                               UNPUBLISHED

                  UNITED STATES COURT OF APPEALS
                      FOR THE FOURTH CIRCUIT


                               No. 12-4866


UNITED STATES OF AMERICA,

                Plaintiff - Appellee,

          v.

OBINNA FELIX UKWU,

                Defendant - Appellant.



Appeal from the United States District Court for the District of
Maryland, at Baltimore.    Catherine C. Blake, District Judge.
(1:12-cr-00134-CCB-1)


Submitted:   August 21, 2013            Decided:   November 22, 2013


Before NIEMEYER, GREGORY, and DUNCAN, Circuit Judges.


Affirmed by unpublished per curiam opinion.


Bruce Fein, BRUCE FEIN & ASSOCIATES, INC., Washington, D.C.,
for Appellant.    Rod J. Rosenstein, United States Attorney,
Kathleen O. Gavin, Assistant United States Attorney, OFFICE OF
THE UNITED STATES ATTORNEY, Baltimore, Maryland, for Appellee.


Unpublished opinions are not binding precedent in this circuit.
PER CURIAM:

     Appellant Obinna Ukwu was convicted of twelve counts of

aiding   and    assisting     in   the   preparation    of   false    income    tax

returns.       26 U.S.C. § 7206(2).           Mr. Ukwu was sentenced to 51

months in prison.          He now challenges this sentence, arguing that

the district court erred when it estimated the amount of tax

loss Mr. Ukwu caused.           Because a preponderance of the evidence

supports the district court’s estimate, we affirm the sentence.



                                         I.

     Mr. Ukwu was an officer with the Maryland State Division of

Corrections, but in 2006, he started an accounting business as

side employment.           The business offered tax return preparation

services,      and   Mr.    Ukwu   operated     the   business      until    midway

through 2010, when his legal problems began.                 In the intervening

years,   business      boomed:      in    2006,   his   revenue      was    roughly

$8,000, but by 2009, it soared to $175,000.

     A criminal investigation in 2010 revealed that Mr. Ukwu’s

business    was      less    criminally       successful     than    successfully

criminal.      On many of his clients’ returns, Mr. Ukwu would claim

fictional business losses in order to garner tax benefits.                       At

trial,   the    vast   majority     of    witnesses     testified     that    these

losses were entirely false and that they were not aware that

Mr. Ukwu had invented these numbers on their returns.

                                          2
       Mr. Ukwu’s malfeasance went beyond false business losses.

Mr. Ukwu claimed false charitable deductions on his clients’

forms.        He also committed tax fraud on his own income taxes,

filing a joint return for his wife and himself, but also filing

a   separate     individual      return    for    his    wife     under    a    different

name.       Finally,     Mr.    Ukwu   took      fees    from    his    clients’       bank

accounts and refund checks without notification.

       After Mr. Ukwu’s jury conviction, the government estimated

how much money Mr. Ukwu took from federal and state coffers.                                It

concluded that Mr. Ukwu’s criminal behavior created tax losses

of $2.1 million, which corresponds to a base offense level of 22

under § 2T4.1 of the United States Sentencing Guidelines Manual.

       On     appeal,    Mr.   Ukwu    takes     issue    with    the     $2.1      million

estimate, arguing that a preponderance of the evidence shows

that    his    ill-gotten      gains   amounted     to    less     than    $1       million.

Specifically,      he    argues    that    the    district       court’s       method       of

estimating       the    tax    shortfall   was     unsound       because       it    used   a

small, flawed sample of tax returns to make inferences about

another 1000 returns that he prepared.                     Based in part on its

estimate, the district court sentenced Mr. Ukwu to 51 months in

prison.       Mr. Ukwu filed a timely appeal.




                                           3
                                                II.

       We have jurisdiction to review Mr. Ukwu’s sentence under 28

U.S.C. § 1291 and 18 U.S.C. § 3742.                            The government has the

burden of establishing the amount of tax loss by a preponderance

of the evidence.            United States v. Mehta, 594 F.3d 277, 281 (4th

Cir. 2010).           The district court need not calculate the amount

with     a     pharmacist’s          precision:         the    sentencing        guidelines

require only a reasonable estimate.                      Id.     Further, the district

court may consider any relevant information regardless of its

admissibility,         provided          that   the     information     is    sufficiently

reliable.       Id.

