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Epa Test > Semester 1 > Flashcards

Semester 1 Flashcards

1
Q

A variable manipulated by a researcher is known as?

A

An independent variable

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2
Q

A variable that measures the effect that manipulating another variable has is known as?

A

Dependent variable

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3
Q

Variance is?

A

An estimate of average variability (spread) of a set of data

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4
Q

A confounding variable is?

A

A variable that affects the outcome being measured as well as, or instead of, the dependent variable

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5
Q

Six people walk in a room. There are 6 chairs. How many degrees of freedom in chair choice are there in this situation?

A

5

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6
Q

The mean is?

A

The sum of all scores divided by the number of scores, the value from which scores deviate least, and a hypothetical value that doesn’t have to be a value in the data set

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7
Q

What does a z-score indicate?

A

A z-score indicates the number of standard deviations a score is from the mean

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8
Q

What is partial eta squared a measure of?

A

Effect size

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9
Q

For a normal distributed set of data…

A

The distribution is symmetrical about the mean, the values for the mean, mode and median are the same, there are scores both above and below 2 standard deviations, approximately 68% of scores fall within +/-1 standard deviations

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10
Q

Bars being highest on the left hand side is said to be…

A

Positively skewed

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11
Q

A frequency distribution in which there are too many scores at the extremes of the distribution are said to be?

A

Platykurtic

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12
Q

What is the standard error a measure of?

A

The variability of sample estimates of a parameter

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13
Q

What is the relationship between sample size and the standard error of the mean?

A

The standard error decreases as the sample size increases

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14
Q

What is true about the 95% confidence interval of the mean?

A

95/100 confidence intervals will contain the population mean

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15
Q

What does probability show?

A

P is the probability of observing a test statistic at least as big as the one we have if there were no effect in the population (I.e the null hypothesis were true)

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16
Q

A type I error occurs when?

A

We conclude that there is an effect in the population when in fact there is not (false positive)

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17
Q

A type II error occurs when?

A

We conclude that there is not an effect in the population when in fact there is (false negative)

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18
Q

What does a bonferroni correction do?

A

Corrects for family wise error

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19
Q

How many independent and dependent variables are there in a one-way repeated measures ANOVA?

A

Only 1 independent variable and only 1 dependent variable

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20
Q

How many dependent variables must you have for an ANOVA to be conducted?

A

Only one at interval or higher

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21
Q

How many levels must there be in one independent variable for an ANOVA to be used?

A

3 or more levels

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22
Q

What do unplanned comparisons do?

A

Test every possibility and compare each condition to each other

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23
Q

Mauchly’s test does what?

A

Indicates whether there is a significant difference between the variance of the conditions in a repeated measures ANOVA

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24
Q

What do tests of significance such as ANOVA’s look at?

A

The probability that the samples are from the same population

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25
Q

What is the cut off point for small effect size (partial eta squared)

A

0.01

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26
Q

What is the cut off point for medium effect size?

A

0.06

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27
Q

What is the cut off point for large effect size?

A

0.14

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28
Q

When looking at degrees of freedom, what 2 columns do you look at?

A

Corrected model and error

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29
Q

What does it mean it the levenes test is non-significant?

A

The assumption of homogeneity of variance has not been violated - significant = significant problem

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30
Q

If we are being alpha level of .05 we judge a test to be significant is the p value is?

A

Less than .05

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31
Q

If you carry out a Krystal-Wallis test and your results are significant what post-hoc test would you run?

A

Mann-Whitney test

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32
Q

If you carry out a Friendman’s test and your results are significant what post-hoc test would you run?

A

Wilcoxon test

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33
Q

You have 4 groups and each group drinks one of four different caffeine drinks. How many post-hoc pair wise companions will you need to make?

A

6

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34
Q

With your 6 post-hocs, what will the new alpha level be?

A

0.05/6 =0.00833

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35
Q

What is the effect size for a Wilcoxon test?

A

A statistic divided by the square root of the number of observations

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36
Q

You carry out a study to see the effect of 3 different types of energy drink on runners’ performance. You stage a race and give each runner one of the 3 drinks. At the end of the race, for each runner, you record which drink the runner frank and the position they finished in. Which test would be suitable to use on your results?

A

One-way independent ANOVA

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37
Q

What is the non-parametric alternative to the one-way between-subjects ANOVA?

A

Kruskal-Wallis test

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38
Q

What is the Kruskal-Wallis test used to compare?

A

More than 2 independent groups

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39
Q

What test would you use for repeated measures instead of one-way ANOVA?

