A biologist looked at the relationship between number of seeds a plant produces and the percent of those seeds that sprout. The results of the survey are shown below. Seeds Produced 55 49 67 70 46 68 41 54 Sprout Percent 48.5 64.5 45.5 41 59 49 67.5 48 Find the correlation coefficient: r=r= Round to 2 decimal places. The null and alternative hypotheses for correlation are: H0:H0: ? μ r ρ == 0 H1:H1: ? μ ρ r ≠≠ 0 The p-value is: (Round to four decimal places) Use a level of significance of α=0.05α=0.05 to state the conclusion of the hypothesis test in the context of the study. There is statistically insignificant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. There is statistically significant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. There is statistically insignificant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the use of the regression line is not appropriate. There is statistically significant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the regression line is useful. r2r2 = (Round to two decimal places) Interpret r2r2 : 77% of all plants produce seeds whose chance of sprouting is the average chance of sprouting. There is a 77% chance that the regression line will be a good predictor for the percent of seeds that sprout based on the number of seeds produced. Given any group of plants that all produce the same number of seeds, 77% of all of these plants will produce seeds with the same chance of sprouting. There is a large variation in the percent of seeds that sprout, but if you only look at plants that produce a fixed number of seeds, this variation on average is reduced by 77%. The equation of the linear regression line is: ˆyy^ = + xx (Please show your answers to two decimal places) Use the model to predict the percent of seeds that sprout if the plant produces 54 seeds. Percent sprouting = (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: The slope has no practical meaning since it makes no sense to look at the percent of the seeds that sprout since you cannot have a negative number. As x goes up, y goes down. For every additional seed that a plant produces, the chance for each of the seeds to sprout tends to decrease by 0.76 percent. Interpret the y-intercept in the context of the question: The y-intercept has no practical meaning for this study. The best prediction for a plant that has 0 seeds is 95.87 percent. The average sprouting percent is predicted to be 95.87. If plant produces no seeds, then that plant's sprout rate will be 95.87.

A biologist looked at the relationship between number of seeds a plant produces and the percent of those seeds that sprout. The results of the survey are shown below. Seeds Produced 55 49 67 70 46 68 41 54 Sprout Percent 48.5 64.5 45.5 41 59 49 67.5 48 Find the correlation coefficient: r=r= Round to 2 decimal places. The null and alternative hypotheses for correlation are: H0:H0: ? μ r ρ == 0 H1:H1: ? μ ρ r ≠≠ 0 The p-value is: (Round to four decimal places) Use a level of significance of α=0.05α=0.05 to state the conclusion of the hypothesis test in the context of the study. There is statistically insignificant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. There is statistically significant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds. There is statistically insignificant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the use of the regression line is not appropriate. There is statistically significant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the regression line is useful. r2r2 = (Round to two decimal places) Interpret r2r2 : 77% of all plants produce seeds whose chance of sprouting is the average chance of sprouting. There is a 77% chance that the regression line will be a good predictor for the percent of seeds that sprout based on the number of seeds produced. Given any group of plants that all produce the same number of seeds, 77% of all of these plants will produce seeds with the same chance of sprouting. There is a large variation in the percent of seeds that sprout, but if you only look at plants that produce a fixed number of seeds, this variation on average is reduced by 77%. The equation of the linear regression line is: ˆyy^ = + xx (Please show your answers to two decimal places) Use the model to predict the percent of seeds that sprout if the plant produces 54 seeds. Percent sprouting = (Please round your answer to the nearest whole number.) Interpret the slope of the regression line in the context of the question: The slope has no practical meaning since it makes no sense to look at the percent of the seeds that sprout since you cannot have a negative number. As x goes up, y goes down. For every additional seed that a plant produces, the chance for each of the seeds to sprout tends to decrease by 0.76 percent. Interpret the y-intercept in the context of the question: The y-intercept has no practical meaning for this study. The best prediction for a plant that has 0 seeds is 95.87 percent. The average sprouting percent is predicted to be 95.87. If plant produces no seeds, then that plant's sprout rate will be 95.87.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A biologist looked at the relationship between number of seeds a plant produces and the percent of those seeds that sprout. The results of the survey are shown below.

Seeds Produced	55	49	67	70	46	68	41	54
Sprout Percent	48.5	64.5	45.5	41	59	49	67.5	48

Find the correlation coefficient: r=r= Round to 2 decimal places.
The null and alternative hypotheses for correlation are:
H0:H0: ? μ r ρ  == 0
H1:H1: ? μ ρ r   ≠≠ 0
The p-value is:    (Round to four decimal places)
Use a level of significance of α=0.05α=0.05 to state the conclusion of the hypothesis test in the context of the study.
- There is statistically insignificant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds.
- There is statistically significant evidence to conclude that a plant that produces more seeds will have seeds with a lower sprout rate than a plant that produces fewer seeds.
- There is statistically insignificant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the use of the regression line is not appropriate.
- There is statistically significant evidence to conclude that there is a correlation between the number of seeds that a plant produces and the percent of the seeds that sprout. Thus, the regression line is useful.
r2r2 = (Round to two decimal places)
Interpret r2r2 :
- 77% of all plants produce seeds whose chance of sprouting is the average chance of sprouting.
- There is a 77% chance that the regression line will be a good predictor for the percent of seeds that sprout based on the number of seeds produced.
- Given any group of plants that all produce the same number of seeds, 77% of all of these plants will produce seeds with the same chance of sprouting.
- There is a large variation in the percent of seeds that sprout, but if you only look at plants that produce a fixed number of seeds, this variation on average is reduced by 77%.
The equation of the linear regression line is:
ˆyy^ = + xx (Please show your answers to two decimal places)
Use the model to predict the percent of seeds that sprout if the plant produces 54 seeds.
Percent sprouting = (Please round your answer to the nearest whole number.)
Interpret the slope of the regression line in the context of the question:
- The slope has no practical meaning since it makes no sense to look at the percent of the seeds that sprout since you cannot have a negative number.
- As x goes up, y goes down.
- For every additional seed that a plant produces, the chance for each of the seeds to sprout tends to decrease by 0.76 percent.
Interpret the y-intercept in the context of the question:
- The y-intercept has no practical meaning for this study.
- The best prediction for a plant that has 0 seeds is 95.87 percent.
- The average sprouting percent is predicted to be 95.87.
- If plant produces no seeds, then that plant's sprout rate will be 95.87.

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