CBMR Quiz 2 (Group 2)

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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.

Multi-response questions can be coded with an ordinal variable for each item, identifying if this item was or was not chosen by a specific respondent.

Pairwise deletion is an appropriate procedure for handling missing values when (1) the sample size is large, (2) there are few missing responses, and (3) the variables are not highly related.

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

For a symmetric distribution, mean, median and mode show the same value.

In SPSS, the options “SPLIT FILE” and “SELECT CASES” lead to the same output tables.

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

The probability of a type I and/or type II error is also called level of significance.

To test the equality of variances, the researcher should check the result of the Levene’s test before interpreting the output table of the independent samples t-test.

The alternative hypothesis for the chi-square statistic, is that there is no association between the variables.

As a general rule, chi-square analysis should not be conducted when the expected frequency in any of the cells is less than 5.

Eta² measures the significance of the effect of X on Y and varies between 0 and 1.

ANOVA must have a dependent variable that is metric and also one categorical (non-metric) independent variable.

A correlation coefficient of 0 indicates that X and Y are unrelated.

The correlation coefficient can be used to summarize the strength of association between two metric variables.

The OLS procedure determines the best-fitting regression equation by minimizing the square of the horizontal distances of all points of observation from the regression line.

Even if a regression analysis helps to explain the variation in the dependent variable, this does not necessarily imply causation.

The difference between the observed value of Y and the value predicted by the regression equation, is called error term.

The amount of variation a variable shares with all other variables included in a factor analysis is referred to as communality.

Factor analysis requires an appropriate sample size. A a rough guide, there should be at least two or three times as many observations (sample size) as there are variables.