       While we generally review for clear error, Mr. Ukwu did not

challenge the district court’s tax loss estimate at sentencing.

Therefore,       we    will     apply      a    plain    error    standard      of     review.

United       States    v.     Slade,      631   F.3d    185,     188   (4th     Cir.    2011).

Mr. Ukwu must demonstrate that an error was made, that the error

was plain, and that the error affected his substantial rights.

Id.    at     190.      In     the     sentencing       context,       an   error      affects

substantial          rights    if    a    different       sentence      would    have     been

imposed absent the error.                 Id.    In addition, even if these three

elements are met, we retain discretion over whether to correct

the forfeited error and do not exercise this discretion “unless

the error seriously affects the fairness, integrity or public

reputation of judicial proceedings.”                          United States v. Olano,

                                                 4
507    U.S.        725,   732    (1993)    (internal        quotations          and    citations

omitted).

       Mr. Ukwu takes issue with how the district court reached

its conclusion that his crimes caused over $1 million in tax

losses.        The sentencing court faced a difficult problem because

of the sheer size of Mr. Ukwu’s potential fraud.                                       Mr. Ukwu

prepared       roughly          1,000    tax     returns         that    reported       business

losses, but the sentencing court and the IRS do not have time to

audit each return, interview each taxpayer, and identify the

extent of Mr. Ukwu’s crimes.                   As a result, the government had to

rely     on    sampling          techniques      to       make     inferences         about    the

universe of 1,000 tax returns.                       Essentially, the government had

to take a spoonful of sauce out of the pot to assess whether the

whole batch was spoiled.

       The     government         used     two       samples      of     Mr.     Ukwu’s       1,000

prepared       tax    returns      to    answer      the    following          question:       how

often did Mr. Ukwu invent Schedule C losses from whole cloth?

First, the government relied on a sample of 18 returns that were

used at Mr. Ukwu’s criminal trial.                         These returns all reported

Schedule       C     losses     and     contained      loss      descriptions         that    were

vague, undocumented, and suspicious.                             Based on the testimony

from the taxpayers involved, the government concluded that 16

out    of     18    returns      had    Schedule      C    losses       that    were    entirely

false.        The two remaining returns were disputed.                            Using these

                                                 5
numbers, the government found that 88.88% of the returns in this

sample used entirely false Schedule C losses.                   Note, however,

that       the   returns    investigated      at     trial   were   chosen   for

investigation specifically because they contained very high tax

loss amounts.        Thus, this was not a random sample of returns.

       To    solve   this   problem,    the    government    then   collected   a

random sample of returns to confirm its initial findings.                    The

government drew 24 returns from the universe of 1,000 returns

that contained Schedule C losses. 1            Then, investigators analyzed

these returns and found that every single one had large Schedule

C losses that were vague, undocumented, and suspicious.                      That

is,    these     returns    exhibited    the       same   pattern   questionable

Schedule C descriptions as the non-random sample of returns that

were investigated at trial.


       1
        Specifically, the investigators alphabetized the returns
by the first name of the taxpayer, then drew one out of every
fifty returns.    This technique passes muster, though it is not
perfect.    Mr. Ukwu is Nigerian, and many of his clients were
Nigerian immigrants.    If these immigrants were more likely to
have the same first name, or the same first letter of their
first name, and if Mr. Ukwu was more likely to file false
returns on immigrants’ forms, as the district court suggested,
then the sampling technique would be problematic.        However,
given the burden of proof—simply a preponderance of the
evidence—it is more likely than not that this issue was not so
grave    that  it   affected  the   outcome  of  the   sentencing
calculation. Thus, while this technique does not warrant
reversal here, future sentencing courts should be wary of
accepting at face value that a randomization technique is truly
random.



