ECON 311 Project 1

Laura Willits

Course #311-01Professor Alireza Akbari

10/13/2016

Computer Project #1

“A Study of Alcohol Consumption in the World”

Table of Contents Pages

1. Topic3-4

2. Background Description5-8

3. Scope of the Project9

4. Data Source9

5. Statistical Methods10

a. Numerical Methods10

b. Graphical Methods19

c. Tabular Methods22

6. Exploration of Possible Changes23-24

-Numerical Methods23-24

7. Discussion of Possible Outliers24

8. Limitation of the Study25

9. Conclusion, Summary, and Policy Recommendations26

10. Appendix27

1. Topic

Alcohol permeates every aspect of life in the United States. Whether it’s a work party, a

night out with friends, a sporting event, or many other events and celebrations, there is no way to

not be surrounded by drinking.

In this computer project the comparison between consumption of all types of alcohol will be

analyzed and the investigation of a possible relationship between three variables will be

explained.

I chose this topic because the ethical dilemmas surrounding alcohol fascinates me. Are you

responsible for your actions when you are under the influence? I was also interested to know if

the income of someone can affect the amount of alcohol was consumed. On the one hand, people

often use alcohol as a coping mechanism and could possibly be used by the poor to cope with the

less than ideal conditions they experience. However, people who have a higher income often

have more excess money to spend past food and housing that can be used to buy alcohol.

My hypothesis is that the consumption of alcohol per capita is proportional to the Gross

National Income (GNI) per capita and proportional to the taxes paid by the people as a percent of

the Gross Domestic Product (GDP). This correlation will be checked and discussed in this

project.

One hundred and eighty-eight countries had data, but only one hundred and thirteen countries

had all the needed data to be analyzed.

This is a relevant topic because the amount of alcohol consumed by one person can be

dangerous to others. Drunk driving and other risky behaviors can surface when people are under

the influence. The amount of alcohol consumed per capita by a country can be helpful to know in

order to protect yourself when travelling.

2. Background Description

Alcohol has been prevalent in society since before the written records of history. The

fermentation of alcoholic drinks can be traced back at least 10,000 years ago to prehistoric

times. The first types of alcohol were most likely fermented berries or honey.

In the ancient world, wine appeared in Egyptian pictographs around 4000 BC. The

Hebrews began drinking wine during their captivity in Egypt. Laborers were also given beer

and provided nourishment and calories. The Mayans fermented corn or maize to make mead.

Alcohol was already being consumed all over the world.

The Romans were well known for abusing alcohol. Wine was distributed very cheaply

in order to placate the empire that was experiencing major decline and immigration. Jesus used

wine in his teachings and approved wine in moderation. It’s abuse, however, was seen by the

church as a sin. When the Huns invaded Europe, the production of wine dropped dramatically

as they ravaged vineyards and cellars. Alcohol permeated the Viking culture and they saw

heaven as a place where you could drink endless amounts of alcohol. Wine was very expensive

and so commoners could not afford it, but towns in countries like Germany began to be able to

brew their own beer.

In the Middle Ages came the discovery of distillation of alcohol to be used as

medication. Brandy was first known as aqua vitae, or the water of life. At this point, beer

consumption in countries such as Bavaria was about 300 liters per capita a year.

The Puritans in 1620 brought more beer than water on the Mayflower and landed on

Plymouth because their supply of beer was running low. Brewing beer was one of the first

productions for the colonies.

While the Catholic and Protestant churches believed that only drinking in excess was a

sin, Muslims believed that drinking any amount of alcohol was unacceptable.

Around the 17th century, the first grain spirit, Whiskey, is believed to have been

invented in Ireland or Scotland. At this point, however, spirits were still mainly for medicinal

purposes. It wasn’t until the sugar production in the Caribbean enabled the production of

molasses for rum and used in the Triangle Trade route that spirits became popularized.

After the 1870s, alcohol consumption began to decline. Historians are unsure exactly

why this trend happened, but factors such as other caloric food availability and the temperance

movement are said to be possibilities. Protestant churches began to reject alcohol in any

quantity. Prohibition of alcohol swept the world as Russia, Hungary, Norway, Iceland, the

United States, Canada and many other countries set up the new law to stop the production of

alcohol. However, this created more social problems than fixing them.

