Chapter 4 - Quantitative Data Analysis Flashcards
1
Q
What types of variables are there?
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2.
3.
A
O N I
- interval / ratio - regular distances between all categories in range (e.g. age)
- ordinal - categories can be ranked, but with unequal distances between them (e.g. low < high education)
- nomal - qualitatively different categories - cannot be ranked (special case: dichotomous variable where there are two categories only; e.g. flipping a coin)
2
Q
Why does it matter whether a variable is nominal, ordinal or interval?
A
- specific levels of measurement required for statistical analyses, e.g. makes no sense to compute average hair color
3
Q
What is a univariate analysis?
What kind of measurments do we use here?
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2.
3.
A
- analysis of one variable at a time
- frequency table (number of people or casesin each category, often expressed in percentages, interval data needed)
- diagrams (charts for nominal variables, histogram for interval variables)
4
Q
What are the measures of central tendency?
A
Capture in one figure a value typical for ditribution of values
- arithmetic mean: sum all variables, then divide by total number of values
- median: middle point with entire range of values (not distored by outliers)
- mode: most frequent occuring value
5
Q
What is dispersion?
A
amount of variation in a sample
5
Q
What are the measures of dispersion?
A
- compare levels of variation in different samples - is there more variability in variable in one sample than in another?
6
Q
What is the range?
A
- difference between maximum and minimum values
7
Q
What is the standard deviation?
A
- average amount of variation around the mean
- reducing impact of extreme values (outliers)
8
Q
What is a bivariate analysis?
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A
- analysis of two variables at a time
- explores relationships between variables
- searches for co variance and correlations
- canot establish causality!
- e.g. contingency tables, pearsons correlation coefficient
