$/*$ Generated Code $($IMPORT$)*/$

$/*$ Source File: IPhone.xls $*/$

$/*$ Source Path: $/$home$/$u$63768975/$my$\_$shared$\_$file$\_$links$/$u$63733888/$Data $*/$

$/*$ Code generated on: $14/02/202422$:$29*/$

$\%$web$\_$drop$\_$table$($WORK$.$IMPORT$)$;

FILENAME REFFILE $\text{'}/$home$/$u$63768975/$my$\_$shared$\_$file$\_$links$/$u$63733888/$Data$/$IPhone$.$xls$\text{'}$;

PROC IMPORT DATAFILE$=$REFFILE

DBMS$=$XLS

OUT$=$WORK.IMPORT;

GETNAMES$=$YES;

RUN;

PROC CONTENTS DATA$=$WORK.IMPORT; RUN;

$\%$web$\_$open$\_$table$($WORK$\mathrm{.}4.$ The fourth step is to collect the data. Your professor has provided you with a data set of iPhone auctions that have taken place over the last three weeks on eBay. Are you concerned that the observations may not be comparable since they come from different time periods? Why or why not?

a$)$ Locate and open the $$iPhone$$ dataset from the shared folder on SAS On Demand.

b$)$ Let$$s explore the data. To explore the data, calculate $$summary statistics.$$

i$.$ See what variables are available

ii$.$ Verify that the following variables are available:

PRICEi $-$ the price at which the ith iPhone sold on eBay

NEWi $$ Yes or No

SCRATCHi $$ a dummy variable equal to $1$ if the ith iPhone had a minor cosmetic defect, $0$ otherwise

BIDRSi $-$ the number of bidders on the ith iPhone

c$)$ Understand the data and the values the variables take. For example, what are variables$$ mean, median, minimum, and maximum values? Are there any missing values?

d$)$ Assume that you choose the following specification:

PRICEi $=\backslash$beta $0+\backslash$beta $1$NEWi $+\backslash$beta $2$SCRATCHi $+\backslash$beta $3$BIDRSi $+\backslash$epsi i

Do you see any issue that may affect your ability to use the variable NEW?

e$)$ Transform the variable NEW into a numeric variable that takes the value of $1$ if the iPhone is NEW and $0$ otherwise.

You may use the following code to create the dummy variable:

$/*$ Create dummy vaiable$*/$

data Dataset$\_$Name; set Dataset$\_$Name; $/*$Dataset$\_$Name if your data set name$*/$

if NEW$="$No$"$ then New$\_$dummy$=0$;

else if NEW$=$"Yes" then New$\_$dummy$=1$;

run;

$/*$ Check the new created dummy$*/$

proc freq data$=$Dataset$\_$Name;

tables NEW New$\_$dummy;

run;

If you want to know more about how to create dummy variables, read $$https:$//$stats$.$oarc.ucla.edu$/$sas$/$faq$/$is$-$there$-$a$-$quick$-$way$-$to$-$create$-$dummy$-$variables$/$

$5.$ The fifth step is to estimate the regression model. Use the same specification you defined under $4$d$)$

PRICEi $=\backslash$beta $0+\backslash$beta $1$NEWi $+\backslash$beta $2$SCRATCHi $+\backslash$beta $3$BIDRSi $+\backslash$epsi i

a$)$ Write the estimated regression equation.

b$)$ Do the estimated coefficients correspond to your expectations? Explain.

c$)$ What is the overall quality of the regression equation you have estimated? How can you tell?

$6.$ The sixth step is to document the results. Do not simply copy and paste the SAS results. Write your results as instructed in our textbook $3\mathrm{.}1$ step $6.$IMPORT$)$;