Answer:
Step-by-step explanation:
The table below shows the observed counts in black (first number), expected counts in green (second number), and contribution to
the chi-square statistic in blue (third number). Heart disease No Heart disease Total Anger score Low Anger 53 69.7 4.014 3057 3040.3 0.092 3110 Moderate High Anger Anger 110 106.1 0.145 4621 4624.9 27 4731 14.2 11.557 606 0.0033 0.265 618.8 8284 633 Total 190 O Yes, because the sample size is greater than 30. 8474 Are the conditions met to conduct a chi-square test of association? Yes, because the expected cell counts are greater than 5. O Yes, because there are no extreme outliers in the data. O Yes, because the observed cell counts are greater than 5.
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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
so you are going to use the Pythagorean theorem on the smaller triangle to find the connecting side's length
now you can find the bigger triangle's hypotenuse
c=4