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Lamb’s quarters is a common weed that interferes with the growth of corn. An agriculture researcher planted corn at the same rate in 16small plots of ground and then weeded the plots by hand to allow a fixed number of lamb’s quarters plants to grow in each meter of cornrow. The decision on how many of these plants to leave in each plot was made at random. No other weeds were allowed to grow. Here are the yields of corn (bushels per acre) in each of the plots:


Here is some computer output from a least-squares regression analysis of these data. Do these data provide convincing evidence at the α=0.05level that more lamb’s quarters reduce corn yield?


PredictorCoefSECoefTPConstant166.4832.72561.110.000Weedsper−1.09870.5712−1.920.075meterS=7.97665R-Sq=20.9%R-Sq(adj)=15.3%

Short Answer

Expert verified

Yes, there is convincing evidence that more lamb's quarters reduce corn yield.

Step by step solution

01

Given Information

We need to find the given data which provides convincing evidence at the α=0.05level that more lamb’s quarters reduce corn yield.

02

Simplify

Consider:

n=Samplesize=16α=Significancelevel=0.05

The estimate of the slope b1is given in the row "Weeds per meter" and in the column "Coef" of the given computer output:

b1=-1.0987

The estimated standard deviation of the slope SEb1is given in the row "Weeds per meter" and in the column "SE Coef" of the given computer output:

SEb1=0.5712

Given claim: Slope is negative (reduction):

The null hypothesis or the alternative hypothesis states the given claim The null hypothesis states that the slope is zero. If the given claim is the null hypothesis, then the alternative hypothesis states the opposite of the null hypothesis.

role="math" localid="1654162502097" H0:β1=0Hα:β1<0

Compute the value of the test statistic:

t=b1−β1SEb1=−1.0987−00.5712≈−1.9235

The P-value is the probability of obtaining the value of the test statistic, or a value more extreme. The P-value is the number (or interval) in the column title of the Student's T table in the appendix containing the -value in the row df=n−2=16−2=14We can ignore the minus sign in the test statistic:

0.025<P<0.05

If the P-value is less than or equal to the significance level, then the null hypothesis is rejected:
P<0.05⇒RejectH0

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Most popular questions from this chapter

T12.12 Foresters are interested in predicting the amount of usable lumber they can harvest from various tree species. They collect data on the diameter at breast height (DBH) in inches and the yield in board feet of a random sample of 20 Ponderosa pine trees that have been harvested. (Note that a board foot is defined as a piece of lumber 12 inches by 12 inches by 1 inch.) Here is a scatterplot of the data.

a. Here is some computer output and a residual plot from a least-squares regression on these data. Explain why a linear model may not be appropriate in this case.

The foresters are considering two possible transformations of the original data: (1) cubing the diameter values or (2) taking the natural logarithm of the yield measurements. After transforming the data, a least-squares regression analysis is performed. Here is some computer output and a residual plot for each of the two possible regression models:

b. Use both models to predict the amount of usable lumber from a Ponderosa pine with diameter 30 inches.
c. Which of the predictions in part (b) seems more reliable? Give appropriate evidence to support your choice.

Women who are severely overweight suffer economic consequences, a study has shown. They have household incomes that are $6710less than other women, on average. The findings are from an eight-year observational study of 10,039randomly selected women who were 16-24years old when the research began. If the difference in average incomes is statistically significant, does this study give convincing evidence that being severely overweight causes a woman to have a lower income?

a. Yes; the study included both women who were severely overweight and women who were not.

b. Yes; the subjects in the study were selected at random.

c. Yes, because the difference in average incomes is larger than would be expected by chance alone.

d. No; the study showed that there is no connection between income and being severely overweight.

e. No; the study suggests an association between income and being severely overweight, but we can’t draw a cause-and-effect conclusion.

AP4.37 A manufacturer of electronic components is testing the durability of a newly designed integrated circuit to determine whether its life span is longer than that of the earlier model, which has a mean life span of 58 months. The company takes a simple random sample of 120 integrated circuits and simulates typical use until they stop working. The null and alternative hypotheses used for the significance test are H0:μ=58 and

Ha:μ>58. The P -value for the resulting one-sample t test is 0.035. Which of the following best describes what the P -value measures?
a. The probability that the new integrated circuit has the same life span as the current model is 0.035.
b. The probability that the test correctly rejects the null hypothesis in favor of the alternative hypothesis is 0.035.
c. The probability that a single new integrated circuit will not last as long as one of the earlier circuits is 0.035.
d. The probability of getting a sample mean as far or farther above 58 if there really is no difference between the new and the old circuits is 0.035.
e. The probability of getting a sample mean for the new integrated circuit that is less than the mean for the earlier model is 0.035.

Which sampling method was used in each of the following settings, in order from I to IV?

I. A student chooses to survey the first 20 students to arrive at school.

II. The name of each student in a school is written on a card, the cards are well mixed, and 10 names are drawn.

III. A state agency randomly selects 50 people from each of the state’s senatorial districts.

IV. A city council randomly selects eight city blocks and then surveys all the voting-age residents on those blocks.

a. Voluntary response, SRS, stratified, cluster

b. Convenience, SRS, stratified, cluster

c. Convenience, cluster, SRS, stratified

d. Convenience, SRS, cluster, stratified

e. Cluster, SRS, stratified, convenience

Which of the following is a categorical variable?

a. The weight of an automobile

b. The time required to complete the Olympic marathon

c. The fuel efficiency (in miles per gallon) of a hybrid car

d. The brand of shampoo purchased by shoppers in a grocery store

e. The closing price of a particular stock on the New York Stock Exchange

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