Empirical rcises1.doc

Empirical Exercises1By Yanan Zhang, 142106901018. The dataset TeachingRatings.xls contains data on course evaluations, course characteristics, and professor characteristics for 463 courses at the UT Austin. Please read the detailed description given in TeachingRatings Description.pdf. You will investigate how course evaluations are related to the professors beauty.(a) Draw a scatterplot of average course evaluations (Course_eval) on the professors beauty. Any relationship between two variables?(b) Run a regression of Course_eval on Beauty. Interpret the estimated parameters?(c) Suppose Prof. Wooldridge has an average value of Beauty, while Prof. Zhus value of Beauty is one standard deviation below the average. Predict Prof. Wooldridges and Prof. Zhus course evaluation.(d) Does Beauty explain a large fraction of the variation in evaluation across courses? Explain.Coding as follows:x=xlsread(TeachingRatings,E2:E464);y=xlsread(TeachingRatings,F2:F464);x_mean=mean(x);y_mean=mean(y);x_std=std(x);y_std=std(y);scatter(x,y);p=polyfit(x,y,1);x1=ones(463,1),x;b,bint,r,rint,stats=regress(y,x1);b) So 1=3.9983, 0=0.1330, course_eval=0.1330+3.9983beauty.The regression result indicates that beauty has a positive influence on course_eval and when beauty increase 1 unit, course_eval is expected to increase 3.9983 units.c)Prof. Wooldridge: beauty=6.2635e(-8), course_eval =0.1414Prof. Zhu: beauty=6.2635e(-8)-0.7886, course_eval = -3.0117d)because of R2=0.0357, the goodness of fit is low. Beauty cant explain course evaluation well.9. Use the dataset CHARITY.xls (with a description file charity.txt) to answer the following questions:(a) What is the average gift in the sample of 4268 people? What is the percentage of people gave no gifts?(b) What is the average mailings per year? What are the minimum and maximum values?(c) Estimate the model gift =0 +1mailsyear +u by OLS and report results, including the sample size and R2.(d) Interpret the slope coefficient. If each mailing costs one guilder, is the charity expected to make a net gain on each mailing? Does this mean the charity makes a net gain on every mailing? Explain.(e) What is the smallest predicted charitable contribution in the sample? Using this simple regression analysis, can you ever predict zero for gift?a)The smallest predicted charitable contribution in the sample is zero. Using this simple regression analysis, I cant predict zero for gift for both1 and 00.gift=xlsread(CHARITY,B2:B4269);mean_gift=mean(gift)mean_gift =7.4445gift=xlsread(CHARITY,B2:B4269);count=0;length=4268;for i=1:length if(gift(i)=0) count=count+1; endendcountratio=1-count/numel(gift)ratio=0.4b)mailsyear=xlsread(CHARITY,F2:F4269);mailsyear_mean=mean(mailsyear);mailsyear_max=max(mailsyear);mailsyear_min=min(mailsyear);so the average mailings per year equals to 2.0496. The minimum value is 0.25 and the maximum is 3.5.c)y=xlsread(CHARITY,B2:B4269);x=xlsread(CHARITY,F2:F4269);x_mean=mean(x);y_mean=mean(y);x_std=std(x);y_std=std(y);scatter(x,y);p=polyfit(x,y,1);x1=ones(4268,1),x;b,bint,r,rint,stats=regress(y,x1);gift=2.6495+2.0141mailsyear.R2=0.0138Sample size=4238d)The charity is expected to make a net gain on each mailing because 10. However, this doesnt mean the charity makes a net gain on every mailing because 1mailsyear just represents the expectation of gift.e)The smallest predicted charitable contribution in the sample is 0. Using this simple regression analysis, you cant predict zero for gift.10. Something real. Collect the financial information from the annual reports of selected public firms. Clearly state your data source and be prepared for peer validation.(a) Pick all listed companies whose headquarters are in the province that your personal identification card is designated to.(b) Collect the annual reports in the year that you entered into your undergraduate college.(c) Tabulate the cross sectional descriptive statistics of the following financial variables:_ Total Assets_ Total Liability_ Earnings Per Share_ Return on Asset_ Return on Equity(d) Based on the information from the same annual report, you may speculate, hypothesize, or simply guess another THREE variables or ratios (not necessarily financial ones) that, you believe, are the best indicators to explain the stocks performance in the next calendar year. Briefly explain your logic. Please also tabulate their cross sectional summary statistics.totalassettotalliabilityEPSROEROAcurrentratioebitda_incomeEPSYOYnetprofit_salesmean6341.62353533.0680.55625915.924969.7328471.66433716.4831572.454548.926446var153304895491841080.237853310.295750.816831.994646171.2989126285.571.27814std12276.2586953.4510.48355117.465297.0679221.40029912.97673352.34238.370785mode7116.16424369.9740.787816.12436.37591.31616.53798.18463.9685median2375.53621173.3410.451613.58418.21761.292613.8913645.9141max70395.36142396.62.37127.380942.53718.512382.2612125040.8472min412.476145.5022-0.43-19.428-6.32390.2386-6.8843-2250-14.993211. Simulation I: There are two normally distributed random variables x1N(0, 1) and x2N(0, 1.5). Write program codes to draw two random sequences数列 from the two random variables with 200 observations each. Define y = 1/2 (x1 + x2).(d) Please submit the codes that generate the above results and prepare for the cross-validation交叉验证 from your peers.a)x1=normrnd(0,1,1,200);x2=normrnd(0,1.5,1,200);y=(x1+x2)*0.5;var1=var(x1);var2=var(x2);var3=var(y);（var1+var2）/4=0.860175, closed to var(y)b)varof3 = ;for i=1:100x1= normrnd(0,1,1,200);x2= normrnd(0,1.5,1,200);y= (x1+x2)*0.5;varonce=var(x1) var(x2) var(y);varof3 =varof3; matrix;endmeanvar1=mean(varof3(1:100,1)meanvar2=mean(va