There are 5 cards with a picture of a rose and 1 card with a picture of a daisy. Olga keeps all the cards face down on the table
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Answer:
The appropriate conclusion that answers the question stated in step one is:
- The weak correlation value does not support the idea that beavers benefit beetles.
- The largest number of beetle larvae was 55 and the largest number of stumps was 5.
Step-by-step explanation:
1) Select the appropriate practical question.
The appropriate practical question is:
"How does the number of beaver-caused stumps influences the number of beetle larvae clusters?"
2) Make a scatter plot.
The scatter plot is attached below.
From the scatter plot it can be seen that there exists a negative relationship between beaver stumps and beetle larvae. That is as the number of stumps increases the number of beetle larvae decreases.
The maximum number of beaver stumps found is 5.
3)
The best numerical summary for this problem are,
Correlation and regression line
The least square regression line for predicting the number of beetle larvae from the number of stumps is:
<em>y</em> = 31.594 - 2.8365 <em>x</em>.
Use the Excel function "=CORREL(array1,array2)" to compute the correlation.
The correlation value is, <em>r</em> = -0.219.
Both the correlation coefficient and regression line explains a negative relationship between the number of beetle larvae and the number of stumps.
Values amid 0 and 0.3 (0 and -0.3) implies a weak positive (negative) linear relationship amid the variables.
Thus, a correlation coefficient, r = -0.219, indicates a weak negative correlation between two variables.
Thus, the appropriate conclusion that answers the question stated in step one is:
- The weak correlation value does not support the idea that beavers benefit beetles.
- The largest number of beetle larvae was 55 and the largest number of stumps was 5.
Answer:
Step-by-step explanation:
The sinusoidal function has a general form of:
The period is given by:
Y is the y-intercept, thus y = 3.
At the maximum value:
At the minimum value:
Therefore, the equation of the function described is: