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Psychology - Year 1 Weekly Flashcards > PL1010: Research Design and Methods 1B > Flashcards

PL1010: Research Design and Methods 1B Flashcards

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1
Q

Categorical variable

A

Variable with scores that are not on a numeric scale

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2
Q

Descriptive statistics –

A

Summarise samples – giving someone the main points in a simple form To describe data, we will use graphical and numerical (statistical) techniques

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3
Q

Inferential statistics –

A

Examine patterns in the data and consider how much data we have You can then draw conclusions about a population based on the analysis of a sample. -> conceptual replication

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4
Q

Summarising

A

collecting and summarising data

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5
Q

Statistical inference

A

the ability to draw general conclusions from samples

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6
Q

How many times does a particular score occur?

A

Percentages/Averages Scores for a particular variable (Frequency statement)

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7
Q

Do scores for one variable correlate with scores for the other variable?

A

Statement about association

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8
Q

How strong is the correlation or association between two variables?

A

Statement about association

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9
Q

Do I trust that there is a “genuine” association (relationship)?

A

Statement about relationship between two variables

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10
Q

Frequency Distribution?

A

show scores in order and their frequency of appearance in the sample

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11
Q

Negatively skewed

A
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12
Q

Positively Skewed

A
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13
Q

When not to describe the skew of data?

A

When we cannot put our scores in order , from lowest
to highest so when we are describing a categorical
variable with unordered categories

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14
Q

Unimodal?

A

One major peak

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15
Q

Bimodal

A

Two major peaks

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16
Q
A

Approximately symmetrical

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17
Q

How do outliers and the mean relate to each other?

A

Outliers are extreme values that differ from most values in the data set. Because all values are used in the calculation of the mean, an outlier can have a dramatic effect on the mean by pulling the mean away from the majority of the values.

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19
Q

What happens to the mean, median and mode in a skewed distribution

A

in normal distributions, they all take on the same number

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20
Q

Why are histograms good?

A

effective visual summary of a variable’s central tendency and variability

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21
Q

What is a discrete, continuous, independent and dependent variable?

A

Discrete: variable that is limited (age, gender) Continuous: exists on a continuum basically infinite between highest/lowest IV: variable manipulated/changed to see whether it has an effect on the DV that might change because of the manipulation DV: variable that, though measured, is not being controlled

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22
Q

What is the role of measurement scales?

A

The numbers don’t necessarily say anything concrete about the objects measured <i>ex.: if I scored high on a test, but someone else scored lower, it’s not necessary because they remembered less even though the data might suggest it → we assume that they mean I remembered more</i>

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23
Q

What is the purpose of a frequency distribution?

A

Organising data into a meaningful order of how many times

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24
Q

Which variable do I usually find on the X- and Y-Axis in histograms vs. line graphs?

A

histogram: dv-iv Line/Bar graph: iv-dv

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25
Q

What is the mode, median, mean (+formulas)?

A

Mode: the highest point in the graph Median: 50th percentileMean: Sum of N/ N

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26
Q

If the mean is slightly larger what does it probably say about or distribution?

A

Positively skewed

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27
Q

When will the mean and the median be equal?

A

Symmetric distribution

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28
Q

The benefit of the mode is?

A
  • Representing categorical data * More informative *But not very reflective of the remaining data set
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29
Q

The benefit of the median is?

A

Not affected by outliers Not stable in comparison and not useful to calculation

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30
Q

What does central tendency refer to?

A

The scores tendency to distribute in a certain way?

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31
Q

What is the advantage of a bar chart?

A
  • Comparing categories * Mirrors other visualisation techniques were the spread is along the X-axis and the frequency or percentage is along the Y-axis already hints at modality and skewness
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32
Q

What is an alternate name for the y-axis/x-axis?

A

ordinate/abscissa

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33
Q

Suppose you sell ice cream with three different flavours: chocolate, strawberry and yogurt. The ice cream flavours are measured on a ____________ level. You sell ice cream to children, adults and elderly people. These age groups are measured on a ____________ level.

A

nominal; ordinal

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34
Q

operational definition

A

defining a variable in terms of the set of steps or procedures that the researcher goes through in order to manipulate or measure the variable

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35
Q

right skewed

A

positively skewed

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36
Q

What does a negatively skewed distribution reveal?

