如何最快的判定price sales是唯一一个signifcant 的independent variable？

NO.PZ202208220100000507 问题如下 Your seconrouninterview for the Junior Quantitative Analyst position went well, anthe next y, you receive email from the investment firm congratulating you for making it this far. You are one of four remaining cantes from more th100 who appliefor the position. Because the position involves quantitative analysis, you are given assignment to complete within 72 hours. You are provia taset antaskewith creating two logistic regression mols to prewhether ETF will a “winning” fun this, whether the ETF’s monthly return will one stanrviation or more above the memonthly return across all ETFs in the taset, or whether the ETF will “average” funThe variables in the taset are follows:For the first logistic regression, you are asketo use all the inpennt variables, except for the funsize mmy variables (small_funanmeum_fun. For the seconlogistic regression, you are asketo use all the inpennt variables except the funsize continuous variable (net assets). You use a stanrsoftware package (in Python or R) to velop the logistic regression mols. Your results are follows: termine, using the significant variable(s) in Logistic Regression 2 anthe information provi whiof the following is closest to the probability of the Alpha ETF being a winning funanwhether it woulclassifiea winning funAlpha ETF variable values: small_fun= 0, meum_fun= 0, portfolio_stocks= 99.3%, portfolio_bon = 0.7%, price_earnings = 25.0, price_book =1.1, price_sales = 4.0, anprice_cashflow = 5.7.Use significanlevel of 5% anprobability thresholfor being a winner of 65%. A.27.4%, anthe Alpha ETF is not classifiea winning fun B.36.0%, anthe Alpha ETF is not classifiea winning fun C.82.2%, anthe Alpha ETF is classifiea winning fun B is correct. Besis the significant intercept, the only significant (5% level) variable in Logistic Regression 2 is price_sales. Using these factors, the probability of this ETF being a winning funis calculateto 35.95%, follows:Because this probability is well below the 65% thresholfor being a winner, the Alpha EFT woulnot classifiea winning fun 只有price_sales的系数是落在[0.025，0.975]的区间里的。从这点看只有price_sales的系数为0

NO.PZ202208220100000507 问题如下 termine, using the significant variable(s) in Logistic Regression 2 anthe information provi whiof the following is closest to the probability of the Alpha ETF being a winning funanwhether it woulclassifiea winning funAlpha ETF variable values: small_fun= 0, meum_fun= 0, portfolio_stocks= 99.3%, portfolio_bon = 0.7%, price_earnings = 25.0, price_book =1.1, price_sales = 4.0, anprice_cashflow = 5.7.Use significanlevel of 5% anprobability thresholfor being a winner of 65%. A.27.4%, anthe Alpha ETF is not classifiea winning fun B.36.0%, anthe Alpha ETF is not classifiea winning fun C.82.2%, anthe Alpha ETF is classifiea winning fun B is correct. Besis the significant intercept, the only significant (5% level) variable in Logistic Regression 2 is price_sales. Using these factors, the probability of this ETF being a winning funis calculateto 35.95%, follows:Because this probability is well below the 65% thresholfor being a winner, the Alpha EFT woulnot classifiea winning fun 我记得课上有个地方说的是，不管系数是不是显著，最后预测都按照原来的模型带数字进去预测，这里为什么要简化不太明白

NO.PZ202208220100000507 问题如下 Your seconrouninterview for the Junior Quantitative Analyst position went well, anthe next y, you receive email from the investment firm congratulating you for making it this far. You are one of four remaining cantes from more th100 who appliefor the position. Because the position involves quantitative analysis, you are given assignment to complete within 72 hours. You are provia taset antaskewith creating two logistic regression mols to prewhether ETF will a “winning” fun this, whether the ETF’s monthly return will one stanrviation or more above the memonthly return across all ETFs in the taset, or whether the ETF will “average” funThe variables in the taset are follows:For the first logistic regression, you are asketo use all the inpennt variables, except for the funsize mmy variables (small_funanmeum_fun. For the seconlogistic regression, you are asketo use all the inpennt variables except the funsize continuous variable (net assets). You use a stanrsoftware package (in Python or R) to velop the logistic regression mols. Your results are follows: termine, using the significant variable(s) in Logistic Regression 2 anthe information provi whiof the following is closest to the probability of the Alpha ETF being a winning funanwhether it woulclassifiea winning funAlpha ETF variable values: small_fun= 0, meum_fun= 0, portfolio_stocks= 99.3%, portfolio_bon = 0.7%, price_earnings = 25.0, price_book =1.1, price_sales = 4.0, anprice_cashflow = 5.7.Use significanlevel of 5% anprobability thresholfor being a winner of 65%. A.27.4%, anthe Alpha ETF is not classifiea winning fun B.36.0%, anthe Alpha ETF is not classifiea winning fun C.82.2%, anthe Alpha ETF is classifiea winning fun B is correct. Besis the significant intercept, the only significant (5% level) variable in Logistic Regression 2 is price_sales. Using these factors, the probability of this ETF being a winning funis calculateto 35.95%, follows:Because this probability is well below the 65% thresholfor being a winner, the Alpha EFT woulnot classifiea winning fun 请问这道题讲解视频链接

NO.PZ202208220100000507 问题如下 termine, using the significant variable(s) in Logistic Regression 2 anthe information provi whiof the following is closest to the probability of the Alpha ETF being a winning funanwhether it woulclassifiea winning funAlpha ETF variable values: small_fun= 0, meum_fun= 0, portfolio_stocks= 99.3%, portfolio_bon = 0.7%, price_earnings = 25.0, price_book =1.1, price_sales = 4.0, anprice_cashflow = 5.7.Use significanlevel of 5% anprobability thresholfor being a winner of 65%. A.27.4%, anthe Alpha ETF is not classifiea winning fun B.36.0%, anthe Alpha ETF is not classifiea winning fun C.82.2%, anthe Alpha ETF is classifiea winning fun B is correct. Besis the significant intercept, the only significant (5% level) variable in Logistic Regression 2 is price_sales. Using these factors, the probability of this ETF being a winning funis calculateto 35.95%, follows:Because this probability is well below the 65% thresholfor being a winner, the Alpha EFT woulnot classifiea winning fun p value小于5%还是2.5%？这个跟单尾双尾有关系吗？另外，我还想问另外一个问题F统计量和t统计量和α相比还是和criticvalue相比？考试时是否会给出criticvalue？

NO.PZ202208220100000507 问题如下 termine, using the significant variable(s) in Logistic Regression 2 anthe information provi whiof the following is closest to the probability of the Alpha ETF being a winning funanwhether it woulclassifiea winning funAlpha ETF variable values: small_fun= 0, meum_fun= 0, portfolio_stocks= 99.3%, portfolio_bon = 0.7%, price_earnings = 25.0, price_book =1.1, price_sales = 4.0, anprice_cashflow = 5.7.Use significanlevel of 5% anprobability thresholfor being a winner of 65%. A.27.4%, anthe Alpha ETF is not classifiea winning fun B.36.0%, anthe Alpha ETF is not classifiea winning fun C.82.2%, anthe Alpha ETF is classifiea winning fun B is correct. Besis the significant intercept, the only significant (5% level) variable in Logistic Regression 2 is price_sales. Using these factors, the probability of this ETF being a winning funis calculateto 35.95%, follows:Because this probability is well below the 65% thresholfor being a winner, the Alpha EFT woulnot classifiea winning fun 为什么全部带进去再算这种不行呢？就因为其他都不显著（除了price_sale）？？另外，我想问下这题的H0是什么？为什么落在拒绝域就是winning？