(Let B = beta)
The finance department of an automobile insurance company uses a multiple regression model to estimate the total number of accident claims that will be filed each month. Based on the most recent 17 months of claims data, the company has selected 4 independent variables that it believes are related to accident claims. Let B1, B2 ... B4 denote the coefficients of the 4 variables in this model. When this data is entered into a regression software program, the error sum of squares (SSE) associated with the model is reported to be 78.22 and the corresponding regression sum of squares (SSR) is 204.94. Using a significance level of 0.01, can you conclude that at least one of the independent variables in the model provides useful (i.e., statistically significant) information for predicting monthly accident claims?
Perform a one-tailed test. Then fill in the blanks below.
Carry your intermediate computations to at least three decimal places and round your answers as specified in the table
Type of test statistic (chi square, T, Z, F) degrees of freedom __
The value of the test statistic (round to at least two decimal places)___
The critical value at the 0.01 level of significance (round to at least two decimal places)___
H1: At least one BI is different from zero.
Type of test ...
The solution provides the answers to the blank spaces about multiple regression for an F test.