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YEAR 2 Stats > Essential theory > Flashcards

Essential theory Flashcards

1
Q

Choice of statistic, or statistical test, depends
on 4 things

What are they?

A
  1. Scale of measurement
  2. Research aims
  3. Experimental design
  4. Properties of dependent/outcome variable
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2
Q

What are the 3 types of research aims?

A
  1. Descriptive only
  2. Relational (correlation)
  3. Experimental (differences)
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3
Q

What type of test do we use for normally distributed data?

A

Parametric

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4
Q

What type of test do we use for not normally distributed data?

A

Non-parametric

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5
Q

What 3 things do we look for in an experiment based on its experimental design?

A
  1. Subjects design (between or within)
  2. Number of independent variables (IVs)
  3. Number of IV levels
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6
Q

What are the 4 types of scales of measurement?

A
  1. Nominal
  2. Ordinal
  3. Interval
  4. Ratio
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7
Q
  1. Nominal
  2. Ordinal
  3. Interval
  4. Ratio

These are…?

A

Scales of measurement

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8
Q

Which scales of measurement are used for categorical data?

A

Nominal

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9
Q

Which scales of measurement are used for discrete or continuous data?

A
  1. Ordinal
  2. Interval
  3. Ratio
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10
Q

What is nominal data?

A

Numbers or names serve as labels but no numerical relationship between values

e.g. gender, political party, religion

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11
Q

Numbers or names serve as labels but no numerical relationship between values

e.g. gender, political party, religion

This is known as…?

A

Nominal data

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12
Q

What is ordinal data?

A

Data is organised by rank

Values represent true numerical relationships but intervals between values may not be equal

e.g. race position, likert scale ratings

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13
Q

What is interval data?

A

True numerical relationships and intervals between values are equal but scale has not true zero point

e.g. temperature (ºF), shoe size

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14
Q

What is ratio data?

A

True numerical relationships, equal intervals and true zero point

e.g. height, distance

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15
Q

Data is organised by rank

Values represent true numerical relationships but intervals between values may not be equal

e.g. race position, likert scale ratings

This is known as…?

A

Ordinal data

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16
Q

True numerical relationships and intervals between values are equal but scale has not true zero point

e.g. temperature (ºF), shoe size

This is known as…?

A

Interval

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17
Q

True numerical relationships, equal intervals and true zero point

e.g. height, distance

This is known as…?

A

Ratio

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18
Q

A study’s research aim is to describe

What descriptive statistics should be used?

A

Summarise a set of sample
values

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19
Q

What research aim does not allow us to make predictions and infer causality?

A

The research aim to describe

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20
Q

What are the 2 statistics used in a study following the research aim of describing?

A
  1. Central tendency
  2. Spread
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21
Q

What are the 3 types of measure of central tendency?

A
  1. Mean
  2. Median
  3. Mode
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22
Q

What are the 2 types of measure of spread?

A
  1. Standard deviation
  2. Range
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23
Q

When do we use the mean as a measure of central tendency?

A

When data is:
- Discrete or continuous
- Normally distributed

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24
Q

When data is:
- Discrete or continuous
- Normally distributed

We use…?

a. Mode
b. Mean
c. Median

A

b. Mean

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25
Q

When do we use the median as a measure of central tendency?

A

When data is:
- Discrete or continuous
- Not normally distributed

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26
Q

When data is:
- Discrete or continuous
- Not normally distributed

We use…?

a. Mode
b. Mean
c. Median

A

c. Median

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27
Q

When do we use the mode as a measure of central tendency?

A

When data is categorical

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28
Q

When do we use standard deviation as a measure of spread?

A

When data is:
- Discrete or continuous
- Normally distributed

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29
Q

When data is:
- Discrete or continuous
- Normally distributed

We use…?

a. Standard deviation
b. Range

A

a. Standard deviation

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30
Q

When do we use range as a measure of spread?

A

When data is:
- Discrete or continuous
- Not normally distributed

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31
Q

When data is:
- Discrete or continuous
- Not normally distributed

We use…?

a. Standard deviation
b. Range

A

b. Range

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32
Q

Relational research explore …?

A

The relationship between observed behaviours or phenomena

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33
Q

True or False?

Relational research actively manipulate variables

A

False

Nothing is actively manipulated in relational research

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34
Q

What type of research aim allows us to make predictions but not infer causality?

