Assume that you have paired values consisting of heights (in inches) and weights (in lb) from 40 randomly selected men. The li
1 answer:
Answer:
The value of the coefficient of determination is 0.263 or 26.3%.
Step-by-step explanation:
<em>R</em>-squared is a statistical quantity that measures, just how near the values are to the fitted regression line. It is also known as the coefficient of determination.
A high R² value or an R² value approaching 1.0 would indicate a high degree of explanatory power.
The R-squared value is usually taken as “the percentage of dissimilarity in one variable explained by the other variable,” or “the percentage of dissimilarity shared between the two variables.”
The R² value is the square of the correlation coefficient.
The correlation coefficient between heights (in inches) and weights (in lb) of 40 randomly selected men is:
<em>r</em> = 0.513.
Compute the value of the coefficient of determination as follows:
Thus, the value of the coefficient of determination is 0.263 or 26.3%.
This implies that the percentage of variation in the variable height explained by the variable weight is 26.3%.
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The probability the 51st call arriaves within 150hours is 0.0431, the probability the next call arrives within the next 2 hours 0.5488, the probability the sum of these 50 numbers is less than 356 is 0.4165.
Data;
- Mean rate = 0.3
- x = 50
- standard deviation = ?
Using poission formula,
Let's substitute the values into the formula.
For 50 calls in 150 hours
For 150 hours = x = 0.3 * 150 = 45
b)
The probability the next call arrives after 2 hours.
c)
The number of calls recieved each day is recorded for 50 consecutive days.
for 50 days;
The mean = 360
The standard deviation is given as
The probability the sum of these 50 number is less than 356 is
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