Studies in the 1970s on the consumption of moderate amounts of alcohol found it to

actually have positive benefits to health. Since then, the taxes of alcohol have increased, the

drinking age has risen, punishments for alcohol-related accidents has become much stricter,

and there are more restrictions on the advertising of alcohol.

But the danger of drinking has increased since the beginnings of time. When people

were consuming double the amount of alcohol we do today, their only transportation was at

most a horse. Now, our transportation can reach even deadlier and more dangerous speeds than

ever before. Additionally, although the prevalence of alcohol might not have increased since its

peak in the 18th and 19th centuries, we are now in a world of constant communication. Before,

alcohol could be out of sight, out of mind. But today’s world causes us to constantly be

bombarded by messages, whether we want to hear them or not. This means that something as

addictive as alcohol could be constantly shown to us in order to convince us to buy and drink it

in excess, making it feel even more prevalent today than ever before. The restrictions on

alcohol seek to ameliorate these problems. (Boyle, 2013)

After some research, I found some similar studies to mine. The first studied 6894

persons in Norway, and asked them to self-report their socio-economic class and amount of

alcohol consumed. The study spanned from 1993 to 2000. They found that consumption of

alcohol increased from year to year, and that the consumption of alcohol increased based on

lower income and education level. It was also found in this study that if you were male, you

were more likely to drink more than if you were a woman (Strand, 2000).

Another study that I found that was similar to mine was a study in the Netherlands. In

1991, researchers studied whether there was a correlation between excessive drinking and

stressors such as financial problems, deprivation, and income. They defined excessive drinking

as “drinking more than six glasses on 3 or more days a week or more than four glasses on 5 or

more days a week” (Droomers, 1999). They also studied how educational level affected

drinking level. They found that excessive drinking was more common among people with

lower educational levels and the prevalence of the stressors.

Other than that, I was surprised that I didn’t find any more studies that were related to

mine. I researched on Google Scholar to find related studies. While there were many on the

topic of alcohol, it was alcohol and a variable other than income or anything related that was

studied with it.

Alcohol has been prevalent in society since the beginning of time, and in no way is

going away anytime soon. Understanding the reasons why alcohol is more prevalent in certain

countries, and which countries it is most prevalent in, is essential to not only ensure safety

when traveling, but also to begin to understand this ancient drink.

3. The Scope of the Project

The main purpose of this project is to explore, analyze, and describe the data set of the

alcohol consumption per capita in 2013, which is measured by how many liters of all types of

alcohol are consumed per capita. In this research, numerical, graphical, and tabular methods

will be used to analyze the chosen data set. The aim of my report is to understand how certain

factors can affect the amount of alcohol that is consumed by people in different countries.

The secondary objective of my project is to compare alcohol consumption in the world in

2009 and 2013. Measures of central tendency and measures of difference will be used to

discover if my hypothesis is true or not.

4. Data Source

The source of the data is http://apps.who.int/gho/data/node.main.A1026?lang=en given by

the World Health Organization. Data in the tables are those available from 2000 to 2015 and

was last updated on September 29, 2016. This is cross-sectional data. The data is recorded

from 186 countries.

The other sources of data are http://data.worldbank.org/indicator/NY.GNP.PCAP.CD for

the GNI per capita (cross-sectional data recorded in 146 countries) and

https://stats.oecd.org/Index.aspx?DataSetCode=REV for the tax revenue (cross-sectional data

recorded in 161 countries)

https://stats.oecd.org/Index.aspx?DataSetCode=REV

http://data.worldbank.org/indicator/NY.GNP.PCAP.CD

http://apps.who.int/gho/data/node.main.A1026?lang=en

5. Statistical Analysis

Numerical Methods:

As Table #2 indicates:

1. A typical country in the world is expected to have an alcohol consumption of 5.70 liters

per capita per year.

2. The bottom 50% (half least alcohol consuming) of the countries consume less than 5.87

liters of alcohol per capita per year and the top 50% (half most alcohol consuming) of

countries consume at least 5.87 liters of alcohol per capita per year.

