Compare and contrasts the "interesting pairs" of the four bivariate data
analysis models we are working with.
1. There are four basic bivariate data analysis models. The first is pearson's chi-square. This model is used to find a
pattern of relationships when you have two qualitative variables. The second model is between
groups ANOVA. BG ANOVA compairs the mean differences of different participants in two
different conditions. Another model is pearson's correlation. Correlation is used to determine
a linear relationship between two quantitative variables.Finally, the last model is the within
groups ANOVA. WG ANOVA compares the mean differences of the same participants in two
different conditions. In all of these models, you CANNOT use them to test a attibutive
research hypothesis because the models are bivariate and attributive research hypothesis is
univariate. Yet, in all the models you can always use them to test an associative research
hypothesis, and sometimes a causal research hypothesis (given that there is random
assignment by the researcher before manipulation of the IV, proper manipulation of the IV,
and no potential confounds). Correlation can be paired with WG ANOVA for longitudinal
studies and repeated measures. Chi-square can be paired with BG ANOVA for crosssectional studies. Correlations are shown on a scatterplot, and chi-square analysis are
shown on a contingency table. Both ANOVAs have a qualitative variable and a quantitative
variable. Correlation is about about a linear relationship, chi-square is about pattern
relationship, and BG ANOVA and WG ANOVA are about mean differences.
2. One "interesting pair" is WG ANOVA and BG ANOVA; both of these analyses are ANOVAs
and so both are used to compare one qualitative and one quantitative variable. They are
different, because WG ANOVA compares data from a within-groups experiment, whereas,
BG ANOVA compares data from a between groups experiment. Another pair is BG ANOVA
and Pearson's Chi-square; both of these analyses are generally used for between groups
experiments. They are different, because BG ANOVA is used to compare one quantitative
variable and one qualitative variable, whereas, Pearson's Chi-square is used to compare two
qualitative variables. A third pair is WG ANOVA and Pearson's correlation; both of these
analyses are generally used for within-groups experiments. They are different, because WG
ANOVA is used to compare one quantitative variable and one qualitative variable, whereas,
Pearson's correlation is used to compare two quantitative variables. The fourth and final pair
is Pearson's Chi-square and Pearson's correlation; both of these analyses are used to
compare two of the same type of variables. They are different, because Pearson's Chi-square
is used to compare two qualitative variables, whereas, Pearson's correlation is used to
compare two quantitative variables.
3. The first interesting pair of the data analysis model is BG ANOVA and WG anova. They are
similar because they both measure mean quantitative differences between qualitative
variables. The next interesting pair is Chi squared and Correlation. They are similar in that
they both measure associations, but are different because one (r) measures linear
relationships between two quantitative variables and the other (X^2)measures patterns of
relationships between two qualitative variables. Chi squared is similar to BG ANOVA because
they are both comparisons of different groups, though F tests mean differences and X^2
measures patterns. The last interesting pair is r and WG anova. They are both about
repeated measures but r tests linear relationships and WG anova tests mean differences.
4. Pearson's correlation (r) deals with two quantitative variables and if they have a linear
relationship. Pearson's Chi-square deals with two qualitative variables and if they have a
relationship. WG ANOVA deals with a quantitative variable as the DV and and comparison of
a qualitative variable as the IV. The analysis is used for studies in which the participants are
the same in both groups. BG ANOVA deals with a quantititative variable as the DV and a
comparison of a qualitative variable as the IV. The analysis is used for studies in which the
participants are different in the two groups.
5. The four bivariate data analysis that we are working with are between and within groups
ANOVA, correlation, and chi-square. Between groups ANOVA is used when you have a
cross-sectional test with a qualitative and quanitative variable. A within groups ANOVA is
used when you a longitudinal study with a qualitative and quantitative variable. ANOVA's are
used to compare the means of the variables. A correlation is used with two quantitative
variables and looks at their relationship and whether it is linear or non-linear. A chi-square
test is used when you have two qualitative variables and what to compare their means.
6. First, all of the bivariate data we worked with are Between Groups Anova, Within Groups
Anova, Pearson's Chi-squared and Pearson's R. BG Anova is when there are different
conditions in a study and participants are in one of the conditions, not all of them. Also it is
when there is one quantitative variable and one qualitative variable. Bg Anova can
sometimes be confused with Pearson's Chi-squared because it is very similar however there
are differences one difference is that the Dv is qualitative. Another difference is that both
variables are qualitative. Also Anovas are looking for mean difference and Chi-squareds are
looking for relationships. Wg Anova is when there are different conditions, but everyone
participates in all of the conditions. Also because it is an Anova there is one qualitative
variable and one quantitative. Pearson's r can be confused with Wg Anova, but all you have
to remember is that pearson's correlation has two quantitative variables, the Dv is quantitative
and you are looking for a positive, negative or no correlation.