A

Friedmans test

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40
Q

In the Kruskal-Wallis test, the test statistic is based on what?

A

Ranks of groups

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41
Q

In Friedman’s test, the test statistic is based on what?

A

Sum of ranks

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42
Q

What is the primary use of a two-way repeated measures ANOVA

A

To assess the impact of 2 independent variables on a single dependent variable with repeated measures

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43
Q

In a two-way repeated measures ANOVA, what does the interaction effect test?

A

Whether the effect of one independent variable on the dependent variable depends on the level of the other independent variable

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44
Q

What is a key assumption of a two-way repeated measures ANOVA?

A

There must be sphericity for both independent variables

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45
Q

If a significant interaction effect is found in a two-way ANOVA, what is a suitable next step?

A

Conduct post hoc tests to explore the interaction further

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46
Q

In a two-way repeated measures ANOVA, what would a significant main effect for one of the independent variables indicate?

A

That the dependent variable is significantly different across the levels of that independent variable, regardless of the other independent variable

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47
Q

What is the purpose of the bonferroni correction in statistical hypothesis testing?

A

It adjusts the significance threshold to control the overall probability of making type I errors when performing multiple tests

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48
Q

What is the key difference between planned comparisons and post hoc tests after finding a significant interaction in a two-way ANOVA?

A

Planned comparisons focus on specific hypotheses set before the study, while post hoc tests explore all possible comparisons after the data has been analysed

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49
Q

When would it be appropriate to use post hoc tests rather than planned comparisons following a significant interaction in a two-way ANOVA?

A

When you have no specific hypotheses in mind and want to explore all possible pairwise comparisons

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50
Q

In a psychological study examining the effects of different modalities of therapy, and treatment duration on anxiety reduction, each participant undergoes both types of therapy and is assessed at both time points. Which statistical test would be most appropriate to analyse the data?

A

Two-way repeated measures ANOVA

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51
Q

After an ANOVA you need more analysis to find out which groups differ. When you did not generate specific hypothesis before the experiment, what should you use?

A

Post-hoc tests

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52
Q

When the between-groups variance is a lot larger than the within-groups variance, the F-value is… and the likelihood of such a result occurring because the sampling error is …?

A

Large; low

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53
Q

What is the overall effect of an independent variable on a dependent variable known as?

A

Main effect

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54
Q

The results of a two-way repeated measures ANOVA with three levels on each independent variable revealed a significant value for Maichly’s test of p=.048. What does this mean?

A

The assumption of sphericity has been violated

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55
Q

When you have data that violates the assumption of sphericity what should you do?

A

Use a greenhouse-geisser or huynh-feldt correction

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56
Q

What is statistical power in hypothesis testing?

A

The probability of correctly rejecting the null hypothesis when it is false

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57
Q

What generally increases statistical power?

A

Increasing the sample size

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58
Q

What does a priori power analysis help researchers determine?

A

The size of the sample needed to detect an effect

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59
Q

What is the relationship between effect size and statistical power?

A

Generally, as effect size increases, statistical power increases

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60
Q

What is a core principle of open science?

A

Sharing data, materials and methods publicly

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61
Q

What platform is commonly used for open science to share research data and materials?

A

Open science framework (OSF)

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62
Q

What does the replication crisis refer to in psychology research?

A

The inability to reproduce the results of published studies

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63
Q

What is meant by reproducibility in the context of scientific research?

A

Repeating a study using the same data and methods

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64
Q

What is one reason for the replication crisis in psychology?

A

Publication bias towards positive findings

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65
Q

Which practice can help improve the reproducibility of research in psychology?

A

Sharing data and analysis scripts openly, using the open science framework

66
Q

What are the first 3 steps into research?

A
  1. Research question
  2. Generate theory
  3. Generate hypothesis
67
Q

What is a sample?

A

A smaller collection of units from a population used to make inferences about that population

68
Q

What is a population?

A

The collection of units to which we want to generalise a set of findings or a statistical model

69
Q

What is a deviation?

A

The difference between the mean and an actual data point

70
Q

How can deviations be calculated?

A

By taking each score and subtracting the mean from it
Score - mean

71
Q

What is the standard deviation from the mean that 68% of people would fall in?

A

+/-1

72
Q

What is the standard deviation that 95% of data would fall in?

A

+/-1.96

73
Q

What is the standard deviation that 99.7% of data would fall into?

A

+/-3

74
Q

What do z scores allow?

A

To test a score relative to the population as a whole

75
Q

How to calculate z score?