3. The most observed alcohol consumption per capita was .01 liters per year-in the world

of 113 countries, 2 countries had this value for consumption.

4. The actual consumption of alcohol per capita per year is spread from the expected value

by a measure of 3.89.

5. The data is moderately flat (-.99)

6. The data is slightly skewed to the right (.18)

7. Lithuania’s consumption of alcohol per capita per year exceeds Afghanistan and

Bangladesh’s consumption by 15.03 liters.

8. The least alcohol consumed by a country per capita per year was .01 liters by

Afghanistan and Bangladesh

9. The most alcohol consumed by a country per capita per year was 15.04 liters by

Lithuania

10. The total consumption of all countries is 638.42 liters per capita in 2013

11. There were 113 countries in the world in 2013 with available data for alcohol

consumption.

12. The bottom quarter of countries consumed less than 1.88 liters of alcohol per capita per

year. The top three-quarters of countries consumed more than 1.88 liters of alcohol per

capita per year.

13. The top quarter of countries consumed more than 8.94 liters of alcohol per capita per

year. The bottom three-quarters of countries consumed no more than 8.94 liters of

alcohol per capita per year.

14. The middle 50 percent of countries’ consumption differs by 7.07 liters per capita per

year. One-fifth of countries have a consumption of less than 1.55 liters.

15. Four-fifths of countries have a consumption of more than 1.55 liters.

16. One-third of countries have a consumption of less than 3.20 liters. Two-thirds of

countries have a consumption of more than 3.20 liters.

17. Two-thirds of countries have a consumption of less than 7.56 liters. One-third of

countries had a consumption of more than 7.56

18. 90 percent of countries had a consumption rate of at most 10.62 liters per capita per

year. 10 percent had a consumption rate of at least 10.62 liters.

6. The standard deviation is 66 percent of the mean

Table #3 shows changes of consumption rate of countries between 2009 and 2013

Table #2 indicates kurtosis (-.99) and skewness (.18). The alcohol consumption rate

distribution is moderately flat. The alcohol consumption rate distribution is skewed slightly to

the right- toward the large alcohol consumption rate of country #62 (Lithuania).

Interpretation of Z Score

Mean = 5.70, Standard Deviation = 3.89.

Afghanistan/Bangladesh .01

Z = (.01-5.70)/3.89 = -1.46

The consumption of alcohol in Afghanistan and Bangladesh is 1.46 standard deviations below

average

United States 5.82

Z = (5.82-5.70)/3.89 = .03

The consumption of alcohol in The United States is .03 standard deviations above average.

Lithuania 15.04

Z = (15.04-5.70)/3.89 = 2.40

The consumption of alcohol in Lithuania is 2.40 standard deviations above average.

Application of the Chebyshev’s theorem

Mean = 5.70, Standard Deviation = 3.89.

Z=1.2; ( Z * σ ) = 1.2 * 3.89 = 4.67

Z=1.5; ( Z * σ ) = 1.5 * 3.89 = 5.83

Z=2.3; ( Z * σ ) = 2.3 * 3.89 = 8.95

Z Score µ + - ( Z * σ ) Low End High End

1.2 5.70 + - 4.67 1.03 10.37

1.5 5.70 + - 5.83 -0.13 11.54

2.3 5.70 + - 8.95 -3.25 14.65

Z=1.2; (1 – 1/Z*Z) = (1 – 1/(1.2)*(1.2)) = .3056

Z=1.5; (1 – 1/Z*Z) = (1 – 1/(1.5)*(1.5)) = .5556

Z=2.3; (1 – 1/Z*Z) = (1 – 1/(2.3)*(2.3)) = .8110

At least 30.56 percent of countries consume between 1.03 liters and 10.37 liters of alcohol

At least 55.56 percent of countries consume between -.13 liters and 11.54 liters of alcohol

At least 81.10 percent of countries consume between -3.25 liters and 14.65 liters of alcohol

Empirical Rule

The distribution of my data set was almost normal distribution, but the empirical rule is used.