                                         6
        In   sum,   the   government   analyzed       a   non-random       sample   of

returns at trial and found that 90% of the Schedule C losses

were entirely false.          Then, investigators used a random sample

to confirm this estimate, reasoning that since the random sample

bore the same patterns as the non-random sample, the two samples

likely contained similar levels of fraud.                    That is, since the

random sample looked like the non-random one, and since 90% of

returns in the non-random sample were completely false, then 90%

of the random sample was also likely to be completely false.

        Finally, the government used this 90% number to calculate

Mr. Ukwu’s tax loss estimate.           The investigators could establish

that among the 1000 returns where a Schedule C loss was claimed,

Mr. Ukwu claimed roughly $16.4 million in Schedule C losses.                        If

90% of these losses were entirely fabricated, then this means

that     roughly    $14.6    million   of     false       losses    were    claimed.

Assuming the lowest marginal tax rate of 10%, and factoring in

state    tax    losses,     the   estimated   tax     loss    was    roughly    $2.1

million.       Because this estimate is between $1 million and $2.5

million, the district court concluded that Mr. Ukwu merited a

base offense level of 22. U.S.S.G. § 2T4.1.

       Mr. Ukwu takes issue with several methodological moves made

by the government in reaching its $2.1 million estimate.                      First,

he argues that the samples used were too small.                        Second, he

argues that it was error to rely on the non-random sample of

                                        7
returns.         Third, he argues that the government never established

that       the   $14.6     million    in   Schedule        C    losses   were    totally

fraudulent, rather than partially fraudulent.

                                             A.

       As a preliminary matter, we can reject with ease Mr. Ukwu’s

argument that the government’s samples were too small to make a

robust inference about the universe as a whole.                           His argument

has intuitive appeal—how can 24 cases tell us about 1000?                               But

Mr.    Ukwu’s      claim      that   small    sample       sizes    render     estimates

useless is statistically incorrect.                   See David H. Kaye & David

A. Freedman, Reference Guide on Statistics, in Reference Manual

on Scientific Evidence 83, 126 n.145 (2d ed. 2000) (“Analyzing

data from small samples may require more stringent assumptions,

but    there       is    no   fundamental         difference       in”   how    we     make

statistical           inferences     in      small     versus       large       samples).

Certainly,        a     larger   sample      size     is       preferable,     since     it

decreases the odds that one’s sample will be misleading. 2                              See


       2
       Specifically, statisticians teach that larger sample sizes
can cut down on two types of error.         First, there is the
possibility that Mr. Ukwu committed rampant corruption, but by
chance, we end up with a sample of cases where he did nothing
wrong. Sanders, Bendectin, supra, at 342–43. Second, there is
the possibility that Mr. Ukwu committed almost no corruption,
but we happen to end up with a sample of cases in which he
appears to fudge numbers constantly. Id. A larger sample size
decreases the chance of both false negatives and false
positives. Id.



                                             8
Joseph Sanders, The Bendectin Litigation:                       A Case Study in the

Life Cycle of Mass Torts, 43 Hastings L.J. 301, 342–43 (1992).

However, even very small samples can be useful, as any political

polling agency can attest:             in many elections, a sample of 1,000

Americans     can    show,    with      enough     certainty          to    satisfy    the

preponderance of the evidence standard, what is likely to happen

in an election involving over 100 million voters.                              See Nate

Silver, The Signal and the Noise 63 fig.2-4 (2012).                         While 24 is

a   relatively      small    sample,    it      amounts    to    2%    of    the    entire

universe.     This sample size does not paralyze us in our attempts

to make inferences about the universe of all cases.                          See United

States   v.    Littrice,      666    F.3d       1053,   1061      (“[R]equiring        the

government to go through all the needles in the haystack of

materially    fraudulent       and   false       returns   . . .       would       place   a

burden on the government beyond what the preponderance standard

requires.”).        As any chef or statistician can attest, even a

small spoonful of sauce can indicate how much salt to add.

