Research Methods 3 - shorter Flashcards
What is chronbach’s alpha and what does it assess?
what score on cronbach’s alpha is acceptable?
the average correlation among all possible pairs of items. (easily calculated [by a computer] and reported) Cronbach’s alpha can range from 0-1. SPSS will calculate it and can also indicate the change in Cronbach’s if any particular item were omitter. Good (i.e., acceptable, though not outstanting reliability = .80*. the higher the better)
internal reliability
What do 95% confidence interavals show/mean/represent?
they define the range of values within which the true mean is likely to lie on 95% of occasions.
95% CI indicate
- error of measurement (in estimation of population mean)
- whether means are likely to differ significantly
if the confidence interval bars for two means overlap by more than 1/4 is the difference between means likely to be significant or non-significant?
Non-significant
What is significance?
The significance level or ‘p’ is the probability that an observed effect arose by chance if there really is no effect.
What are the three types of descriptive statistics and when are they used?
- Mean (M), median & mode - tell us typical score on a continuious measure for comparing means between conditions.
- Percentages or proportions of cases that fall into particular categories (or frequencies) - compare between catefories with different no. of cases.
- Correlation coefficients (r) and regression coefficients (B and beta) - describe the nature of a linear relationship between continuous variables. direction and strength. Bs tell us about the effect in the original scales of the measurement. Betas can indicate the relative strength of different predictors.
parametric tests assume that…….?
- scores on continuous variables (that are used in the analysis) are normally distibuted
- the variability (or variance) in scores in similar for different conditions (there are tests available to assess this, including in SPSS
if these assumptions are violated, then the outcome of parametric test can be misleading. If the data do deviate markedly from these assumptions, we could use a nonparametric test.
What are the broad classes/types of parametric tests?
- tests that assess the signifiance of the difference between means (t-test and ANOVAs)
- Tests that assess the significance of the linear relationship between continuous variables (correlations and regressions)
What are the assumptions of an ANOVA/t-test?
- Scores on the DV are (roughly) normally distributed) i.e., bell curve)
- Variance or variability is (roughly) similar for the different conditions(the assumption of ‘homogeneity of variance’)
In order to meet the homogeneity of variance assumption (i.e. in ANOVA) the levene’s test should be _____________?
Non-significant
In what situations does heterogeneity of variance(different levels of variance between conditions) pose a greater threat to the validity of the statistical outcome?
- the n per condition is small
- the Ns per condition are markedly different
- the direction of skewness varies between conditions
- Heterogeneity of variance and non-normality coexist.
What is the appropriate parametric test to assess the difference between means where the IV is varied between subjects and there is one IV with 2 levels?
Independent groups t-test (or one-way ANOVA)
What is the appropriate parametric test to assess the difference between means where the IV is varied between subjects and there is one IV with 3 levels?
Oneway ANOVA
What is the appropriate parametric test to assess the difference between means where the IV is varied within subjects and there is one IV with 2 levels?
Paired samples t-test
What is the appropriate parametric test to assess the difference between means where the IV is varied within subjects and there is one IV with 3+ levels?
Oneway repeated measures ANOVA
What is the appropriate parametric test to assess the difference between means where the IV is varied between subjects and there are 2 IVs with 2+ levels on each?
Factorial ANOVA (2-way, 3-way etc)
What is the appropriate parametric test to assess the difference between means where the IV is varied within subjects and there are 2 IVs with 2+ levels on each?
Repeated measures ANOVA
What is the appropriate parametric test to assess the difference between means where the IV is varied both between and within subjects (i.e., mixed design) and there are 2 IVs with 2+ levels on each?
mixed ANOVA (split plot ANOVA)
What is a moderator?
The moderator is the variable (another IV) that affects the primary IV-DV relationship in which we’re interested. In other words, the moderatory affects the relationshop between the key IV and the DV. We say that two IVs interact. We could just as correctly say that the IV and the moderator interact.
(Moderation is closely related to interaction, however it’s a more theorestical idea in that it reflects our focus in posing and answering a research question)
What is an Interaction?
