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Concepts for further analysis:
1. Describe the structure of a cereal grain; identify the parts of
the grain that contribute to fiber, starch, and rancidity.
2. How are additives applied to grain products if the additives
are not stable when heated? Explain.
3. Explain how cereal grains are used in the American food
supply. Briefly outline each.
4. Identify the three grains of primary importance in the world
today. (List them)
5. Based on your answer from question #4, explain the
following for each grain:
a. How is the grain classified
b. How is the grain grown (only for wheat)
c. What forms are found in the food supply? (Identify and
define various forms of each grain)
6. a. Describe the moist-heat preparation method for pasta. b.
Explain how cooked pasta hold its shape.
7. Why does the cooking water from pasta become cloudy?
8. Your sister desires consuming the healthiest grain products.
Would you recommend white flour for consumption? Why or
why not- explain in detail.
9. Explain how popcorn pops.
10. a. What is starch? b. Identify and explain the functions of
starch in the food supply.
11. Why are amylose and amylopectin important to starch?
Explain.
12. What is gelatinization? Explain the process and the factors
that influence gelatinization.
13. How does too much heat or too little heat affect
gelatinization?
14. How is a gel formed? Explain.
15. How would one avoid eventual syneresis (retrogradation)
when making a pie?
16. What is a modified starch? How do they work? Give
examples of types of modified starches and their use in
processed food.
17. What are the three primary ingredients in a sauce? Explain
each.
Vocabulary for a better understanding:
Choose only 5 and write definition with your own words.
Extruding
Semolina
Al dente
Amylose
Amylopectin
Retrogradation
Syneresis
Gelatinization
Gel formation
Dextrinization
Dextrose Equivalent (DE)
Modified starch
DataCountry Name2010 [YR2010]2004 [YR2004]2005
[YR2005]2006 [YR2006]2007 [YR2007]2008 [YR2008]2009
[YR2009]2011 [YR2011]2012 [YR2012]2013 [YR2013]2014
[YR2014]Uruguay40284481651.902113686333821.7864173628
57683.854519579457966.053823410572634.314730366213119.
292831660911277.029447962439303.724751383858669.857157
524653093.508357471277325.1312United
States149643720000001227492800000013093726000000138558
88000000144776350000001471858200000014418739000000155
17926000000161631580000001676805300000017419000000000
United
Kingdom2407856922126.082298042841450.022412109090909.
092582752529898.82963097238895.562791681985294.1223089
95170587.322592015702611.762614946487602.8126781734875
57.32941885537461.48United Arab
Emirates286049336031.676147824374345.116180617018379.85
222105922396.188257916133424.098315474615741.223253547
358746.804347454049215.014372313955071.477402340163738
.042401646583173.427Ukraine136419300367.96264883060725.
700386141530605.8135107753069306.931142719009900.99179
992405832.321117227769791.56163159671670.2651757813790
51.433183310146378.081131805126738.287Turkey7311680519
03.114392166275622.589482985910562.689530900094644.732
647155131936.449730337495735.69614553921806.4527747541
55283.582788863301670.379823242587404.139799534963353.
895Tunisia44426016487.35531183139301.485332272178403.51
4734377791551.623738909334495.294844855069425.18774345
5740497.306145951389299.963445238860996.54794699480403
5.7204..Switzerland581211717326.685393541696823.48240753
5656922.583429195565480.938477407780739.75355154694857
3.539539528260270.196696311711711.712666100605107.0646
85434208916.934..Sweden488379327089.837381705425301.746
389042298376.845420032121655.688487816328342.309513965
650650.119429657033107.737563113421113.421543880647757
.404579526008582.065570591266159.776Swaziland3527776867
.180242420645241.19142584077932.016452947943587.092963
053808158.514783019779208.831653144671158.997843806792
359.284413760602923.264313530226512.413133400422936.22
785Spain1431672847682.121069555500372.491157276458151.
