Write the linear model to test the hypothesis that there is no treatment effect. Clearly describe each term in the model, and the range of the subscripts. Write the null hypothesis that you are testing.
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.
- Write the linear model to test the hypothesis that there is no treatment effect. Clearly describe each term in the model, and the
range of the subscripts. Write the null hypothesis that you are testing.
Call:
lm(formula = score ~ list, data = hearing)
Residuals:
Min 1Q
-14.7500 -5.5833 -0.2083 6.3333 16.4167
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 32.750 1.612 20.315 < 2e-16 ***
listList2 -3.083 2.280 -1.352 0.17955
listList3 -7.500 2.280 -3.290 0.00142 **
listList4 -7.167 2.280 -3.144 0.00225 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 7.898 on 92 degrees of freedom
Multiple R-squared: 0.1382, Adjusted R-squared: 0.1101
F-statistic: 4.919 on 3 and 92 DF, p-value: 0.00325
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