Low End High End

µ + - (1)* σ 5.70 + - (1)* 3.89 1.81 9.59

µ + - (2)* σ 5.70 + - (2)* 3.89 -2.08 13.48

µ + - (3)* σ 5.70 + - (3)* 3.89 -5.97 17.37

Approximately 68 percent of countries’ alcohol consumption is between 1.81 liters and 9.59

liters per capita per year.

Approximately 95 percent of countries’ alcohol consumption is between 0 liters and 13.48

liters

Almost all of countries’ alcohol consumption is between 0 liters and 17.37 liters

b. Numerical Measures of Association

In this computer project, multivariate model will be analyzed:

Consumption of alcohol per capita = f(GNI per capita 2009, GNI per capita 2013, taxes

(%of GDP), where

Dependent Variable (Y): Consumption of Alcohol per capita in 2013

Independent Variable (X1): GNI per capita, calculate using World Bank Atlas Method in

U.S. dollars 2009.

Independent Variable (X2): GNI per capita, calculate using World Bank Atlas Method in

U.S. dollars 2013.

Independent Variable (X3): Taxes (% GDP) 2009.

Relationship between gross national income per capita in 2009 and the alcohol

consumption per capita in 2013:

Y=bo +b1X1

Y=4.3435+9E-05X1

Intercept (b0): At X1=0, the Y is expected to be 4.34

If people have no gross national income in 2009, they are expected to have a consumption of

4.34 liters of alcohol per year.

Slope (b1): for every additional unit increase in X1, Y is estimated to increase by 9E-05.

For every increase in the gross national income data, the alcohol consumption is expected to

increase by 9E-05.



Y=bo +b1X2

Y=4.3623+8E-05X2


If people have no gross national income, they are expected to have a consumption of 4.36 liters

of alcohol per year.

Slope (b1): for every additional unit increase in X2, Y is estimated to increase by 8E-05.

For every increase in the gross national income data, the alcohol consumption is expected to

increase by 8E-05.

Relationship between percent of taxes of the GDP and the alcohol consumption per capita

in 2013:

Y=bo +b1X3

Y=2.24+.1502X3


If people pay no taxes, they are expected to have a consumption of 2.24 liters of alcohol per year.

Slope (b1): for every additional unit increase in X2, Y is estimated to increase by .1502.

For every increase in the percent of taxes of the GDP, the alcohol consumption is expected to

increase by .1502.

Goodness of Fit



R2 = .19 it is a direct weak linear relationship




Relationship between percent of taxes of the GDP and the alcohol consumption per capita

in 2013:


Strength of linear relationship



R=.44 medium

There is a medium direct relationship between the gross national income per capita in

2009 and the consumption of alcohol per capita in 2013.



R=.43 medium

There is a medium direct relationship between the gross national income per capita in

2013 and the consumption of alcohol per capita in 2013.

This is a weaker relationship than the relationship between gross national income per

capita in 2009 and the alcohol consumption per capita in 2013

Relationship between percent of taxes of the GDP per capita and the alcohol consumption

per capita in 2013:

R=.48 medium

There is a medium direct relationship between the percent of taxes of the GDP per capita

in 2013 and the consumption of alcohol per capita in 2013.

This is a stronger relationship than the relationship between gross national income per

capita in 2009 and 2013 and the alcohol consumption per capita in 2013

Prediction Step

In this research, we will forecast consumption of alcohol, if we intend to have X1 (gross

national income per capita of 2009):

Y=4.3435+9E-05X1

Gross National Income

Consumption rates

X1=680 Y=5.68 Haiti tends to have 680-dollar gross national income per capita and is expected to have an alcohol consumption rate of 5.68 liters per capita.

X1=3680 Y=.4 Jordan tends to have 3,680-dollar gross national income per capita and is expected to have an alcohol consumption rate of .4 liters per capita.

X1=18480 Y=.46 Oman tends to have 18,480-dollar gross national income per capita and is expected to have an alcohol consumption rate of .46 liters per capita.

X1=42210 Y=7.31 Iceland tends to have 42,210-dollar gross national income per capita and is expected to have an alcohol consumption rate of 7.31 liters per capita.

X1=87840 Y=6.21 Norway tends to have 87,840-dollar gross national income per capita and is expected to have an alcohol consumption rate of 6.21 liters per capita.