971264551499184.541479341637010.681634989014208.291499
074742984.161494505143174.871355732589969.331393040177
013.681404306536057.92South
Africa375349442837.24228593703990.959257771618012.99927
1638630111.497299415359539.558286769850239.67529593647
1258.128416596716626.957397386418270.402366057913372.2
07349817096206.474Singapore236420337820.74511418664364
7.134127417879442.861147794117957.108179981089132.4941
92231203403.942192406441870.911275369805946.6682899411
06344.187302245904259.57307871907185.983Saudi
Arabia526811466666.667258742133333.333328461070013.087
376900133511.349415964509673.115519796800000429097866
666.667669506666666.667733955733333.333744335733333.33
3746248533333.333Portugal238317615894.04189187484479.76
2197304564108.942208566930121.691240169312893.51226200
7616815.585243745762711.864244879899916.59721636821849
0.174224912480764.725229583711490.434Poland47668789175
2.065253525770715.543304411705932.047343261472028.8734
28762961089.635530185123692.512436476394987.3452436276
4952.072496205742361.431526064038473.708548003360278.9
67Paraguay20047518281.0588033877360.416978734653762.36
75610646243498.204513794987109.049918503387744.9421593
3721804.867925099681460.894324595319573.75482889666061
8.382230984747863.3426Norway428524701366.5992643574946
59.388308722079937.912345424664369.357400883873279.083
461946808510.638386383919342.271498157406416.158509704
856037.817522349106382.979500103094419.465Netherlands83
6439735099.338646041718400.795672374082825.51971941287
1659.767833190528332.877931293393877.252858085579327.5
91893701695857.659823139235420.959853539351964.4588695
08125480.255Morocco90770208620.443956948015336.0397595
23801936.461365640092773.659675223563590.2006888795272
44.106790907274329.473499210991483.207595903875573.686
9103914824207.356107004984356.97Mexico1051128600823.05
770267585947.191866346483685.297966870460676.013104347
1321901.141101275279207.89894948749398.751171187518614
.221186659478340.11262248825555.91282719954861.76Malay
sia247533525880.554124749736842.105143534418325.8181626
91714851.183193549257178.92230812191087.49720225745820
1.389289326512786.666304956531561.712313158247642.5733
26933043800.609Lebanon38009950248.756220955223880.5972
1287562189.054721796351575.456124577114427.86072882985
0746.268735139635157.545640078938640.132743205095854.0
6344352418120.437745730945273.6318Kuwait115416397089.8
2359440511981.757680797945205.4795101558973317.6971146
35466885.582147380278353.806105905295688.7111540349419
41.584174044698001.211175826716255.725..Jordan264253794
36.619711407566733.534112588665303.24415056936953.4556
17110615282.710221972870920.857123818322957.7465288402
63380.281730937277605.633833593843661.971835826925774.
6479Japan5495385617892.024655803055650.554571867441130
.414356750212598.014356347794333.084849184641953.57503
5141567658.95905632338015.465954476603961.524919563108
372.54601461206885.08Italy2126747549668.871799125900173.
831853512498445.471943530297327.812204085546126.472391
875494360.632186239372047.792278089102029.472075220966
827.972136948255815.562144338185064.6Iraq138516722649.5
7336627901762.06349954890353.260965140295167.096188840
049180.6764131613657833.713111660855042.73518574966444
4.444218000992453.286232497236277.873220505682865.352Ir
an, Islamic
Rep.422568112861.574163226579221.143192014941988.55224
2515194970.475307490175011.339355988432886.61136266102
0975.296576566256355.386557935497765.774493798398466.3
71415338504536.257Indonesia755094157594.526256836883304
.41285868619205.805364570515631.492432216737774.861510
228634992.258539580085612.401892969104529.574917869913
364.916910478729099.036888538201025.345India17084588768
29.92721585608183.523834215013605.932949116769619.5541
238699170079.011224097069459.661365371474048.191835814
449584.81831781515471.561861801615477.92066902397333.2
6Greece299615364238.411239648745964.738247671558263.89
8273278760506.837318684779633.178354615643767.39432985
6904695.749288784959688.629249524986004.58524223073209
1.102237592274370.978Germany3412211920529.828154705736
28.012857629648053.722998619997490.93435683000273.7537
46916654460.233412975826618.513751876563803.1735332424
61467.053730260571356.513852556169656.01Georgia1163853
6834.42745125273880.749986410941012.591897745406200.85
37410172869679.736612795044472.766310766836276.5639144
34619982.211715846474595.77316140047012.14381652996318
7.4044France2646994701986.752124112242364.042203678646
934.462325011918203.492663112510265.542923465651091.26
2693827452070.022862502085070.892681416108537.39281024
9215589.072829192039171.84Finland247814569536.424196768
065557.487204436015420.968216552502822.732255384615384
.615283742493042.332251499027507.641273657214345.28825
6706466091.089268196956059.897270673584161.517Egypt,
Arab
Rep.218888324504.75378845185715.910489685724897.157110
7484034644.765130478960092.499162818181818.18218898237
4700.805236001858960.015262824255567.604271972822883.3
8286538047765.904Denmark319810991980.939251242843551.2
68264559522419.917282961088316.405319500339842.3873525
91553716.09319762353336.194341498686832.93932227654446
