Using 27 observations on each variable, a computer program generated the following multiple regression model. y = 52.8 + 6.67x - 2.05x,+4.69.x3- 7.22x4 If the standard errors of the coefficients of the independent variables are, respectively, 2.72, 1.35, 3.19, and 2.96, can you conclude that the independent variable x, is needed in the regression model? Let B,, B, ..., B, denote the coefficients of the 4 variables in this model, and use a two-sided hypothesis test and significance level of 0.10 to determine your answer. |(a) State the null hypothesis H, and the alternative hypothesis H,. B H :0 H :0 (b) Determine the type of test statistic to use. (Choose one) ▼ O=0 OSO (c) Find the value of the test statistic. (Round to two or more decimal places.) O
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.
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