Concept explainers
Seedlings of understory trees in mature tropical rainforests must survive and grow using intermittent flecks of sunlight. How does the length of exposure to these flecks of sunlight (fleck duration) affect growth? Researchers experimentally irradiated seedlings of the Southeast Asian rainforest tree with flecks of light of varying duration while maintaining the same total irradiance to all the seedlings. Below is the data. Fit a linear model to the data.
Tree |
Mean Fleck (min) |
Relative growth rate (mm/mm/week |
1 |
3.4 |
0.013 |
2 |
3.2 |
0.008 |
3 |
3 |
0.007 |
4 |
2.7 |
0.005 |
5 |
2.8 |
0.003 |
6 |
3.2 |
0.003 |
7 |
2.2 |
0.005 |
8 |
2.2 |
0.003 |
9 |
2.4 |
0 |
10 |
4.4 |
0.009 |
11 |
5.1 |
0.01 |
12 |
6.3 |
0.009 |
13 |
7.3 |
0.009 |
14 |
6 |
0.016 |
15 |
5.9 |
0.025 |
16 |
7.1 |
0.021 |
17 |
8.8 |
0.024 |
18 |
7.4 |
0.019 |
19 |
7.5 |
0.016 |
20 |
7.5 |
0.014 |
21 |
7.9 |
0.014 |
a)What is the rate of change in relative growth rate per minute of fleck duration? Also, provide a standard error of your estimate.
(b) Use these data, test the hypothesis that fleck duration affects seedling growth rate.
Trending nowThis is a popular solution!
Step by stepSolved in 4 steps with 3 images
- The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. x 11.8 8.2 6.8 3.5 2.8 2.8 2.3 0.5 y 13.9 10.8 10.1 7.2 6.5 6.5 6.3 4.8 x = thousands of automatic weapons y = murders per 100,000 residents This data can be modeled by the equation y = 0.81x + 4.35. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator. A) How many murders per 100,000 residents can be expected in a state with 7 thousand automatic weapons? Round to 3 decimal places. B) How many murders per 100,000 residents can be expected in a state with 7.8 thousand automatic weapons? Answer = Answer = Round to 3 decimal places.arrow_forwardBelow is a scatterplot of a student’s SAT score and their college GPA. Suppose we want to decide if a student’s SAT score and their GPA are linearly related. What does this scatterplot tell us of the relationship? Support your answer. SAT score_GPA scatterplot.pdfarrow_forwardPrehistoric pottery vessels are usually found as sherds (broken pieces) and are carefully reconstructed if enough sherds can be found. Information taken from Mimbres Mogollon Archaeology by A. I. Woosley and A. J. McIntyre (University of New Mexico Press) provides data relating x = body diameter in centimeters and y = height in centimeters of prehistoric vessels reconstructed from sherds found at a prehistoric site. The following Minitab printout provides an analysis of the data. Predictor Coef SE Coef T P Constant -0.212 2.429 -0.09 0.929 Diameter 0.7527 0.1686 5.33 0.013 S = 4.16190 R-Sq = 81.2% (c) The formula for the margin of error E for a c% confidence interval for the slope ? can be written as E = tc(SE Coef). The Minitab display is based on n = 12 data pairs. Find the critical value tc for a 90% confidence interval in the relevant table. Then find a 90% confidence interval for the population slope ?. (Use 3 decimal places.) tc lower limit upper…arrow_forward
- The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. 11.8 8.5 7 3.3 2.5 2.8 2.2 0.6 14.2 11.6 10.3 7.1 6.4 6.7 6.2 4.8 thousands of automatic weapons = murders per 100,000 residents This data can be modeled by the linear equation ŷ = 0.84x + 4.33 a. How many murders per 100,000 residents can be expected in a state with 9.1 thousand automatic weapons? Round to 3 decimal places. murders per 100,000 residents b. How many murders per 100,000 residents can be expected in a state with 4.3 thousand automatic weapons? Round to 3 decimal places. murders per 100,000 residentsarrow_forwardA botanist found a correlation between the length of an aspen leaf and its surface area to be 0.94. Why does thecorrelation value of 0.94 not necessarily indicate that a linear model is the most appropriate model for therelationship between length of an aspen leaf and its surface area? (A) The value must be exactly 1 or to indicate a linear model is the most appropriate model. (B) The value must be 0 to indicate a linear model is the most appropriate model. (C) A causal relationship should be established first before determining the most appropriate model. (D) The value of 0.94 implies that only 88% of the data have a linear relationship. (E) Even with a correlation value of 0.94, it is possible that the relationship could still be better represented by a nonlinear model.arrow_forwardA patient is classified as having gestational diabetes if their average glucose level is above 140 milligrams per deciliter (mg/dl) one hour after a sugary drink is ingested. Rebecca's doctor is concerned that she may suffer from gestational diabetes. There is variation both in the actual glucose level and in the blood test that measures the level. Rebecca's measured glucose level one hour after ingesting the sugary drink varies according to the Normal distribution with μ=140+5 mg/dl and σ=5+1 mg/dl. Using the Central Limit Theorem, determine the probability of Rebecca being diagnosed with gestational diabetes if her glucose level is measured: Once? n=5+2 times n=5+4 times Comment on the relationship between the probabilities observed in (a), (b), and (c). Explain, using concepts from lecture why this occurs and what it means in context.arrow_forward
- To investigate the relationship between yield of soybeans and the amount of fertilizer used, a researcher divides a field into eight plots of equal size and applies a different amount of fertilizer to each plot. The table shows the yield of soybeans and the amount of fertilizer used for each plot. A scatterplot of the data confirms that there is a linear association. Predict the yield of soybeans for 2.75 pounds of fertilizer. Round answer to the nearest whole number. Do not include the label in your answer. Amount of Fertilizer (in pounds) Yield of soybeans (in pounds) 1 25 1.5 21 2 27 2.5 28 3 36 3.5 35 4 32 4.5 34 im not sure how to start with thisarrow_forwardSometimes we have data that can be paired together, such as height and weight of an individual. When two variables are measured and paired together, we have what we call paired data. When we have paired data, we can plot the results using a scatterplot. This will give us a visual to determine if there is a relationship between the variables of interest. For two variable relationships, we can often report the data as ordered pairs in (x, y) format. Our x-variable in this case is known as the explanatory variable, and the y-variable is known as the response variable. We use values of x to predict y. If there appears to be a linear relationship between the two variables, we can create a least squares regression line. This is a line that “best” fits the dataset we have. The result will be a linear equation and we can use this equation to predict future values. For simple linear regression (ordered pairs with only two variables), the general form of a regression line follows:�̂=β0+β1�,…arrow_forwardThe table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.8 8.4 7.2 3.6 2.7 2.7 2.2 0.7 yy 13.8 11.5 10 7.2 6.4 6.1 6.2 4.4 xx = thousands of automatic weaponsyy = murders per 100,000 residents This data can be modeled by the equation y=0.84x+4.06.y=0.84x+4.06. Use this equation to answer the following;A) How many murders per 100,000 residents can be expected in a state with 2.7 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 4.9 thousand automatic weapons?Answer = Round to 3 decimal places.arrow_forward
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
- Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman