When the levels of one or more categorical variables are greater than two, we us
ID: 3131621 • Letter: W
Question
When the levels of one or more categorical variables are greater than two, we use what to estimate effect size.
proportion of variance
the phi coefficient
Cramer’s V
all are appropriate
Is it possible to predict the height of a tennis ball's bounce from the height from it was dropped? To explore this, a Physics teacher drops a tennis ball onto a cement floor from various heights (measured in feet), and measures the height of the corresponding return bounces. In order to investigate, she then makes a scatterplot based on these data. In making thescatterplot, the teacher should
plot the height of the ball's return bounce on the horizontal axis.
plot the height of the ball's drop on the horizontal axis.
first determine if the bounce return heights follow a Normal distribution.
use a plotting scale that makes the overall trend roughly linear.
proportion of variance
the phi coefficient
Cramer’s V
all are appropriate
Is it possible to predict the height of a tennis ball's bounce from the height from it was dropped? To explore this, a Physics teacher drops a tennis ball onto a cement floor from various heights (measured in feet), and measures the height of the corresponding return bounces. In order to investigate, she then makes a scatterplot based on these data. In making thescatterplot, the teacher should
plot the height of the ball's return bounce on the horizontal axis.
plot the height of the ball's drop on the horizontal axis.
first determine if the bounce return heights follow a Normal distribution.
use a plotting scale that makes the overall trend roughly linear.
Explanation / Answer
When the levels of one or more categorical variables are greater than two then the commonly used effect sizes are phi coefficient and Cramer’s V.
Phi coefficient can be computed by finding the square root of the chi-squared statistic divided by the sample size.
Cramér's V can be computed by taking the square root of the chi-squared statistic divided by the sample size and the length of the minimum dimension (k is the smaller of the number of rows r or columns c).
The teacher should plot the height of the ball's drop on the horizontal axis or the x axis to predict the height of a tennis ball's bounce from the height from it was dropped.
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