Question

Potassium and nitrogen are nutrients that are essential for plant health. Suppose that Willard is a soil scientist who is doing research on the relationship between potassium available in a plant and the quantity of nitrogen in the soil surrounding the plants root system. Based on a simple random sample of n = 55 strawberry plants, he has constructed a linear regression model to predict the amount of potassium as a percentage of the available dry matter in the plants from the quantity of nitrogen in the soil in parts per million (ppm). Assume that the requirements for inference for regression have been met. The software he is using indicates that the 99% prediction interval for percent potassium when nitrogen is 23 ppm is (0.58%, 0.79%). How should Willard interpret this prediction interval? O Willard can be 99% confident that the mean percentage of potassium is between 0.58% and 0.79% of available dry matter in the population of all strawberry plants in which soil nitrogen level is 23 ppm. O Willard can be 99% confident that the percentage of potassium will be between 0.58% and 0.79% of available dry matter for a plant chosen at random from the population of all strawberry plants in which soil nitrogen level is 23 ppm. There is a 99% chance that the percentage of potassium is between 0.58% and 0.79% of available dry matter in a single plant randomly chosen from the population of strawberry plants in which soil nitrogen level is 23 ppm. O Willard can be 99% confident that the slope of the population regression line is between 0.58% and 0.79%. O There is a 90% chance that the mean percentage of potassium is between 0.58% and 0.79% of available dry matter in the population of strawberry plants in which soil nitrogen level is 23 ppm.

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