A

A lot of people got close to the maximum score

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37
Q

What does central tendency mean?

A

average score

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38
Q

Age in months is an example of a variable with a ratio scale of measurement. Select one:
True
False

A

T

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39
Q

What are two ways to visually represent to measurement data variables?

A
  1. scatter plots 2. contingency tables/crosstabulation
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40
Q

What is a way to visually represent a mix of categorical and measurement data?

A

compound histogram

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41
Q

What is a way to visually represent categorical data pairs?

A

crosstabulation

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42
Q

What are the groupings of scores in histograms called?

A

bins

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42
Q
A
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43
Q

Do these images show the same data?

A

Yes

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44
Q

Which visual representation should you choose if you want to show that variables vary simuntaneously?

A

scatter-plots

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45
Q

What does a boxplot do?

A

summarises the data while showing the range, interquartile range, as well as the min, max and the median

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46
Q

When is the mean most useful?

A

best for interval/ratio measurement data (categorical data can hardly be split into 2), needs equal spacing between adjacent values

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47
Q

What is the mode most useful for?

A

all but notably for nominal/ordinal categorical data because popular choice

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48
Q

Variables are

A

properties of objects that vary in the values that they take on

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49
Q

A score is

A

an individual value for a variable

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50
Q

Measurement data describes

A

scores on a numerical scale

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51
Q

Categorical data describes

A

scores not on a numerical scale

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52
Q

A Population describes

A

a complete set of scores that might be of interest

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53
Q

A Sample is

A

a sub-set of scores from a population which were obtained

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54
Q

A parameter is

A

a number that summarises the entire set of scores in a population

55
Q

A statistic is

A

a number that summarises the scores in a sample

56
Q

Descriptive Statistics…

A

summarise samples by presenting the main points in a simplified way

57
Q

Inferential statistics…

A

examine patterns in the data and consider the amount of data

58
Q

Ethnicity or political ideology are examples

A

nominal variables

59
Q

standardised scores (z-scores)

A
60
Q

Z-Score Formula

A
61
Q

Falsifiability

A

capacity for some proposition, statement, theory or hypothesis to be proven wrong (through systematic empiricism) a basis provided by the null hypothesis

62
Q

null hypothesis

A

states the contrary of the experimental or alternative hypothesis

63
Q

falsifiable hypothesis

A

can be logically contradicted by an empirical test that can potentially be executed with existing technologies .

64
Q

What is meant by dispersion/variability around the mean?

A

Determining how the scores relate towards the mean score

65
Q

What are measures of variability?

A

Range Interquartile Range Standard deviation Sample variance if sd=0 so we square scores and then take the sum so negative scores become positive Absolute Mean Deviation SD but not squared which could= 0

66
Q

What are the mean and standard deviation in the standard normal distribution?

A

mean=0 and sd=1 → z-score standard score specifying the amount of distance of the sd

67
Q

What is the mean and the standard deviation of t-scores?

A

Mean = 50 SD= 100

68
Q

What is meant by sampling error?

A

Chance difference = the way some statistics naturally varies from sample to sample = in that it wll always deviate from the parameter it is the random variability = standard deviation of the sampling distribution

69
Q

What is the standard error of the mean?

A

The standard deviation / variability from the estimated parameter mean of the distribution

70
Q

What is the purposes of the standard error?

A

It gives us an indication of just how much the sample statistic might differ across the samples. It’s like a z-score for all the potential differences we could observe but would not go against the finding

71
Q

What are the logical steps of hypothesis testing?

A

Set up a research Hypothesis H1 Set up a null hypothesis H0 Get a sample and sample distribution of sample statistics (eg mean) und the H0 Calculate probability value of of sample statistic at least as large as the one obtained Reject or Fail to Reject H0

72
Q

What’s the philosophical hypothesis of the null hypothesis?

A

M1-m2 =0 has been proposed by Fisher With the logic that we can always show that something is false

73
Q

How do you calculate the IQR?

A

Order the scores Find the median location (N/2) Find the median of the upper and lower quartile N low /2; N high /2

74
Q

What do d= 1 and d= .5 indicate?

A

That the effect the difference is either twice or half as large as the standard deviation

75
Q

What are the absolute deviations from the mean?

