DE200
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43 questions
🇬🇧 | 🇬🇧 |
What are the three things you need to consider before designing an effective research question? | How your assumptions guide your focus, phrasing, implications |
NA | NA |
Consequentialism | Argues rightness and wrongness depends on the consequences of the action |
Deontology | Argues some things are right and wrong regardless of outcome |
Operationalism | The process of turning an abstract idea into a measurable concept |
What is the difference between nominal, ordinal and interval data | Nominal (Categorical: gender), Ordinal (High, medium, low), Interval (Age, Temperature) |
Descriptive stats | Stats that summarise the data collected in a study |
Inferential stats | Allow you to make sense of patterns in your data |
List the measures of central tendence | Mean, median, mode |
Standard deviation | Distance between points and the mean |
Interquartile range | Difference between upper and lower quartiles |
Normal distribution | Function representing distribution of variables as symmetrical bell-shaped graph |
Skewed distribution | Representation of scores that lack symmetry |
Experimental designs | Establish cause and effects between variables |
Correlational designs | Predict associations or relationships between naturally occuring variables |
Two-tailed hypothesis | When your hypothesis has no direction |
One-tailed hypothesis | Your hypothesis predicts a direction in the results |
Null hypothesis | Predicts that two samples are from the same population and any differences between them is purely due to sampling error |
How do you calculate Standard error? | SE = SD/√n |
How do you know if your experiment has worked? | You find enough evidence to reject the null hypothesis |
Statistical significance | Calculates the probability the results obtained are due to sampling error and not experimental manipulation. The smaller the probability, the more significant the difference. |
Effect size | Calculates the difference between the conditions in real time |
T-test | Allows you to tell whether there is a statistically significant difference between two conditions |
When is an independent t-test used? | When your experiment is a between-participants design |
When is a repeated-measures t-test used? | When your experiment is a within-participants design |
What is the formula for a t-test? | T=difference between group means/standard error of difference in means |
What assumptions must be met for a t-test to be reliable? | Assumption of normality, homogeneity of variance, independence and data must be interval. |
How do you write up an independent t-test in APA format? | T(12)=3.45,p<0.05,d=0.67 |
What is the IV | Independent variable, the variable that is manipulated |
What is the DV | The variable that is measured as as result of manipulating the IV |
Systematic variation | Variance due to experimental manipulation |
Unsystematic variation | Variance due to other sources |
What is an ANOVA? | Analysis of variance, it looks at the variability of a data set to establish whether the means of the different conditions are the same or not |
When is a One-way independent ANOVA used? | When you have a between-participants design |
When is a One-way repeated measures ANOVA used? | When you have a within-participants design |
What is the formula for a one-way ANOVA? | F=systematic variance/unsystematic variance |
What are post-hoc tests? | Post-hoc tests compare each possible pair of conditions |
What must you do if your ANOVA produced results p<0.05 rejecting the null hypothesis? | Run post-hoc tests |
Give an example of a post-hoc test | Bonferroni |
What does it mean if the unsystematic variance outweighs the systematic variance? | F<1 and will never be significant |
How do we write up an ANOVA in APA format? | F(2,297)=7.34,p=0.001,ƞp2= .05 |
What assumptions must be met for a repeated-measures ANOVA to be reliable? | Independece within groups and assumption of sphericity |
What is the assumption of sphericity? | It assumes the variances between the different combinations of conditions are equal |