Suppose the correlation between height and weight for adults is +0.40. What proportion (or percent) of the variability in weight
1 answer:
Answer:
We are given the correlation between height and weight for adults is 0.40.
We need to find the proportion of the variability in weight that can be explained by the relationship with height.
We know that coefficient of determination or R-square measures the proportion or percent of variability in dependent variable that can be explained by the relationship with independent variable. There the coefficient of determination is given below:
Therefore, the 0.16 or 16% of the variability in weight can be explained by the relationship with height
You might be interested in
The frequency table, stem and leaf plot, and histogram are attached.
The histogram looks similar to the stem and leaf plot, except turned on its side. It is different from the frequency table in shape, but the numbers in the table are the same as the size of the bars.
The height of the bars in the histogram is the same as the number of leaves in the stem and leaf plot, and it is also the same as the numbers in the frequency table. Using larger intervals will result in larger bars on the histogram and larger numbers in the frequency table; smaller intervals will result in smaller bars and smaller numbers in the table.
The histogram looks similar to the stem and leaf plot, except turned on its side. It is different from the frequency table in shape, but the numbers in the table are the same as the size of the bars.
The height of the bars in the histogram is the same as the number of leaves in the stem and leaf plot, and it is also the same as the numbers in the frequency table. Using larger intervals will result in larger bars on the histogram and larger numbers in the frequency table; smaller intervals will result in smaller bars and smaller numbers in the table.