We will forecast consumption of alcohol, if we intend to have X2 (gross national income per

capita of 2013):

Y=4.3623+8E-05X2

Gross National Income

Consumption rates

X2=3120 Y=.45 Morocco tends to have 3,120-dollar gross national income per capita and is expected to have an alcohol consumption rate of .45 liters per capita.

X2=7480 Y=12.06 Bulgaria tends to have 7,480-dollar gross national income per capita and is expected to have an alcohol consumption rate of 12.06 liters per capita.

X2=10530 Y=5.11 Panama tends to have 10,530-dollar gross national income per capita and is expected to have an alcohol consumption rate of 5.11 liters per capita.

X2=13510 Y=10 Poland tends to have 13,510-dollar gross national income per capita and is expected to have an alcohol consumption rate of 10 liters per capita.

X2=470 Y=1.86 Ethiopia tends to have 470-dollar gross national income per capita and is expected to have an alcohol consumption rate of 1.86 liters per capita.

We will forecast consumption of alcohol, if we intend to have X3 (% of taxes of GDP):

Y=2.24+.1502X3

% of Taxes of GDP

Consumption rates

X3=10.5 Y=1.83 Sierra Leone tends to have taxes 10.5% of GDP and is expected to have an alcohol consumption rate of 1.83 liters per capita.

X3=17 Y=1.03 Thailand tends to have taxes 17% of GDP and is expected to have an alcohol consumption rate of 1.03 liters per capita.

X3=17.1 Y=7.2 Chile tends to have taxes 17.1% of GDP and is expected to have an alcohol consumption rate of 7.2 liters per capita.

X3=21.7 Y=5.91 Georgia tends to have taxes 21.7% of GDP and is expected to have an alcohol consumption rate of 5.91 liters per capita.

X3=38.8 Y=7.24 Brazil tends to have taxes 38.8% of GDP and is expected to have an alcohol consumption rate of 7.24 liters per capita.

Graphical Methods:

a. Graphical Measures

Interpretation of the graph #1 (The Bar Graph)

The graph is asymmetrical and unimodal

Graph #1 shows that the most frequent category is 0-1 liters of

alcohol and the second most frequent category is 1-2 liters of alcohol

Interpretation of the graph #2 (The Area Chart)

The alcohol consumption relative distribution is moderately skewed

to the left toward the lower consumption of alcohol.

The alcohol consumption distribution is moderately flat.

The most observed consumption of alcohol in 2013 was .1-out of 113

countries, 2 countries had a consumption of .1

Interpretation of the graph #3 (Pie Graph)

13.51% of countries fell in the category 0-1 liters of consumption of

alcohol consumed, the most common category. The least common

categories, making up .9% of the data each, was 2-3 and 14-15 liters.

The bulk of the data is clustered around countries with consumptions

0-2 liters and 5-10 liters.

Interpretation of the graph #4 (Stem and Leaf Display)

A Stem and Leaf Display is a graphical method of displaying data

It is not useful for my data because my data is too numerous and the

range of my data is too small.

Interpretation of the graph #5 (Ogive)

86% countries had an alcohol consumption of at most 10 liters

44% countries had an alcohol consumption of at most 5 liters

34% countries had an alcohol consumption between 5 and 10 liters

14% countries had an alcohol consumption of at least 10 liters

Interpretation of the graph #6 (Box and Whisker Plot)

The IQR of the data is skewed slightly to the left of the median

There are no outliers.

Interpretation of the graph #7-8 (Box and Dot Plots)

The bulk of the data is clustered between 0-2 liters and 5-10 liters

b. Graphical Mesaures of Relationship –Visualization Step

Interpretation of Graph #8 “Scatter plot of the relationship between Alcohol Consumption

2013 and GNI in 2009”:

Alcohol Consumption (Y) and GNI 2009 (X1) seem to be slightly related in a direct linear

fashion. Between $0-$20,000, there seems to be no relationship between the data. However,

after $20,000 there seems to be a direct linear relationship between X and Y.

Interpretation of Graph #9 “Scatter plot of the relationship between Alcohol Consumption

2013 and GNI in 2013”

Alcohol Consumption (Y) and GNI 2013 (X2) seem to be slightly related in a direct linear

fashion. Between $0-$20,000, there seems to be no relationship between the data. However,

alike to Graph #8, after $20,000 there seems to be a direct linear relationship between X and Y

Graph #10 “Scatter plot of the relationship between Alcohol Consumption 2013 and % of

Taxes of GDP in 2013”

Alcohol Consumption (Y) and % of Taxes of GDP (X3) seem to be related in a direct linear

fashion. In comparison to Graph #8 and #10, this relationship between x and y is much

stronger.

II. Tabular Methods:

a- Frequency , Relative Frequency, Cumulative Frequency and the Relative

Cumulative Frequency Distribution Tables.

As table #6 indicates:

1. The most prevalent alcohol consumption category was 0-1 liters. 15 countries

had an alcohol consumption between 0 and 1 liter.

2. The second most prevalent alcohol consumption rate category was 1-2 liters.

13 countries had an alcohol consumption between 1 and 2 liters.

3. The third most prevalent alcohol consumption category was 9-10 liters. 11

countries had an alcohol consumption between 9 and 10 liters.

4. The lowest category of alcohol consumption frequency exceeds the highest

category of alcohol consumption frequency by 14.

5. The most common relative frequency was .05 and .07. Both of these relative

frequencies occurred three times in the table.

6. The relative frequency of 0-1 liters is double that of 3-4 liters, 5-6 liters, and 6-

7 liters.

7. 74 countries had an alcohol consumption of 8 liters at most-the middle of the

range of data categories.

8. A quarter (25.23%) of the countries’ alcohol consumption is less than 2 liters


9. A little over half (51.35%) of countries’ alcohol consumption is at most 6 liters


10. The difference between one quarter and halfway point of the cumulative data is

4 liters, and the difference between the halfway point and the three quarters

point of the cumulative data is 3 liters.

b- Tabular Mesaures of Relationship – Cross tabulation

As Table #8-11 indicates:

There is a direct linear relationship between consumption of

alcohol 2013 and the percent of taxes of the GDP. The most

common category was an alcohol consumption between 3-4 liters

and a 10-20% of the GDP. This occurred 6 times. The data for 0-1

liters had at most 30% taxes of the GDP. The data for 14-15 liters

and 15-16 liters had 20-30% in taxes, the middle category. 37.8%

of countries have 10-20% taxes of GDP. This is the most common

category. Noting these observations, the direct linear relationship

isn’t perfect, but there is definitely a correlation between these

two data sets.

7- Exploration of Possible Changes .

As Table #3 indicates, from 2009 to 2013:

1. The typical countries’ alcohol consumption deteriorated by 1%

2. The alcohol consumption of the top 50% of countries improved by .045 of a

liter.

3. The most frequent alcohol consumption stayed the same at .01 liter

4. The spread of actual data increased by 8% around the expected value

5. The data distribution became 26% more flat

6. The data is more skewed to the left by 6%

7. The range of data decreased by 95%

8. The minimum stayed the same at .01 liter

9. The maximum improved by .95 liters

10. The total alcohol consumption of the world deteroriated by 1.66 liters.

8- Discussion of the Possible Outliers – In my data set, I found no outliers in my data.

VARIABLE A

IQR 7.0650

1.5 * IQR 10.5975

3.0 * IQR 21.1950

Outer Fence -19.3175

Inner Fence -8.72001- Very First small # that is NOT an Outlier

.01 (Bangladesh and Afghanistan)

2- First Quartile 1.8775

3- Median 5.865

4- Third Quartile 8.94255- Very First large # that is NOT an Outlier

15.04 (Lithuania)

Inner Fence 19.5400

Outer Fence 30.1375

All of my data fits within the inner and outer fences, so there are no outliers

9. Limitations of the StudyData availability limited the elements available in my study. There were many countries

that had certain variable that had no data, and so the initial 193 countries had to be

trimmed down to 111.