A

Relational research

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35
Q

Explores relationship between observed behaviours or phenomena

a. Describe
b. Infer differences
c. Infer relationships

A

c. Infer relationships

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36
Q

Summarise a set of sample
values

a. Describe
b. Infer differences
c. Infer relationships

A

a. Describe

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37
Q

Examines the influence of one or more variables (IVs) on other variables (DVs)

a. Describe
b. Infer differences
c. Infer relationships

A

b. Infer differences

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38
Q

Experimental research examines …?

A

The influence of one or more variables (IVs) on other variables (DVs)

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39
Q

We cannot make predictions or claims of causality

a. Describe
b. Infer differences
c. Infer relationships

A

a. Describe

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40
Q

We can make predictions but not claims of causality

a. Describe
b. Infer differences
c. Infer relationships

A

c. Infer relationships

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41
Q

We can make predictions and claims of causality if confounding variables are controlled for

a. Describe
b. Infer differences
c. Infer relationships

A

b. Infer differences

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42
Q

True or False?

We can always make claims about causality regardless of whether we have controlled for confounding variables

A

False

We can only make claims about causality IF we have controlled for confounding variables

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43
Q

How does experimental research control for confounding variables?

List 2 ways

A
  1. Random allocation (between-subjects)
  2. Counterbalancing (within-subjects)
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44
Q

When is controlling for confounding variables not possible?

A

Quasi-experimental design

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45
Q

What type of research manipulates a small number of variables to measure the effect of the manipulated variables?

a. Descriptive
b. Relational
c. Experimental

A

c. Experimental

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46
Q

What is an IV?

A

Hypothesised to influence the DV

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47
Q

The IV is measured on a ____ scale

a. Categorical
b. Discrete
c. Continuous

A

a. Categorical

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48
Q

What is a DV?

A

Hypothesised to be ‘dependent’ on the IV

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49
Q

The DV is measured on a ____ scale

a. Categorical
b. Discrete
c. Continuous

A

b. Discrete
c. Continuous

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50
Q

Why do we measure the DV under different levels of the IV?

A

To determine the effect of the IV

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51
Q

How do we determine the effect of the IV?

A

We measure the DV under different levels of the IV

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52
Q

List 2 characteristics of true-experimental IVs

A
  1. IVs are actively manipulated
  2. Random allocation is possible (can make claims about causality)
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53
Q

List 2 characteristics of quasi-experimental IVs

A
  1. IV reflects fixed characteristics
  2. Random allocation is not possible (must be cautious about implying causality)
54
Q

IVs are actively manipulated

This applies to…?

a. True experimental IVs
b. Quasi-experimental IVs

A

a. True experimental IVs

55
Q

IV reflects fixed characteristics

This applies to…?

a. True experimental IVs
b. Quasi-experimental IVs

A

b. Quasi-experimental IVs

56
Q

Random allocation is possible (can make claims about causality)

This applies to…?

a. True experimental IVs
b. Quasi-experimental IVs

A

a. True experimental IVs

57
Q

Random allocation is not possible (must be cautious about implying causality)

This applies to…?

a. True experimental IVs
b. Quasi-experimental IVs

A

b. Quasi-experimental IVs

58
Q

Handedness (2 levels: right, left) is an example of a…?

a. True experimental IV
b. Quasi-experimental IV

A

b. Quasi-experimental IV

59
Q

Treatment group (3 levels: placebo, drugs, counselling) is an example of a…?

a. True experimental IV
b. Quasi-experimental IV

A

a. True experimental IV

60
Q

Sport context (2 levels: solo, competitive) is an example of a…?

a. True experimental IV
b. Quasi-experimental IV

A

a. True experimental IV

61
Q

Age (3 levels: 18-20yrs, 20-22yrs, 22-24yrs) is an example of a…?

a. True experimental IV
b. Quasi-experimental IV

A

b. Quasi-experimental IV

62
Q

Distribution of participants across IV levels is known as…?

A

Subjects design

63
Q

What is subjects design?

