Quiz
Research Methods
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Questions in this quiz (44)
1What is the key feature of a quasi-experimental design?
- AParticipants are volunteers
- BParticipants are not randomly allocated
- CParticipants are measured pre and post treatment
- DParticipants are not measured at baseline
2Which is not a type of quasi-experimental design?
- AOne group pre-test post-test
- BStatic Group Comparison
- CPost-test only
- DPre-test post-test non-equivalent groups design
3If we were conducting an experiment to compare two methods of teaching someone how to drive, we would have a baseline measure and a follow-up measure (pre-test post-test design).
- ATrue
- BFalse
4When we are expressing cells in factorial designs, we specify the number of levels on the IV
- ATrue
- BFalse
5In an experiment that has 2 independent variables with 3 levels each, how would we express the number of levels of each IV? [blank_start]2 x 3 x 2[blank_end]
- A2 x 3 x 2
6To find out how many cells a factorial design has, we [blank_start]multiply[blank_end] the number of levels of each IV together. So a study with 2 IV's with 3 levels each, has [blank_start]12[blank_end] cells.
- Amultiply
- B12
7When each participant participates in all levels of the IV, this is called a between subjects design
- ATrue
- BFalse
8When would we use a t-test?
- AWhen there is 2 IVs with 1 level
- BWhen there is 3 IVs with 2 levels
- CWhen there is 1 IV with 3 levels
- DWhen there is 1 IV with 2 levels
9An interaction is where the effect of 1 IV differs in [blank_start]size[blank_end] or [blank_start]direction[blank_end] depending on another IV
- Asize
- Bdirection
10What elements are required to be discussed when reporting the ANOVA results?
- ADescribe the test
- BDescribe the main effects (significance, effect size and SDs
- CReport the interaction (significance, effect size and cell means)
- DDiscuss the number of participants
11Variability is made up of errors of measurement and the IV
- ATrue
- BFalse
12Error of measurement is a type of [blank_start]random[blank_end] difference
- Arandom
13To calculate the random individual differences in an experiment, you would measure the variance [blank_start]within[blank_end] groups
- Awithin
14In an experiment, if the treatment (IV) had an effect, we would expect that:
- AThe between-groups variance is greater than the within-groups variance
- BThe between-groups variance is equal to the within-groups variance
- CThe between-groups variance is less than the within-groups variance
15When both the IV and the DV are categorical, which test would we use?
- At-test
- BCorrelation
- CFactorial ANOVA
- DPearson chi-square
- EOneway ANOVA
16Which is not an example of a NONparametric test for a categorical IV and a continuous DV?
- AMann-Whitney
- BFriedman Test
- CWilcoxon signed rank test
- DHierarchical Regression
17The effect size can tell us if a real effect has occurred in our results
- ATrue
- BFalse
18Error bars are used in figures to represent condition means. Difference between means is significant if:
- ANo more than half of the whole bar overlap
- BNo more than three quarters of the whole bar overlap
- CNo more than one quarter of one side of the bar overlap
- DNo more than one quarter of the whole bar overlap
19For proportions of variance explained for ANOVAs, partial eta squared considers unexplained variability and any extra variability from the effect of the IV
- ATrue
- BFalse
20For regressions, the index of variance is [blank_start]R[blank_end] squared or [blank_start]R[blank_end] squared [blank_start]change[blank_end]
- AR
- BR
- Cchange
21When we are testing the significance of the difference between means, the tests we could use are [blank_start]t-test[blank_end] or [blank_start]ANOVAs[blank_end] but if we are interested in the significance of a linear relationship between continuous variables, we could use [blank_start]regression[blank_end] or [blank_start]correlation[blank_end]
- At-test
- BANOVAs
- Cregression
- Dcorrelation
22The two assumptions of parametric inferential statistic tests are:
- AEach group of participants have similar numbers
- BAll scores will be linear
- CScores on continuous variables are normally distributed
- DVariability in scores will be similar for different conditions
- EEach participant has an equal chance of being in each group
23Inferential statistics can not tell us about the size, importance or direction of an effect
- ATrue
- BFalse
24p is the probability that the observed effect could have arisen by chance if there really is no effect
- ATrue
- BFalse
25When regression towards the mean occurs, why do extreme scores move closer to the mean?