A

X- Mean that’s why if we average and take the root of them we get the standard sample deviation

76
Q

When you collect data from a sample, the sample variance is used to ?

A

make estimates or inferences about the population variance and comparing the variance of samples helps you assess group differences

77
Q

How is the sample mean related to variance and standard deviation?

A

it is expanded on in the formulas for variance and standard deviation

78
Q

Which five steps need to be taken to calculate the sample variance?

A
  1. The mean (∑ 𝑋 /N) 2. The Deviation from the mean X- (∑ 𝑋 /N) 3. Squared deviation from the mean (X- (∑ 𝑋 /N))^2 4. Find the sum for all scores and devide by N-1 5. Take the root to find the standard deviation or z-score
79
Q

The standard deviation is more informative about the variability than the variance.

A

False

80
Q

The standard deviation is expressed in larger units than the variance.

A

False because the root is taken

81
Q

What does the standard deviation tell me?

A

how far, on average, a value lies from the mean which is why it is derived from the variance (square root)

82
Q

Which graph describes a correct null hypothesis?

A

right

83
Q

The p-value can be defined as

A

the probability of obtaining a significant result when the null hypothesis is true

84
Q

Do scores for one variable correlate with scores for the other variable?

A

Statement about association

85
Q

How strong is the correlation or association between two variables?

A

Statement about association

86
Q

Do I trust that there is a “genuine” association (relationship)?

A

Statement about relationship between two variables

87
Q

null hypothesis

A

states the contrary of the experimental or alternative hypothesis

88
Q

A linear correlation describes

A

Two variables that are either proportionate or anti proportionate

89
Q

Correlation coefficient

A

A number also represented by “r” describes positive (r=1), negative (r=-1) or no correlation (0=r)

90
Q

Operational Definition

A

procedure for indirectly measuring and defining a variable that cannot
be observed or measured directly. An operational definition specifies a measurement procedure (a set of operations) for measuring an external, observable behaviour and uses the resulting measurements as a
definition and a measurement of the hypothetical construct.

91
Q

operational definition

A

defining a variable in terms of the set of steps or procedures that the researcher goes through in order to manipulate or measure the variable

92
Q

Sampling variability

A

differences in or across samples due to random things happening

93
Q

What are two ways to visually represent to measurement data variables?

A
  1. scatter plots 2. contingency tables/crosstabulation
94
Q

How should the strength of a correlation be interpreted?

A
  • Perfect:(-) 1/1 * Strong:(-) 09-07 * Moderate:(-).6-.4 * Weak: (-). 3-.1 * None:0
95
Q

Which visual representation should you choose if you want to show that variables vary simuntaneously?

A

scatter-plots

96
Q

The p-value can be defined as

A

the probability of obtaining a significant result when the null hypothesis is true

97
Q

Face Validity

A

basic form of validity demonstrated when a measurement procedure superficially appears to measure what it claims to measure

98
Q

Concurrent Validity

A

demonstrated when scores obtained from a new measure are directly related to scores obtained from an established measure of the same variable.

99
Q

Predictive Validity

A

demonstrated when scores obtained from a measure accurately predict behaviour according to a theory.

100
Q

Construct Validity

A

requires that the scores obtained from a measurement procedure behave exactly the same as the variable itself.

101
Q

What needs to be taken into consideration for construct validity

A

based on many research studies that use the same measurement procedure and grows gradually as each new study contributes more evidence.

102
Q

Convergent Validity

A

demonstrated strong relationship between the scores obtained from two or more different methods

103
Q

Divergent Validity

A

demonstrated by showing little or no relationship between the measurements and two constructs

104
Q

Test-retest reliability

A

established by comparing the scores obtained from two successive measurements of the same individuals and calculating a correlation between the two sets of scores.

105
Q

Inter-rater reliability

A

degree of agreement between two observers who simultaneously record
measurements of the behaviours

106
Q

Split-half reliability

A

obtained by splitting the items on a questionnaire or test in half, computing a
separate score for each half, and then calculating the degree of consistency between the two scores for a
group of participants.

107
Q

What are the two types of measures of reliability

A

Successive and simultaneous measurements

108
Q

Construct

A

hypothetical attributes or mechanisms that help explain and predict behaviour in a
theory

109
Q

What is naturalistic observation

A

A form of non-participant observation where a researcher is in a natural setting in which behaviur usually occurs without interupting

110
Q

What is In participant observation

A

researcher engages in the same activities as the people being observed
in order to observe and record their behaviour.

