Multiple Regression Analysis Hypothesis Testing

A financial analyst is conducting a multiple regression analysis to understand the impact of several independent variables on the return of a portfolio. The independent variables included are: market return (MR), interest rates (IR), and GDP growth (GDP). After running the regression, the analyst forms the following hypothesis regarding the coefficient of market return:

$$H_0: eta_{MR} = 0$$

$$H_1: eta_{MR} eq 0$$

Where:

- $H_0$ is the null hypothesis stating that the market return does not have a statistically significant effect on portfolio returns.

- $H_1$ is the alternative hypothesis, indicating that market return does have a significant effect.

The analyst finds the estimated coefficient of market return to be 0.12 with a standard error of 0.05. The t-statistic for this coefficient is computed as the estimated coefficient divided by the standard error. Based on a significance level of 0.05, what conclusion should the analyst draw regarding the null hypothesis?