I need help with this, thanks.

Click on this link to download the dataset in spreadsheet format that you are going to analyze. The first column represents the date, the second is the monthly percentage return of the Berwyn mutual fund (ticker:BERWX) and the remaining columns represent the US equity market return (MKT), Small-minus-Big (SMB), and High-minus-Low (HML) (see Ken French website for more details). The aim of this exercise is to use regression analysis to evaluate the exposure of the mutual fund returns to the risk factors (MKT, SMB, HML) and classify the style of the fund. The regression model is: mutual fund returns = alpha + beta1 * MKT + beta2 * SMB + beta3 * HML + error where the intercept alpha in the context of this model represents the risk-adjusted return and the slopes beta are the exposures of the mutual fund to the risk factors. Answer the following questions: The sign of the SMB coefficient indicates that the BERWX fund manager overweights - relative to the market factor - (type SMALL or LARGE) capitalization stocks while for HML the estimated coefficient indicates the manager overweights (type HIGH or LOW) Book-to-Market ratio stocks. Test the null hypothesis that the exposure of the fund to HML is equal to 0 against the alternative that it is different from 0 at the 10% significance level. Is the factor significant? (type YES or NO) Use the p-value of the intercept estimate (alpha) to test the one-sided hypothesis that alpha is less or equal to zero against the alternative that it is positive. Since the sign of the estimate of alpha is and the alternative hypothesis requires to reject the null hyp. for (type POSITIVE or NEGATIVE) values of alpha: does it matter how large the p-value is to decide to reject the null hypothesis? (type YES - if it matters- or NO - if it doesn't) Test the null hypothesis that the coefficient of MKT, beta1, is lower or equal to -1 against the alternative that it is larger. The test statistic for this hypothesis is and at 5% significance level we (type REJECT or DO NOT REJECT) the null hypothesis Test the overall significance of the regression model, that is, HO: beta1 = beta2 = beta3 = 0 against the alternative that at least one of the coefficients is different from zero. Calculate the F statistic for this hypothesis which is F distributed with 3 degrees of freedom in the numerator and 253 in the denominator. At 1% level the null hypothesis is (type REJECT or DO NOT REJECT)SUMMARY OUTPUT Regression Statistics Multiple R 0.91527467 R Square 0.83772772 Adjusted R S 0.83580354 Standard Err 2.12737981 Observations 257 ANOVA df SS MS F Significance F Regression 3 5911.11119 1970.3704 435.369305 1.454E-99 Residual 253 1145.01345 4.52574487 Total 256 7056.12464 Coefficients itandard Errol t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.0321003 0.13477757 -0.2381723 0.81194026 -0.2975292 0.23332861 -0.2975292 0.23332861 MKT 0.88905488 0.03115135 28.539851 4.6045E-81 0.82770589 0.95040388 0.82770589 0.95040388 SMB 0.66283582 0.04194454 15.8026708 1.3387E-39 0.58023087 0.74544076 0.58023087 0.74544076 HML 0.76569822 0.04452936 17.1953568 2.0119E-44 0.67800277 0.85339366 0.67800277 0.85339366