111
Q

What are naturalistic observation usually used for

A

used to describe non-human behaviour or children

112
Q

What are the benefits and disadvantages of naturalistic observation (5)

A

external validity: real world setting behaviour is not manipulated overcoming ethical barriers –> instigating spanking vs. observing spanking time-consuming: having to wait till behaviour occurs research is prone to interruptions

113
Q

When is participant observation needed

A

When simple observation is not possible. e.g. studying cults or gangs because their presence would alter the behaviour

114
Q

What are advantages and disadvantages of participant observations (5)

A

access to information and observation unavailable to mere outside observation high external validity because of naturalistic setting time consuming observation potentially dangerous for researcher (sensitive nature) observers presence might alter participants’ experience –> objectivity?

115
Q

What is Structured observation?

A

or contrived observation is the observation of behaviour in settings arranged
specifically to facilitate the occurrence of specific behaviours so they don’t have to wait for them to happen

116
Q

Advantages and Disadvantages of structured observations

A

can be held in laboratory or other controlled settings to percipitate the behaviour that they want to observe –> good for developmental psych can be held in what is perceived a sa natural environment (field setting) less time consuming how natural is the behaviour?

117
Q

During a study using observational methods, it is common to have two observers record behaviour
simultaneously. What is the purpose for this procedure?

A

objectivity of the measurements

118
Q

In an observational study of children diagnosed with autism spectrum disorder, you record how
much time each child spends playing alone during a 30-minute observation period. Which method
of quantifying behaviour is being used?

A

duration

119
Q

When researchers use behavioural observation techniques to measure behaviours in movies, what
is the measurement process called?

A

content analysis

120
Q

What are behavioural tasks

A

usually computer-controlled, structured tasks measured across multiple repeated trials that researchers use to collect behavioural measures such as
response times and task accuracy measures.

121
Q

What are many behavioural tasks structured around?

A

human information processing like cognitive tasks assessing attention, memory, language and decision making

122
Q

What can also be measured by behavioural tasks

A

attitudes, preferences aside from cognitions

123
Q

What is the main measure of interest in behavioural tasks

A

not the usually correct answer but speed of the response (response or reaction time)

124
Q

What is a task paradigm

A

task originally constructed to investigate a particular hypothesis is used and adapted to examine others subsequently providing a standard model for line of research

125
Q

What are two prerequisites of behavioural observations

A

behaviour is not disturbed observations are based in subjective judgments and intepretations which pose a threat to reliability so need for more than one observer

126
Q

Archival research

A

involves looking at pre-existing records (archives) to measure behaviours or events
that occurred in the past

127
Q

Content analysis

A

measuring the occurrence of specific events, actions or statements in written
text (e.g., literature, press reports, transcripts) or film/video recordings (e.g., movies, television programmes) or similar media

128
Q

How is the issue of interpretation in observational designs addressed (3)

A

well-defined categories of behaviour well-trained observers multiple observers or coders to assess inter-rater reliability

129
Q

What are behaviour categories

A

well/defined sets of behaviour that is to be observed which helps isolating relevant behaviours

130
Q

How are observations quantified (3)

A

frequency: how many times does something occur in the given time-frame duration: for how long does a behaviour occur interval: does a behaviour occur in a given interval

131
Q

When are the three quantification methods most appropriate

A

first two techniques are often well suited for specific behaviours but can lead to distorted
measurements in some situations. For example, a bird that sings continuously for the entire 30-minute
observation period would get a frequency score of only 1. Another bird that sings 25 times with
each song lasting two seconds would get a duration score of only 50 seconds. In such situations, the interval method provides a way to balance frequency and duration to obtain a more representative
measurement

132
Q

How do observers overcome issues of complex situations that cannot be watched multiple times

A

creating a recorded sample or taking a general sample

133
Q

What are the 5 research strategies?

A

Descriptive (examining individual variables) Correlational (two variables for each individual) → numerical Experimental (cause-effect) Quasi-experimental (less control, assignment) Non-experimental

Psychology - Year 1 Weekly Flashcards (4 decks)

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