CBMR Pre-Quiz Nr. 4

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Data integrity should begin as soon as the first batch of questionnaires is received from the field, while the fieldwork is still going on.

A codebook generally contains the following information: (1) row identifier, (2) question name, (3) question type, and (4) coding instructions.

A method for handling missing responses in which cases or participants with any missing responses are discarded from the analysis, is called casewise deletion.

A standardized scale will have a mean of 1 and a standard deviation of 1.

In the data view of SPSS, each row represents a case of observation, each column represents a variable/item.

Crosstabulation, ANOVA, Factor and Cluster Analysis belong to the dependence techniques.

The median is defined as the value above which half of the values fall and below which half of the values fall.

As the standard deviation is defined as the square root of the variance, the standard deviation always shows smaller values than the variance.

When using the SPSS option “SPLIT FILE”, separate analyses are displayed for each sub-sample build based on the grouping variable.

An error that occurs when the sample results lead to the rejection of a null hypothesis that is in fact true, is called type II error (or: beta error).

The t statistic assumes that the variable is normally distributed, but is quite robust to departures from normality.

To test the equality of variances, the researcher should check the result of the Welch test before interpreting the output table of the independent samples t-test.

The chi-square statistic is used to test the statistical significance of the observed association in a cross-tabulation.

The contingency coefficient varies between 0 (variables are statistically independent) and 1 (maximum value can be achieved).

In ANOVA, two measures of variation are estimated: within groups and between groups.

All points of observations of two variables with a correlation coefficient of -0.75 form a decreasing linear function.

The adjusted R² as the coefficient of multiple determination, is adjusted for the number of independent variables and the sample size to account for diminishing returns.

Compared to the Elbow criterion, the Kaiser criterion usually leads to higher number of factors which needs to be extracted.

The correlation between the initial variable and a certain factor, is called factor loading.

A factor is an underlying dimension that explains the correlations among a set of variables.