In my research, 76 countries did not have all the data needed for every variable and so

were omitted from the study. The countries are as follows:

AndorraAngolaAntigua and BarbudaBeninBhutanBotswanaBrunei DarussalamBurundiCote d'IvoireCabo VerdeCambodiaCameroonCentral African RepublicComorosCongoCook IslandsDemocratic Republic of the CongoDjiboutiDominicaEritreaEstoniaFijiGambiaGhanaGrenada

GuineaGuinea-BissauIran (Islamic Republic of)IraqKiribatiKuwaitKyrgyzstanLao People's Democratic RepublicLesothoLiberiaLibyaMalawiMaldivesMaliMauritaniaMauritiusMongoliaMontenegroMyanmarNamibiaNauruNigerNiuePapua New GuineaRepublic of Korea

Republic of MoldovaRomaniaRussian FederationSaint Kitts and NevisSaint Vincent and the GrenadinesSamoaSerbiaSeychellesSloveniaSolomon IslandsSomaliaSri LankaSurinameSwitzerland

Syrian Arab RepublicTimor-LesteTogoTurkmenistanTuvaluUnited Arab EmiratesUnited Kingdom of Great Britain and Northern IrelandUnited Republic of TanzaniaUruguayUzbekistanZimbabwe

10-Conclusion, Summary, and Policy Recommendations – In my research paper, the comparison of alcohol consumption per capita showed that

Lithuania was the highest drinking country in the world and Afghanistan and Bangladesh

were the lowest drinking countries in the world. After breaking the consumption into low

consumption, average consumption, and high consumption, I found that European

countries such as Denmark, France, and Finland had high consumption rates. The Middle

Eastern countries such as Egypt, Afghanistan, and Israel had low consumption rates. The

distribution of data was slightly skewed to the right.

My hypothesis was that there will be a direct linear correlation between alcohol

consumption and gross domestic income and between alcohol consumption and the

percent taxes are of the GDP. In my research, I found a medium direct linear correlation.

Therefore, my hypothesis is correct that there is a relationship between these variables.

The comparison of alcohol consumption between 2009 and 2013 found that although

the total alcohol consumption of the world deteriorated by 1.66 liters, the alcohol

consumption of the top 50 percent of countries improved by 4% and the maximum

consumption improved by .95 liters.

Alcohol is one of the oldest and most often abused drugs in our world. It is essential to

not only know the consumption of alcohol globally to protect yourself when going on

international travel, but also to understand our world today, yesterday, and tomorrow.

11- Appendix

Table #1- “The Topic”Topic A Study of Alcohol Consumption

Source of Datahttp://data.worldbank.org/indicator/NY.GNP.PCAP.CD

http://apps.who.int/gho/data/node.main.A1026?lang=enhttps://stats.oecd.org/Index.aspx?DataSetCode=REV

Elements(observations) Countries

# of elements 193

# of Missing Values 75

Table #2- “Measures of central tendency and difference of alcohol consumption in 2013”

Alcohol per capita consumption 2013Mean 5.700178571Standard Error 0.367562692Median 5.865Mode 0.01Standard Deviation 3.889917895Sample Variance 15.13146123Kurtosis 0.986591666Skewness 0.180905542Range 15.03Minimum 0.01Maximum 15.04Sum 638.42Count 112Q1 1.8775Q3 8.9425

IQR 7.065Range 15.03Coefficient of Variation 0.66324260820th P 1.55433rd P 3.199966th P 7.555890th P 10.922

Table #3- “Changes of various measures of alcohol consumption in the world between 2013 and 2009”

Alcohol Consumption per capita in 2009

Difference in Alcohol

Consumption (2013-2009)

Percent Difference in Alcohol Consumption (2013-2009)

Mean 5.715 0.01482 1%Standard Error

0.375319

0.00776 1%

Median 5.82 -0.045 -4%Mode 0.01 0 0%Standard Deviation

3.972008

0.08209 8%

Sample Variance

15.77685

0.64538 65%

Kurtosis -1.2449

2

-0.258329 -26%

Skewness 0.119486

-0.06142 -6%

Range 14.08 -0.95 -95%Minimum 0.01 0 0%Maximum 14.09 -0.95 -95%Sum 640.08 1.66 166%Count 112 0 0%

