Data Screening
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Last updated 7:56 AM on 7/29/23
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6 Terms
1
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What is the purpose and steps of data screening?
Data screening is a process to check data prior to conducting inferential statistics. It checks:
1. Accuracy
2. Missing
3. Outliers
4. Parametric tests
1. Accuracy
2. Missing
3. Outliers
4. Parametric tests
2
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What are the cut-off points for outliers given sample size?
* SMALL (n ≤ 50) = ±1.96
* MEDIUM (n = 51-100) = ±2.58
* LARGE (N > 100) = ±3.29
* MEDIUM (n = 51-100) = ±2.58
* LARGE (N > 100) = ±3.29
3
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What are different ways to assess assumption of normality?
* KOLMOGOROV-SMIRNOV (n > 50)
* SHAPIRO-WILK (n ≤ 50)
* SHAPIRO-WILK (n ≤ 50)
4
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What is z-skewness and z-kurtosis?
Statistic/Std. Error
5
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What is the assumption of homogeneity of variance?
* Levene’s Test
* Test whether variances of 2 samples are approximately equal
* Assessed the same as normality tests
* Test whether variances of 2 samples are approximately equal
* Assessed the same as normality tests
6
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What is the assumption of linearity and homoschedasticity?
* Linearity (scatterplot = linear relationship
* Homoscedasticity = equal variances in scatterplot
* Homoscedasticity = equal variances in scatterplot