A

Z=your score - mean score / standard deviation

76
Q

What is a confidence interval?

A

The boundaries in which we think the true mean of the population lies

77
Q

What 2 factors do the results of T-tests depend on?

A
  1. The size of the difference between the means
  2. The variability in the data
78
Q

How is T calculated?

A

Difference in mean / standard error

79
Q

When do you reject the null hypothesis?

A

When the probability of the result occurring is less than .05

80
Q

What is a type I error?

A

Occurs when we believe there is a genuine effect in our population when there isn’t - the probability is the a-level (usually .05)

81
Q

What is a type II error?

A

Occurs when we believe there is no effect in the population when there is - probability is the b-level (often .2)

82
Q

Why is a p-value not enough?

A

They are tied to sample size and are not standardised

83
Q

What is effect size?

A

Standardised measure of the size of an effect

84
Q

What does standardised mean?

A

Comparable across studies

85
Q

What can you do when there are outliers?

A

Calculate Z-scores for your variables and remove the ones above +/-2
OR
switch to parametric test

86
Q

What is standard error?

A

How widely spread the sample means are spread around the population

87
Q

Is a small standard error a more accurate or less accurate representation?

A

More accurate

88
Q

How many IVs for a one way ANOVA?

A

1

89
Q

What do tests of significance look at?

A

Look at the probability that the samples are from the same population - 1= absolute certainty that samples come from the same population

90
Q

If the probability is less than .05 what can we assume?

A

The means are probably from different populations - effect is unlikely to be due to chance

91
Q

Why don’t we run lots of t-tests?

A

Increases the likelihood of making a Type I error

92
Q

What do ANOVAS test?

A

The relationship between the means for 3 or more levels of the mean

93
Q

What is family wise error?

A

Conducting loads of t-tests which increases the likelihood of making a type I error

94
Q

What are the assumptions of ANOVA?

A
  1. DV is interval / ratio
  2. Sample is normally distributed
  3. Homogeneity of variance not violated
95
Q

What does ANOVA not do?

A

Provide specific information about which groups were affected

96
Q

When do you conduct planned comparisons or post-hoc tests?

A

When the ANOVA results are significant

97
Q

What do ANOVAS compare?

A

The amount of variance explained by our experimental manipulation (effect) with the variance that is unexplained (error)

98
Q

ANOVA test statistic =?

A

Effect / model

99
Q

For a significant effect in ANOVAS what would we expect?

A

The within group variance to be small compared to the between group variance

100
Q

Unsystematic variation is?

A

Random factors such as individual differences affecting score

101
Q

F =?

A

Between group variance / within group variance

102
Q

What does a levenes test aim to measure?

A

Are the variances significantly different

103
Q

What happens for between groups design of the assumptions of homogeneity (levenes) is violated?

A

Non-parametric t test should be conducted instead of between ANOVA

104
Q

What happens if mauchlys test of homogeneity is violated?

A

Greenhouse Geisser or Huynh-Feldt correction can be made

105
Q

How do you know whether to use a greenhouse-geisser or huynh-feldt correction?

A

If greenhouse geisser statistic is less than .75, we make a greenhouse geisser correction, if it is bigger than .75, make a huynh-feldt correction

106
Q

What jamovi column do you use if you make no sphericity correction?

A

Column named ‘none’

107
Q

What are planned comparisons?

A

Comparisons that test a pre-predicted hypothesis

108
Q

What are post-hocs?

A

Test comparisons that you decide after seeing your data

109
Q

What are post-hocs designed to do?

A

Pairwise comparisons that are designed to explore data for any between-condition differences

110
Q

How to do a bonferroni correction?

A

.05/ number of comparisons

111
Q

What do you do if you have a one-way between groups ANOVA with non-parametric data?

A

Kruskal-Wallis

112
Q

What do you do if you have a one way within group ANOVA with non-parametric data?

A

Friedman’s test

113
Q

What is the F-value?

A

Ratio of variance within each condition compared to the random variance across each condition

114
Q

What is degrees of freedom?

A

The number of independent pieces of information

115
Q

How do you calculate Df1 for between subjects design?

A

K(number of levels) - 1

116
Q

How do you calculate Df2 for between subject design?

A

N (total number of datapoints) - K (number of levels)

117
Q

How do you calculate Df1 for within subject design?

A

K (number of levels) - 1

118
Q

How do you calculate Df2 in within subject design?

