Anyone know SAS software, I'm trying to solve my assignment, I'm getting error. Can anyone help? I will be grateful :(

Wisconsin COVID-19 data by census tract boundary

Data is updated at 2:00PM CDT daily. All data are laboratory-confirmed cases of COVID-19 that we freeze once a day to verify and ensure that we are reporting accurate information. The number of people with positiveegative test results includes only Wisconsin residents who had their results reported electronically to DHS. Here are descriptions of the variables in the data.

Variable Name	Variable Description
GEOID	Geographic ID
State	State
CENSUS_TRACT	Census Tract Number
COUNTY	County Name
DATE	Last Date of Report
POSITIVE	Number of Positive on COVID19 Test
NEGATIVE	Number of Negative on COVID19 Test
DEATHS	Number of Deaths by COVID19
HOSP_YES	Number of Hospitalized by COVID19
HOSP_NO	Number of Not Hospitalized by COVID19
HOSP_UNKNOWN	Unknown Number of Hospitalized by COVID19
AREA_LAND	Land Area Size
AREA_WATER	Water Area Size
POPULATION	Total Population
POP_LT18	Percent of Population that is Less Than 18 Years
POP_65P	Percent of Population that is 65 Years and Over
HOUS_NO_VEH	Percent of households with no vehicle available
ADULT_LIMITED_ENGLISH	Percent of adults 18 years and over who have limited English ability
ADULT_SPANISH_LENG	Percent of adults 18 years and over who speak Spanish and have limited English ability
POP_BELOWPOV	Percent of Population whose income in the past 12 months is below poverty level
POP_DISABILITY	Percent of Population with a Disability
POP_MEDICAD	Percent of Population with Medicaid/Means-Tested Public Coverage
POP_MEDICARE	Percent of Population with Medicare Coverage
POP_HEALTHINS	Percent of Population with No Health Insurance Coverage
HOUS_NOSMARTPHN	Percent of Households that Have No Smartphone
HOUS_NOINTERNET	Percent of Households with No Internet Access

Here is the SAS code to load the data into your SAS program.

filename webdat url "https://bigblue.depaul.edu/jlee141/econdata/eco520/COVID19_WI_Census.csv" ;

proc import datafile=webdat out = COVID19 DBMS = csv replace ; run ;

run ;

/*Select 500 randomly selected census tracts in WI using YourDePaulID */

proc surveyselect data= COVID19 method=srs seed= YourDePaulID

N=500 out= MYCOVID19 ;

run;

proc contents data=MYCOVID19 ;

run ;

3. Predictive Analytics using Regression Model (9 points} Use only TRAIN data (70%] to estimate the models and use the TEST data (30%( to perform the out-ofsample prediction Estimate regression models to predict the number of COVID19 confirmed cases per 1000 persons for the census tract using the demographic variables. None of the variables related to COVID19 can be used to predict the COVID19 related dependent variables, but only use variables start with PCP, HOUS, ADULT, or AREA as independent variables. 1} 2} Find the best regression models to explain the variation of the number of confirmed cases per 1000 persons by the census tract. You can use any variables such as nonlinear variables and cluster variables to make the best models. Model 1: Simple Regression Model with your choice of an independent variables Model 2: Your own choices of variables Model 3: Including all possible independent variables Model 3: Stepwise Model 4: adjusted R square Perform the out of sample prediction using the observation that were not used in the estimation (test dataset}. Find the following statistics and compare the results. Which model is the best performing model in terms of the following statistics? a. MSE (mean square error} b. RMSE (root mean square error} c. MPE (mean peroentage error} d. MAE (mean absolute error) Find the best regression models to explain the variation of the number of hospitalized per 1000 persons by the census tract. You can use any variables such as nonlinear variables and cluster variables to make the best models. Model 1: Simple Regression Model with your choice of an independent variables Model 2: Your own choices of variables 2 Model 3: Including all possible independent variables Model 3: Stepwise Model 4: adjusted R square Perform the out of sample prediction using the observation that were not used in the estimation (test dataset}. Find the following statistics and compare the results. Which model is the best performing model in terms of the following statistics