The term interaction indicates that the effect of one IV varies, depending on another IV. It applies when we expect that the size and or direction* of the effect of one IV will differ depending on the other IV. A difference in *size* means that an IV has a larger effect at one level of the 2nd IV than at the other level. A difference in *direction means that an IV has opposite effects at the 2 levels of a 2nd IV. An interaction can be a conceptial proposition, but we also test the statistical significance of interactions.
The following hypotheses is suggestive one what kind of relationship between IVs?:
It was predicted that information type and coping style would interact in their effects on pre-operative anxity. Specifically, it was expected that, for people with a problem-focused style, detailed infroamtion would result in lower anxiety than would routine information. In contrast for those who use avoidant coping, it was expected that routine information would result in lower anxiety than would detailed information.
an INTERACTION
What two types of effects do factorial ANOVAS (2+ IVs) test?
- Main effects of each IV
- Interaction between the IVs. e.g., whether the difference in the mean anxiety between detailed and routine information itself differs between problem-focused people and avoidant people. That is, does the difference between detailed and routine vary between the coping styles? or, in other words, is detailed minus routine different for problem focused people than it is for avoidant people?
What is a main effect?
A test of one IV at a time
A main effect refers to the overall effect of one IV, completely ignoring the other IV.
For example, the test of the main effect of coping style indicates the significance of the overall difference between problem-focused and avoidant participants, collapsed or averaged across levels of information type. That is, all of the problem-focused participants are compared with all of the avoidant participants (regardless of the type of information that thye received). Ps are distinguished only according to their coping style. When an interaction is significant, main effects are sometimes of limited interest because they don’t tell the whole story. We report them, but the interaction would be a central result.
What is moderation?
Moderation is closely related to interaction (moderation is only demonstrated if an interaction exists). However, it’s a more theorestical idea in that it reflects our focus in posing and answering a research question.
An interaction indicates that the relationship between an IV and the DV varied depending on another variable. That other variable is often referred to as the moderator.
So the MODERATOR is the variable (another IV) that affects the primy IV-DV relationship in which we’re interested, In other words, the moderator affects the relationship between the key IV and the DV. We say that two IVs interact. We could just as correctly say that the IV and the moderator interact.
There are two advertisments for mobile phones, one is ‘transformers’ and one is ‘connecting people’, the phone company wants to know which one is the better ad.
You might think that the preferred advertisement will vary depending on the gender of the teenager.
If you do think this, then you are predicting an interaction between type of advertisement and sex of teenager or in other words that….
Sex of teenager _______*fill blank* the effect of type of advertisement.
Moderates
Which of the following is not a potential threat to the internal validity of a quasi-experiement?
A. Instrumentation B. Generalisability C. History D. Selection E. Maturation
B. Generalisability (because this concerns external validity!)
- A threat to internal validity of a static group comparison (non-equivalent control group) design is:
A. Selection B. Instrumentation C. Testing D. Regression toward the mean E. Response bias
Also, describe a static group comparison design.
A. selection
Group 1 X O
Group 2 O (control)
why not the others?:
B. Instrumentation - no reason to think this
C. Testing - no repeated measures
D. Regression toward the mean - repeated measures only
E. response bias - no idea about this and why would it differ
Research has ________ validity when the measures provide a very good index of the phenomena that are being studied
A. Internal B. External C. Construct D. Discriminant E. None of the above
C. Construct
A correlation of .3 between anger and aggressive behaviour:
A. Indicates that anger causes agression
B. Indicates that anger explains 9% of the variance in aggressive behaviour
C. Indicates that reducing anger will reduce aggressive behaviour
D. Shows that anger and aggression are strongly related. Although we can’t be sure of the causal direction
E. Shows that another variable is responsible for the ange-aggression relationship
B. Indicates that anger explains 9% of the variance in aggressive behaviour
For samples of a given size, external validity is promoted by
A. Non-probability samples
B. volunteer samples
C. Random samples
D. Quota samples
E. Samples of convienience
C. Random samples
Consider these questions
Q1 “How close is your relationship with your mother?” - Very close, quite close, not close, quite distant, very distant
Q2 “What was the $ value of your last telephone bill?” _______
Q3 “Australia should remain a monarchy because this is the only way to ensure that the political power of the government is held in check to safeguard the rights of citizens” - strongly disagree, disagree, unsure, agree, strongly agree
How would we evaluate the quality of the questions?