A

Distribution of participants across IV levels

64
Q

Participants exposed to only one IV level

a. Between-subjects (Independent Groups)

b. Within-subjects (Repeated Measures)

c. Mixed

A

a. Between-subjects (Independent Groups)

65
Q

Participants exposed to all IV levels

a. Between-subjects (Independent Groups)

b. Within-subjects (Repeated Measures)

c. Mixed

A

b. Within-subjects (Repeated Measures)

66
Q

At least one IV is between subjects AND at least one IV is within subjects

a. Between-subjects (Independent Groups)

b. Within-subjects (Repeated Measures)

c. Mixed

A

c. Mixed

67
Q

Intervention vs. control group

a. Between-subjects (Independent Groups)

b. Within-subjects (Repeated Measures)

c. Mixed

A

a. Between-subjects (Independent Groups)

68
Q

Sober vs. drunk

a. Between-subjects (Independent Groups)

b. Within-subjects (Repeated Measures)

c. Mixed

A

b. Within-subjects (Repeated Measures)

69
Q

At the end of Year 1, Year 2 and Year 3 of Uni

a. Between-subjects (Independent Groups)

b. Within-subjects (Repeated Measures)

c. Mixed

A

b. Within-subjects (Repeated Measures)

70
Q

Teachers vs. accountants vs. nurses

a. Between-subjects (Independent Groups)

b. Within-subjects (Repeated Measures)

c. Mixed

A

a. Between-subjects (Independent Groups)

71
Q

An investigator is interested in whether right and left-handed people differ in their performance on different types of computer-games (his theory is that left-handed people will have an advantage on games requiring better visuo-spatial skills). He measures the scores of 30 right handers and 30 left handers who each play Daley Thompson’s Decathlon, Horace Goes Skiing & Tetris

What is the…?

a. IV(s)
b. IV(s) levels
c. DV
d. Subjects design

A

a. Handedness, Games

b. 2 (right and left), 3 (Decathlon, Horace and Tetris)

c. Performance on computer games

d. Mixed

72
Q

What analysis do you perform on an experimental study with 1 IV and 2 levels and participants are exposed to only one IV level?

A

Independent t-test

73
Q

What analysis do you perform on an experimental study with 1 IV and 2 levels and participants are exposed to all IV levels?

A

Paired t-test

74
Q

What analysis do you perform on an experimental study with 1 IV and more than 2 levels and participants are exposed to only one IV level?

A

One-way independent ANOVA

75
Q

What analysis do you perform on an experimental study with 1 IV and more than 2 levels and participants are exposed to all IV levels?

A

One-way repeated measures ANOVA

76
Q

What analysis do you perform on an experimental study with 2 IVs and participants are exposed to only one IV level?

A

Two-way independent ANOVA

77
Q

What analysis do you perform on an experimental study with 2 IVs and participants are exposed to all IV levels?

A

Two-way repeated measures ANOVA

78
Q

What analysis do you perform on an experimental study with 2 IVs and participants are exposed to all IV levels for one IV and only one level for the other IV?

A

Two-way mixed ANOVA

79
Q

What are the properties of normal distribution?

List 2

A
  1. Symmetrical about the mean
  2. Bell shaped (suggests majority of the scores cluster close to the mean)
80
Q

What are the 3 types of kurtosis?

A
  1. Mesokurtic
  2. Platykurtic
  3. Leptokurtic
81
Q

Which kurtosis can we use for parametric statistics?

a. Mesokurtic
b. Platykurtic
c. Leptokurtic

A

a. Mesokurtic

82
Q

Which kurtosis can we use for non parametric statistics?

a. Mesokurtic
b. Platykurtic
c. Leptokurtic

A

b. Platykurtic
c. Leptokurtic

83
Q

Which kurtosis is used when data is normally distributed/bell shaped?

a. Mesokurtic
b. Platykurtic
c. Leptokurtic

A

a. Mesokurtic

84
Q

Which kurtosis is used when data is more varied (the distribution peak is flatter and peak at the mean is lower?

a. Mesokurtic
b. Platykurtic
c. Leptokurtic

A

b. Platykurtic

85
Q

Which kurtosis is used when data is less varied (the distribution peak is higher at the mean and the spread is narrow)?

a. Mesokurtic
b. Platykurtic
c. Leptokurtic

A

c. Leptokurtic

86
Q

Which kurtosis is used when data has a large SD?

a. Mesokurtic
b. Platykurtic
c. Leptokurtic

A

b. Platykurtic

87
Q

Which kurtosis is used when data has a small SD?

a. Mesokurtic
b. Platykurtic
c. Leptokurtic

A

c. Leptokurtic

88
Q

Which kurtosis value is -ve

a. Mesokurtic
b. Platykurtic
c. Leptokurtic

A

b. Platykurtic

89
Q

Which kurtosis value is +ve

a. Mesokurtic
b. Platykurtic
c. Leptokurtic

A

c. Leptokurtic

90
Q

What does data with no skew look like?

A

The tail of a distribution curve is bell shaped

91
Q

What does data with positive skew look like?

