kurtosis

Characterized by high peak with thick tails

70
Q

Skewness

A

Measure of the asymmetry of a distribution

71
Q

What is a correlation?

A

Way of measuring the extend to which two variables are related

72
Q

What are the characteristics of a correlation

A

Direction (negative or positive)
Form (linear is most common)
Strength

73
Q

What are the three measures of variability

A

Range
Interquartile range
Standard deviation

74
Q

What are the functions of measures of variability

A

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
Q

What is the correlation coefficient

A

Variance shared by both variables/(total variance of both variables)

= +1/-1

How much of total spread variance is shared between both variables

76
Q

Correlation coefficient levels

A

0 = no relationship
+/- 0.1

77
Q

What is the coefficient of determination?

A

Proportion that each of the variables play

r^2

78
Q

Sum of products (SP)

A

Measures covariability between two variables

SP = Summation (X- Mx)(Y-My)

79
Q

Problems with covariability

A
  1. Depends upon the units of measurement
  2. One solution
80
Q

Partial correlation

A

Measures the relationship between two variables, controlling for the effect that a third variable has on them both.

81
Q

Z score

A

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
Q

Z score calculation

A

Z = X - (mean of sample)/ SD

83
Q

What does the sign and number of the z score tell you

A

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
Q

What is a shape of a normal distribution?

A
  • Symmetrical
  • Highest frequency in the middle
  • Frequencies taper off towards the extremes
85
Q

Definition of probability

A

The likelihood that a specific outcome will actually occur

86
Q

Probability formula

A

number of outcomes classified as A/total number of possible outcomes

ex. 4 men, 15 women
4/19

87
Q
A

Psych research methods (2 decks)

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