- AThere little room on the measure to move further away
- BAll scores tend to change over time
- CExtreme scores might have occurred because of an unusual event
- DAnother event has affected everyones scores
26Which is not a type of measurement validity?
- AInter-rater reliability
- BTest-retest reliability
- CInternal reliability
- DConcurrent reliability
27Measurement validity is essentially how accurate the measure is at [blank_start]measuring[blank_end] the [blank_start]construct[blank_end] of interest
- Ameasuring
- Bconstruct
28Which type of measurement validity is how well a measure represents every single element of a construct
- AConcurrent validity
- BPredictive validity
- CFace validity
- Ddiscriminant validity
- EContent validity
29A moderator is something that changes the [blank_start]relationship[blank_end] between the IV and the [blank_start]DV[blank_end]. So a moderation hypothesis is when the IV and the moderator [blank_start]interact.[blank_end]
- Arelationship
- BDV
- Cinteract.
30To test whether a moderation hypothesis was supported we want to know:
- AThe significance of the interaction
- BThe size of the interaction
- CThe pattern of cells means
- DThe direction of the interaction
31When is moderation relevant in the following examples
- ABirthmarks, speed of processing and cancer
- BGrades and studying
- CDriving lessons and reaction time
- DExercise ,diet and weight loss
32In questionnaires, assessing [blank_start]agreement[blank_end] using anchors with disagree and agree at the end are called [blank_start]likert[blank_end] scales
- Alikert
- Bagreement
33[blank_start]Socially[blank_end] [blank_start]desirable[blank_end] [blank_start]response[blank_end] bias is when we respond in a way that makes a good impression
- ASocially
- Bdesirable
- Cresponse
34How would we test if someone was overclaiming in a questionnaire?
- AAsk people to take a questionnaire anonymously
- BAsk people about something they have achieved when they were younger
- CAsk someone about the olympics they competed in but they really didn't
- DAsk about the new president of Peru and his campaigns about racial democracy, which is fictitious
35Unclear questions and imprecision of ordinal scales can lead to differences in interpretation and decreases validity
- ATrue
- BFalse
36Questions that ask two seperate questions in the same statement, but only have one set of answers is called a what? [blank_start]Double[blank_end] [blank_start]barrelled[blank_end] [blank_start]question[blank_end]
- ADouble
- Bbarrelled
- Cquestion
37When a participant did not hold a particular opinion but after reading a question, has now formed an opinion - what has happened here?
- AOverc-laiming
- BSuggestibility
- CGeneralising
- DSocial desirable response bias
- EDouble barrelled question
38When we have a continuous IV AND a continuous DV - what type of test would we use?
- AChi square
- BANOVA
- Ct-test
- DRegression
- EOne way ANOVA
39When we use a simple regression IVs are entered at the [blank_start]same[blank_end] time in a [blank_start]one[blank_end] step regression, whereas in a [blank_start]hierarchical[blank_end] regression predictors are entered in a [blank_start]series[blank_end] of steps.
- Asame
- Bone
- Cseries
- Dhierarchical
40We would use a hierarchical regression when we want to find out if a predictor (IV) still explains significant variance after controlling for another predictor
- ATrue
- BFalse
41When would we use a simple regression AND a hierarchical regression? To answer whether a particular variable [blank_start]mediates[blank_end] the relationship between the [blank_start]IV[blank_end] and the DV
- Amediates
- BIV
42Which is NOT a step in testing a mediation hypothesis using hierarchical regression
- ATest preconditions
- BHierarchical multiple regression
- CUse a simple regression to test the effect of the IV on the DV
- DControl for the DV by entering it in step 1 of the hierarchical regression
43When a variable changes the direction or strength of the effect of the main variable on the DV, this is called a mediator
- ATrue
- BFalse
44When looking at the predicted change in DV for each increase on the IV - which coefficient measures the predicted change in original measurement units?
- Ab
- Bf
- Cbeta
- Dphi
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- Quiz on Research Methods, created by Eliza Sheridan on 04/11/2017.
- Author
- Eliza Sheridan
- Language
- English
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