In Exercises, presume that the assumptions for regression inferences are met.Plant Emissions. Following are the data on plant weight and quantity of volatile emissions from Exercise. x 57 85 57 65 52 67 62 80 77 53 68 y 8.0 22.0 10.5 22.5 12.0 11.5 7.5 13.0 16.5 21.0 12.0 a. Obtain a point estimate for the mean quantity of volatile emissions of all (Solanum tuberosum) plants that weigh 60 g.b. Find a 95% confidence interval for the mean quantity of volatile emissions of all plants that weigh 60 g.c. Find the predicted quantity of volatile emissions for a plant that weighs 60 g.d. Determine a 95% prediction interval for the quantity of volatile emissions for a plant that weighs 60 g.ExerciseApplying the Concepts and SkillsIn Exercises, we repeat the information from Exercises. For each exercise here, discuss what satisfying Assumptions 1–3 for regression inferences by the variables under consideration would mean.
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
In Exercises, presume that the assumptions for regression inferences are met.
Plant Emissions. Following are the data on plant weight and quantity of volatile emissions from Exercise.
| x | 57 | 85 | 57 | 65 | 52 | 67 | 62 | 80 | 77 | 53 | 68 |
| y | 8.0 | 22.0 | 10.5 | 22.5 | 12.0 | 11.5 | 7.5 | 13.0 | 16.5 | 21.0 | 12.0 |
a. Obtain a point estimate for the mean quantity of volatile emissions of all (Solanum tuberosum) plants that weigh 60 g.
b. Find a 95% confidence interval for the mean quantity of volatile emissions of all plants that weigh 60 g.
c. Find the predicted quantity of volatile emissions for a plant that weighs 60 g.
d. Determine a 95% prediction interval for the quantity of volatile emissions for a plant that weighs 60 g.
Exercise
Applying the Concepts and Skills
In Exercises, we repeat the information from Exercises. For each exercise here, discuss what satisfying Assumptions 1–3 for regression inferences by the variables under consideration would mean.
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