Answer these Summarizing and Making Inferences from Quantitative Data MCQs and see how sharp is your knowledge of Summarizing and Making Inferences from Quantitative Data.
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A. Summary measures of location capture important features of the whole distribution of data for a variable.
B. Summary measures of location are easier to remember than the original dat
C. Summary measures of location indicate the centre of a set of dat
D. Every data point contributes equally to a summary measure of location.
A. Mode
B. Median
C. Mean
D. Mid-mean
E. None of these
A. Mode
B. Median
C. Mean
D. Mid-mean
A. Summary measures of spread capture important features of the whole distribution of data for a variable.
B. Summary measures of spread are easier to remember than the original dat
C. Summary measures of spread indicate the amount of variability around a measure of location.
D. Every data point contributes equally to a summary measure of spread.
A. Robust measures are completely unaffected by measurement error.
B. The median is more robust than the mean.
C. Using robust measures means that the researcher does not have to worry about the assumptions of statistical methods.
D. Robust measures are always less efficient.
A. Failing to confirm the researchers preferred hypothesis
B. Missing a real effect
C. Claiming an effect which is not actually real
D. Finding an effect which is not consistent with existing literature
A. There is always a single correct reference distribution for a specific significance test.
B. The normal distribution is what we should expect data to look like.
C. Using the right reference distribution means that you do not have to check the quality of your dat
D. Reference distributions are approximations which may be useful in practice.
A. Normally distributed data within each group
B. Estimates of a summary measure of location for each group
C. The assumption that all three groups are different from each other
D. A true causal relationship between the grouping variable and the dependent variable
A. Variables measured at least on an ordinal scale
B. Normally distributed data
C. Data without measurement error
D. A true causal relationship between the two variables
A. Two variables measured on nominal scales
B. Two variables measured on continuous scales
C. One variable measured on an ordinal scale and one variable measured on a continuous scale
D. One variable measured on an ordinal scale and one variable measured on a continuous scale