      Mr. Ukwu’s next argument is that the government’s estimate

was erroneous because it relied on a non-random sample, but this

argument is similarly unavailing.                 He cites to Mehta, in which

we questioned a district court’s use of a non-random sample to

estimate the amount of tax loss among a broader universe of

returns.    594     F.3d     277     (4th       Cir.    2010).        In    Mehta,     the

government analyzed a sample of returns that were chosen because

                                            9
they had been audited by the IRS.                      Id. at 282–83.            It calculated

the average tax loss among these returns to be $1,531 and then

concluded        that   the    entire       universe       of      returns       would    have   a

similar average tax loss.               Id.       This was problematic because the

returns     in    the    sample      were       flagged       by    the    IRS     specifically

because they were more likely to contain tax losses.                                     Id.     As

such,    the     average      amount       of    tax    loss       among    this    sample     was

misleading:        the broader universe of returns was likely to have

a   lower    average         tax    loss.       Id.     The     sentencing         court’s      tax

estimate was like using a group of NBA players to estimate the

average height of all Americans.

      Mr. Ukwu is correct that the initial, non-random sample

used in this case is a problematic tool to make inferences about

the amount of tax loss for the broader universe of returns.                                     The

returns        chosen        for     the        non-random          sample       were      chosen

specifically because they had higher tax losses.                                   It could be

that the amount of fraud in these returns was higher than for

the entire universe of returns, so relying on the non-random

sample alone would be problematic.                         However, the government’s

tax loss estimate was based on more than a non-random sample.

The government went out of its way to collect a random sample of

returns     to    bolster      its     initial         estimate.           It    compared      this

random      sample      to    the    original,          non-random         sample,       and   the

government concluded that both groups of returns contained the

                                                 10
same pattern of suspicious, unexplained tax losses.                Though the

government’s original estimate is based on a non-random sample,

the government cleansed this error with the use of a random

sample.     Thus, the district court did not make the sort of

mistake identified in Mehta, and as such, it did not commit

plain error.       See Olano, 507 U.S. at 734 (1993) (“‘Plain’ is

synonymous with ‘clear’ or, equivalently, ‘obvious.’”).

     Mr. Ukwu’s final argument is most challenging.                He admits

that the non-random sample contains 90% falsehoods.                He admits

that the random sample looks similar to the non-random sample.

However, he argues that this similarity alone fails to prove

that in the random sample, all of the unexplained Schedule C

losses were due to criminality.             Instead, these losses might

have been exaggerated instead of false, or due to negligence

instead of fraud.       Mr. Ukwu points to a Seventh Circuit case in

which that court expressed skepticism of a similar methodology.

United    States   v.   Schroeder,   536    F.3d   746,   754–55   (7th   Cir.

2008).

     Mr. Ukwu’s argument fails because the government need only

make a reasonable estimate of the tax loss, and the methodology

here, though imperfect, meets that standard.               U.S.S.G. § 2T1.1

cmt. 1; Mehta, 594 F.3d at 282.             In the eighteen tax returns

investigated at trial, the Schedule C forms Mr. Ukwu prepared

exhibited a suspicious pattern.            Many returns claimed that the

                                     11
taxpayer       worked   as    a    contractor       for   Mary     Kay    or    worked   in

“Nursing Services,” but at trial, the taxpayers testified that

they never worked for Mary Kay and never owned such health care

businesses.          These returns also contained a suspicious pattern

of receipts and expenses.                   The invented businesses often had

revenues that were low or non-existent.                          Nearly all expenses

were     low    or    non-existent.            Labor      costs,     meanwhile,        were

enormous.

       The government’s random sample of tax returns exhibited a

similar or identical pattern.                 Many of the returns listed Mary

Kay as a profession; many more listed nursing services.                                  One

return even listed “General Services” as the profession.                            In the

random    sample,       as    in   the   non-random       sample,        the    businesses

almost always claimed to have zero sales, zero expenses, but

enormous labor costs.              Given these similarities, the sentencing

court made no plain error when it concluded that, just like the

returns     analyzed         at    trial,     the    random      sample        of   returns

contained business losses that were entirely fabricated.                                 See

Olano, 507 U.S. at 734 (“‘Plain’ is synonymous with ‘clear’ or,

equivalently, ‘obvious.’”).