A. Q1 contains an unwarranted assumption; Q2 is ambiguous; Q3 would be vulnerable to social desirability effects
B. Q1 is satisfactory; Q2 is too sensitive - the amount of money spent on phone bills is none of our business; Q3 is satisfactory
C. Q1 is too sensitive - we should not ask people questions about their mothers; Q2 is good because it asks for specific information; Q3 is leading
D. Q1 contains an unwarranted assumption; Q2 requires information that the participant might not remember; Q3 is double-barrelled
E. all of the questions are satifactory
D. Q1 contains an unwarranted assumption; Q2 requires information that the participant might not remember; Q3 is double-barrelled.
First consider this 2x2 between groups desgin study: Researchers investigated the effects of ‘author’s sex’ and ‘errors’ on judgements that people make about the quality of a journalist’s writing. In the study, participants were randomly allocated to one of four conditions: (i) female author and grammatical errors, (ii) female author and no grammatical errors, (iii) male author and errors, (iv) male author and no errors. Author and errors were manipulated using bogus journalist names and 4 similar articles. The participants read the newspaper article and were asked: “What is the quality of the newspaper article?” (rated on a standard rating scale).
Q1. What is the purpose of question “What is the quality of the newspaper article?”
A. It provides a measure of the independent variable
B. It provides a measure of the dependent variable
C. It provides an assessment of extraneous variables
D. It is a manipulation check
E. Both (C) and (D)
Q2. The above design is:
A. a true experimental, posttest only two-group design with one between-subjects factor and one within-subjects factor
B. a true experimental, posttest only two-group design with two between-subjects factors
C. a quasi-experimental, static group comparison with two between-subjects factors
D. a true experimental, four-group design with one-between subjects factor and one within-subjects factor
E. a 2 x 2 between-subjects factorial design
Q1: B. It provides a measure of the dependent variable
Q2. E. a 2 x 2 between-subjects factorial design
The correlation coefficient for the scatter plot is most likely to be (and why)
A. 1.00
B. .64
C. -.80
D. -1.00
E. Impossible to say without knowing the degrees of freedom

C. - 80
Graph goes right to left = negative
In a study of the number of crimes per year
and the number of churches in towns & cities… CRIMES and CHURCHES were found to be highly correlated,
r = .69. However, when the population size (POP) of the towns and cities was taken into account, the partial correlation was .11 (nonsig). This gives us good reason to conclude that:
A. There are likely to be other unstudied factors which predict CRIMES more strongly than POP or CHURCHES (??)
B. CRIMES is highly related to CHURCHES but not to POP (??)
C. There is not a strong linear relationship between CRIMES and
CHURCHES (the correlation is strong)
D. The relationship b/t CRIMES & CHURCHES is a spurious one
E. At least three of these (A, B, C, D) are true
D. the relationship between Crimes and Churches is a spurious on.
Which of the following is true of the figures above?
A. Figure 1 shows heteroscedasticity; Figure 2 shows a strong negative correlation, Figure 3 shows an interaction
B. Figure 1 shows homoscedasticity; Figure 2 shows a strong negative correlation, Figure 3 shows main effects but no interaction
C. Figure 1 shows heteroscedasticity; Figure 2 shows a weak negative correlation, Figure 3 shows an interaction
D. Figure 1 shows heteroscedasticity; Figure 2 shows a moderate positive correlation, Figure 3 shows an interaction
E. Figure 1 shows heteroscedasticity; Figure 2 shows a moderate positive correlation, Figure 3 shows main effects but no interaction
A. Figure 1 shows heteroscedasticity; Figure 2 shows a strong negative correlation, Figure 3 shows an interaction.
What DOES and DOESN’T the significance value (p) tell us?
DOES: tell us if a relationship exists
Doesn’t: tell us effect size or give any conceptual understanding, or how compelling the evidence is
