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Statistical terms
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1A [blank_start]bivariate correlation[blank_end] is a correlation between two variables
- Abivariate correlation
2A [blank_start]partial correlation[blank_end] looks at the relationship between two variables while controlling for one or more additional variables.
- Apartial correlation
3In correlation analysis, look at [blank_start]Pearson's r[blank_end] if the data meets parametric assumptions. However, if it does not, use [blank_start]Spearman's rho[blank_end] or [blank_start]Kendall's tau[blank_end]. These are both non parametric tests.
- APearson's r
- BSpearman's rho
- CKendall's tau
4Regression analysis fits a model to data and uses it to predict the values of the [blank_start]dependent[blank_end] variable by one or more [blank_start]independent[blank_end] variables.
- Adependent
- Bindependent
5R2 is a measure of how much of the variability in the [blank_start]outcome[blank_end] is accounted for by the [blank_start]predictors[blank_end].
- Aoutcome
- Bpredictors
6An R2 value of .335 means that the predictor variable accounts for [blank_start]35%[blank_end] of the variation in the outcome variable.
- A33.5%
- B3.35%
- C.335%
7The adjusted r2 gives an idea of how well the model [blank_start]generalizes[blank_end].
- Ageneralizes
8The difference between r2 and adjusted r2 shows the difference between the [blank_start]sample used[blank_end] and the [blank_start]general population[blank_end].
- Ageneral population
- Bsample used
9[blank_start]B values[blank_end] indicate the individual contribution of each predictor to the model.
- AB values
10B values tell us about the relationship between the [blank_start]DV[blank_end] and each [blank_start]IV[blank_end]. Positive scores each [blank_start]positive[blank_end] relationships (as one variable [blank_start]increases[blank_end], so does the other).
- ADV
- BIV
- Cpositive
- Dincreases
11The confidence intervals tell us the parameters within which the true [blank_start]mean difference[blank_end] lies.
- Amean difference
12We can use the parameters of confidence intervals to see how likely it is to get particular [blank_start]mean difference[blank_end] values if we [blank_start]replicated[blank_end] the experiment.
- Areplicated
- Bmean difference
13In a t-test, to calculate the degrees of freedom you take the number of [blank_start]subjects[blank_end] and minus [blank_start]one[blank_end].
- Asubjects
- Bone
14Which of the following facts are true regarding contrasts?
- AContrasts must add up to 1.
- BContrasts must add up to 0.
- CGroups coded with positive weights will be compared with groups coded with negative weights.
- DGroups assigned with a zero will not be compared to other groups (they will be eliminated from all calculations).
- EFor a given contrast, the weight assigned to the group(s) in one contrast should be equal to the number of groups in the opposite chunk of variation.
- FGroups are assigned the values of 1 or 0.
- GGroups assigned with a 0 will act as the control group for comparisons.
- HOnly two chunks of variation is compared at a time.
- IIf a group is singled out in one comparison, that group should be excluded from any subsequent contrasts.
15ANOVA tells us whether [blank_start]3[blank_end] or more means are the same, so it tests the [blank_start]null hypothesis[blank_end] that all groups are equal.
- A3
- Bnull hypothesis
16The ANOVA produces the [blank_start]F-statistic[blank_end] which compares the amount of [blank_start]systematic variance[blank_end] in the data to the amount of [blank_start]unsystematic variance[blank_end].
- AF-statistic
- Bsystematic variance
- Cunsystematic variance
17The F-ratio tells us that the means of three samples are [blank_start]not equal[blank_end], but it does not provide specific information about which groups are effected.
- Anot equal
- Bhighly correlated
- Cunequal
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- Bachelors Degree Advanced Data Analysis Quiz on Statistical terms, created by Veronica Martin0115 on 14/06/2016.
- Author
- Veronica Martin0115
- Language
- English
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