1.25 Refer to Exercise 11.24. Fit a regression model relating yield to the absolute deviation from the ideal planting date, that is, x 5 |D|. a. Compute the estimated linear regression model ^ y 5 ^b0 1 ^b1x. b. Estimate s2e. c. Estimate the standard error of b ^ 1. d. Place a 95% confidence interval on b1. e. Test the hypothesis that there is a linear relationship between yield per acre and absolute deviation from the ideal planting date. Use a 5 .05.
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.
11.25 Refer to Exercise 11.24. Fit a regression model relating yield to the absolute deviation
from the ideal planting date, that is, x 5 |D|.
a. Compute the estimated linear regression model ^ y 5 ^b0 1 ^b1x.
b. Estimate s2e.
c. Estimate the standard error of b ^ 1.
d. Place a 95% confidence interval on b1.
e. Test the hypothesis that there is a linear relationship between yield per acre and
absolute deviation from the ideal planting date. Use a 5 .05.
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