A

The tail of a distribution curve is longer on the right side (towards positive values on the x axis)

92
Q

What does data with negative skew look like?

A

The tail of a distribution curve is longer on the left side (towards negative values on the x axis)

93
Q

What is bimodal data?

A

Data with 2 modes

94
Q

What is uniform data?

A

Looks like categorical data lined up instead of a curve

95
Q

True or False?

Bimodal and uniform data are normally distributed

A

False

They are not normally distributed

96
Q

We use sample statistics to infer …?

A

Population parameters

97
Q

True or False?

We use population parameters to infer sample statistics

A

False

We use sample statistics to infer population parameters

98
Q

What is Sampling Error?

A

The degree to which sample statistics differ from underlying population parameters

99
Q

The degree to which sample statistics differ from underlying population parameters

This is known as…?

A

Sampling error

100
Q

What are the 2 ways we can minimise error?

A

Sample size must be:

  1. Representative (randomly selected)
  2. Sufficient in size
101
Q

Scores from a normally
distributed population can be converted to z -scores

What is the z-score formula?

A

z = (x - pop. mean) / sample mean

102
Q

Percentage of scores within single standard deviation boundaries

This is known as…?

A

Standard Normal Distribution

103
Q

What is Standard Normal Distribution?

A

Percentage of scores within single standard deviation boundaries

104
Q

What is sampling distribution?

A

Distribution of a statistic
across an infinite number of samples (e.g. sampling distribution of the mean)

105
Q

Distribution of a statistic
across an infinite number of samples (e.g. sampling distribution of the mean)

This is known as…?

A

Sampling distribution

106
Q

Plotting all possible sample means gives us the …?

A

Sampling distribution of the mean

107
Q

Plotting all possible sample means gives us the sampling
distribution of the mean

Its mean is equivalent
to the …?

A

Population mean

108
Q

Plotting all possible sample means gives us the sampling
distribution of the mean

Its standard deviation
is given a special name …?

A

The standard error

109
Q

The standard deviation
of the sampling distribution is known as..?

A

The standard error

110
Q

What is the standard error?

A

The standard deviation
of the sampling distribution

111
Q

As sample size increases, the standard error …?

A

Decreases

112
Q

The standard error decreases as sample size
increases

What does this suggest?

A

Sampling error decreases as sample size increases

113
Q

An estimate of the standard error, based on our sample

This is known as…?

A

Estimated standard error

114
Q

What is ESE?

A

An estimate of the standard error, based on our sample

115
Q

What is the formula for ESE?

A

ESE = SD / sqrt sample size

116
Q

What are the 3 characteristics of sampling distribution of the mean?

A
  1. Mean equivalent to the
    population mean
  2. Standard deviation is the
    ‘standard error’
  3. Always normally distributed
117
Q

True or False?

5% of all sampled
means will fall within ±1.96
standard errors of the
population mean

A

False

95% of all sampled
means will fall within ±1.96
standard errors of the
population mean

118
Q

What are CIs?

A

Interval estimates of population parameters

119
Q

Interval estimates of population parameters

This is known as…?

A

CI

120
Q

We use 95% CI in psychology

What does this suggest?

A

We are declaring that there is still a chance that our
estimates are wrong

There’s a 5% chance that the population mean falls above/below the 95% CI limits

121
Q

If there’s a 95% chance that the sample mean falls within the 95% bounds of the population mean, it follows that…?

A

There’s a 95% chance that the population mean falls within the 95% CIs of the sample mean

122
Q

Is this H1 or H0?

There is no difference
between the population means

A

H0

123
Q

The probability of measuring a difference of that magnitude if the null hypothesis is true

This is known as…?

A

p value

124
Q

What is a p value?

A

The probability of measuring a difference of that magnitude if the null hypothesis is true

125
Q

Threshold level of probability where we will be willing to reject the null hypothesis

This is known as…?

A

alpha value

126
Q

What is alpha value?

A

The threshold level of probability where we will be willing to reject the null hypothesis

127
Q

If p < 0.5 ____ the hull hypothesis

A

Reject

128
Q

What is type 1 error?

A

When H0 is true but you reject it

129
Q

What is type 2 error?

A

When H0 is false but you fail to reject it

130
Q

When H0 is true but you reject it

Is this…?

a. Type 2 error
b. Type 1 error

A

b. Type 1 error

131
Q

When H0 is false but you fail to reject it

Is this…?

a. Type 2 error
b. Type 1 error

A

a. Type 2 error

YEAR 2 Stats (10 decks)

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