       Further, Mr. Ukwu’s reliance on Schroeder is misguided.                            In

that case, the government used a similar argument to make a tax

estimate:       it found strong evidence of fraud in sample A, found

a similar pattern of losses in sample B, and concluded that

                                             12
sample B was therefore likely to contain fraud.                             536 F.3d at

754–55.       The     Seventh        Circuit      expressed     skepticism       of    this

methodology.         Id. at 755.        However, the court’s reversal in that

case was based not on the sampling methodology but rather on

fundamental legal errors made by the sentencing court.                             Id. at

755.     The district court in that case applied the wrong burden

of proof, apparently concluding “that if evidence is admissible

it proves the truth of the proposition for which it is being

offered.”       Id.       Instead of requiring the government to prove a

tax    loss    by    a    preponderance        of    the   evidence,      the   sentencing

court accepted the government’s estimate without any analysis,

concluding that as long as the evidence was reliable, the tax

loss had been proven.                  Id.        Here, meanwhile, the sentencing

court conducted a careful analysis of the evidence.                              It noted

potential shortcomings in the methodology but concluded that the

estimate       was       more       likely     than     not    to    be     accurate     or

significantly lower than the true tax loss.                         Thus, Schroeder is

inapposite.          Though the government’s methods were not perfect,

its    tax    loss       estimate     was    reasonable.        Further,        unlike   in

Schroeder, the district court’s analysis was careful and legally

sound.        This       is   all    that    is     required   under      the   Sentencing

Guidelines.         U.S.S.G. § 2T1.1 cmt. 1; Mehta, 594 F.3d at 282.




                                               13
                                         B.

       Finally, even if Mr. Ukwu is correct that the tax loss

estimate      has    methodological     shortcomings,       these    errors      were

harmless and therefore did not affect his substantial rights.

Slade, 631 F.3d at 190.          The government estimated a tax loss of

$2.1 million.        Mr. Ukwu argues that it is possible that most of

the claimed Schedule C losses were not criminal, but instead

were   legitimate      losses,    or    at    least   negligent      ones.         For

example, a client might have had $1,000 in legitimate business

losses, but Mr. Ukwu might have pumped the number up to $2,000.

       Mr. Ukwu might be correct, but the $2.1 million estimate is

so conservative that even if he is right, the total tax losses

are still likely to be above $1 million, which is the level of

loss   that    is    necessary   for    his    sentencing    range.           U.S.S.G.

§ 2T4.1.        First,    in   addition       to   false   Schedule       C   losses,

Mr. Ukwu      used    false    charitable      deductions     on    his       clients’

returns, and none of these deductions were counted towards the

$2.1 million figure.           In one case, Mr. Ukwu claimed a $10,000

charitable gift that was entirely fabricated, suggesting that

his Schedule A fraud might be significant.                  Similarly, the $2.1

million figure also excludes the fraud Mr. Ukwu committed on his

own tax returns, which amount to roughly $100,000.

       Further, the court’s estimate only looked at Mr. Ukwu’s

returns from 2006 to 2008.             He continued to prepare tax returns

                                         14
in 2009 and for part of 2010, and none of these returns were

factored in to the tax loss estimate.                     Factoring in Mr. Ukwu’s

2009 returns increases the estimated loss to roughly $3 million.

        Most importantly, the $2.1 million figure was calculated by

applying    a    10%     marginal    tax    rate    to    the     entire   universe     of

returns.       This is likely a gross underestimate of the true tax

liability, since many of the returns were likely to have been

subject to a 25% marginal tax rate or higher.                        This alone could

increase the estimated tax loss by more than two-fold.                            In sum,

even if Mr. Ukwu’s arguments are valid, his estimated tax losses

are more likely than not to be well over $1 million.                             As such,

the     district       court’s      alleged       error     did     not     affect     his

substantial rights.

        For the foregoing reasons, we affirm the judgment of the

district    court.        We     dispense    with    oral    argument      because     the

facts    and    legal     contentions       are    adequately      presented      in   the

materials       before    this    court     and    argument       would    not   aid   the

decisional process.

                                                                                 AFFIRMED




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