A

(N(total number of observations) - 1) - (N(number of participants) - 1) - (K (number of levels) - 1)

E.g IV with 3 levels, 19 participants, 57 observations
DF2 = 56-18-2 =36

119
Q

What is the ANOVA assumption about the DV data?

A

Must be on interval or ratio scale

120
Q

If you get a significant Friedman’s test, what post hoc would you use?

A

Wilcoxon test with a bonferroni correction

121
Q

What post hoc test should you use for a between groups design that has non-parametric data?

A

Mann-Whitney U with a bonferroni correction

122
Q

What is an interaction?

A

When the effect of 1 IV changes across the different levels of the other IV

123
Q

How do you find zskew and zkurtosis?

A

Divide skew by standard error skew and divide kurtosis by standard error kurtosis

124
Q

What are planned comparisons also know as in the context of ANOVAS?

A

Simple effects analysis

125
Q

What is a mixed design?

A

One IV is between (independent) groups and one IV is within (repeated) groups

126
Q

What is a main effect?

A

The effect of one of your independent variables on the dependent variable, ignoring the effects of all other independent variables

127
Q

How do you transform positively skewed data?

A

Square root all of the values - brings larger values closer to the centre so reduced positive skew

128
Q

How do you transform negatively skewed data?

A

(Largest value + 1) - original value and then square root it

129
Q

What effect size symbol (n2 or n2p) do you use when reporting the main effect of the between groups IV

A

N2

130
Q

What effect size symbol do you use when reporting the main effect of the within groups IV?

A

N2p

131
Q

When are you only interested in planned comparisons?

A

If you have a significant interaction

132
Q

Why do you need to make bonferroni corrections?

A

To reduce the chance of inflated type I errors

133
Q

When does the focus narrow in a report?

A

Introduction

134
Q

What is the purpose of an abstract?

A

Form a concise and clear summary of the entire report

135
Q

What is the purpose of the introduction?

A

Must establish context, identify research problem/gap, explain rationale, and include predictions

136
Q

What is the purpose of method?

A

Describes to the reader how the study was conducted

137
Q

The method, what goes where? (Who, what, which, how)

A

Participants - who
Method - what
Materials - which
Procedure - how

138
Q

What is the purpose of the results?

A

Convey info in and understandable manner

139
Q

What is the purpose of the discussion?

A

To recap the results, but in a way that’s easily understandable to a naive reader

140
Q

What are the 4 paras in a discussion?

A

1 - recap results
2 - talk about the same topics as intro and add some more literature + unexpected results
3 - limitations and future directions
4 - conclusion

141
Q

What are low power studies more subject to?

A

Have poor reliability, more subject to other bias

142
Q

Effect sizes provide what?

A

Standardised index of effect based on standard deviation

143
Q

Effect size - options for different tests?

A

T-test - cohen’s d
Mann-Whitney U - r=z/square root of n (number of cases)
Correlation = r
Chi squared - offs ratio or relative risk

144
Q

What is small effect size for cohen?

A

0.2

145
Q

What is medium effect size for cohen d ?

A

0.5

146
Q

What is large effect size for cohen d?

A

0.8

147
Q

How is Cohens d calculated?

A

Group A mean - group B mean / pooled standard deviation

148
Q

What is effect size for Mann Whitney, chi-squared & correlation?

A

Small = 0.1
Medium = 0.3
Large = 0.5

149
Q

What is less powerful, non-parametric or parametric?

A

Non-parametric

150
Q

What is a priori power analysis?

A

Conducted prior to the conducting of research and is used to determine an appropriate sample size to achieve adequate power to detect an error

151
Q

What number to aim for for power?

A

Usually .80 or more for power

152
Q

To minimise type I or II error, what do you need to maintain balance between?

A

Power, sample size and alpha

153
Q

If a score in a data set has a z-score of 0 what does this mean?

A

The score has a value equal to the mean of that data

154
Q

what is explained variance?

A

Variance between groups - how much the scores vary between the groups

155
Q

what is unexplained variance?

A

Variance within a group - how much the scores vary within each group - also known as error

156
Q

How is the lower bound for 95% CI calculated?

A

Mean - (1.96x Standard error mean)

157
Q

How is the upper bound for 95% CI calculated?

A

Mean + (1.96xstandard error mean)

158
Q

What is sampling error?

A

The discrepancy or amount of error between a sample statistic and its corresponding population parameter

159
Q

What is sampling distribution?

A

A distribution of statistics obtained by selecting all possible samples of a specific size from a population

160
Q

Standard error is?

A

The standard deviation for the distribution of sample means

Epa Test (1 decks)

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