9.312335877548363.831341951607730.409Czech
Republic207015860050.371118976023159.713135990215966.67
4155213006071.979188818155388.125235204812643.14620572
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4745416076680.870750436294494.501460082020691.58367045
2887537.993962636688809.402162236755927.31956485308445
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5.591941745602165.092268594289022.032729784031906.0935
23094314820.94558431073438.25059419738267.417492432097
810.118461623162714.079490602600148.4910360105247908.3
Chile217538271334.673100630707851.859124404150138.16215
4671012210.645173081277147.793179626674542.40617195695
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1164144248225.781310752820874.471457871706545.01154261
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382.978733868989361.7021Australia1141267760188.15612871
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7638.256329761479745.779406003733991.082378506370535.2
35559849040366.128607711914608.421622057981847.4015401
97457443.535
Definition and SourceCodeIndicator NameLong
definitionSourceNY.GDP.MKTP.CDGDP (current US$)GDP at
purchaser's prices is the sum of gross value added by all
resident producers in the economy plus any product taxes and
minus any subsidies not included in the value of the products. It
is calculated without making deductions for depreciation of
fabricated assets or for depletion and degradation of natural
resources. Data are in current U.S. dollars. Dollar figures for
GDP are converted from domestic currencies using single year
official exchange rates. For a few countries where the official
exchange rate does not reflect the rate effectively applied to
actual foreign exchange transactions, an alternative conversion
factor is used.World Bank national accounts data, and OECD
National Accounts data files.
UNIVERSITY OF DENVER: DANIELS COLLEGE OF
BUSINESS
INFO 1020: ANALYTICS II
RAY BOERSEMA, instructor
COURSE PROJECT
AUTUMN 2015
The INFO 1020 Course Project is a three-phase project that
reinforces the basic business presentation skills developed in
INFO1010, and begins to develop the modeling skills expected
of all business analysts. The project will set students up for
success in INFO2020, but more importantly will help prepare
them for success in any business environment.
PHASE I: Data Collection (40 points)
You may collect data from (almost) any source(s). The
requirement is to include a numerical response (dependent)
variable that can be predicted from some other (independent)
variables. These data do not have to come from the same
source, but should be compatible as data sets (i.e., if your
response is a monthly result over a ten-year period, your other
data should cover the same time period and increments). The
minimum requirement is 50 observations with ten independent
variables.
The data may be from any field (preferably business-related)
and should be collected so that you can establish relationships
among your data to support some sort of conclusion.
DELIVERABLE: An Excel file turned in via CANVAS with a
summary of your data tables. (Ensure you identify your
sources.) Due on Saturday, October 10.
PHASE II: Preliminary Data Analysis (40 Points)
Apply descriptive statistics to your data set. This can include
graphical depictions as well as some basic calculated statistics,
to include exploring the individual relationships between your
independent variables and your response variable. You should,
at this point, be able to make some preliminary observations
about your data and the potential strengths and types of
relationships.
DELIVERABLE: A document turned in via CANVAS. Due on
Saturday, October 31.
FINAL PROJECT (120 Points)
Your mission (should you choose to accept it) is to find the
strongest relationship between your independent variables and
your response variable. This should include looking at all (at
least ten) linear relationships, and as many nonlinear
relationships as appropriate. (The Excel curve-fitting feature
under the scatterplot trend line should be particularly useful in
this regard.) You might also want to consider the relationships
within your set of dependent variables.
When you have identified the strongest relationship(s) in your
data set, as well as the weak relationships, summarize your
findings in a one-page, comprehensive “infographic,” and
organize all of your supporting analysis (to include everything
you did in Phase II) in well-documented enclosures (appendices
or tabs). Include in your summary which independent variables
have strong (and weak) linear relationships, and strong (and
weak) nonlinear relationships.
The “flavor” for this submission should be in terms of
“infographics.” Present your findings in a useful (informative)
manner that captures the information you would like to convey,
that is quickly understood, but that is also visually appealing
(think: “marketing”).
DELIVERABLE: A hard paper copy of your report, due at the
beginning of class on Wednesday, November 18.

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