Table #4 Stem and Leaf Display

Stem-and-Leaf Display

Leaf unit: 10

0

0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 6 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 7 7 7 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 9 9 9

n 112 1 0 0 0 0 0 0 0 0 1 1 1 1 1 2 2 2 2 2 2 5 5

mean5.70017

9median 5.865

std. dev.3.88991

8minimum 0.01maximum 15.04

Table #5 to construct Graphs 1-4Alcohol Consumption

Frequency Cumulative Frequency

Relative Frequency

Cumulative Percent Frequency

0-1 15 15 0.14 13.51%1-2 13 28 0.12 25.23%2-3 6 34 0.05 30.63%3-4 8 42 0.07 37.84%4-5 7 49 0.06 44.14%5-6 8 57 0.07 51.35%6-7 8 65 0.07 58.56%7-8 9 74 0.08 66.67%8-9 10 84 0.09 75.68%9-10 11 95 0.10 85.59%10-11 6 101 0.05 90.99%11-12 5 106 0.05 95.50%12-13 3 109 0.03 98.20%14-15 1 110 0.01 99.10%15-16 1 111 0.01 100.00%Grand Total 111 1.00

Table #6 “Tabular Methods: frequency, relative frequency, cumulative frequency, and cumulative percent frequency of alcohol consumption per capita in 2013”

Alcohol Consumption Frequency

Relative Frequency

Cumulative Frequency


Low Consumption

0-1 15 0.14 15 13.51%1-2 13 0.12 28 25.23%2-3 6 0.05 34 30.63%

Average 3-4 8 0.07 42 37.84%

Consumption

4-5 7 0.06 49 44.14%5-6 8 0.07 57 51.35%6-7 8 0.07 65 58.56%7-8 9 0.08 74 66.67%8-9 10 0.09 84 75.68%9-10 11 0.10 95 85.59%

High Consumption

10-11 6 0.05 101 90.99%11-12 5 0.05 106 95.50%12-13 3 0.03 109 98.20%14-15 1 0.01 110 99.10%15-16 1 0.01 111 100.00%Grand Total 111 1.00

Table #7 “Tabular Methods: frequency, relative frequency, cumulative frequency, and cumulative percent frequency of alcohol consumption per capita in 2009”

Alcohol Consumption (Liters)

Frequency Relative Frequency

Cumulative Frequency


Low Consumption

0-1 17 0.15 17 15.32%1-2 11 0.10 28 25.23%

Average Consumption

2-3 7 0.06 35 31.53%3-4 8 0.07 43 38.74%4-5 9 0.08 52 46.85%5-6 5 0.05 57 51.35%6-7 7 0.06 64 57.66%7-8 11 0.10 75 67.57%8-9 6 0.05 81 72.97%

High Consumption

9-10 9 0.08 90 81.08%10-11 9 0.08 99 89.19%11-12 7 0.06 106 95.50%12-13 3 0.03 109 98.20%13-14 1 0.01 110 99.10%14-15 1 0.01 111 100.00%

Grand Total 111 1.00

Table #8-11 “Tabular Methods: Crosstabulation of Consumption of Alcohol 2013 vs. % of Taxes of GDP in 2013”Count

% Taxes of GDPAlcohol Consumptio

0-10 10-20 20-30 30-40 40-50 Grand

n Total0-1 5 8 2 151-2 1 9 1 2 132-3 1 2 3 63-4 6 2 84-5 2 3 1 1 75-6 2 4 2 86-7 1 3 3 1 87-8 1 2 4 2 98-9 1 3 1 4 1 109-10 1 3 2 3 2 1110-11 1 4 1 611-12 1 1 3 512-13 1 2 314-15 1 115-16 1 1Grand Total 13 42 21 24 11 111

Percent of Grand TotalColumn Labels

Row Labels 0-10 10-20 20-30 30-40 40-50

Grand Total

0-1 4.5% 7.2% 1.8% 0.0% 0.0% 13.5%1-2 0.9% 8.1% 0.9% 1.8% 0.0% 11.7%2-3 0.9% 1.8% 0.0% 2.7% 0.0% 5.4%3-4 0.0% 5.4% 1.8% 0.0% 0.0% 7.2%4-5 0.0% 1.8% 2.7% 0.9% 0.9% 6.3%5-6 1.8% 3.6% 1.8% 0.0% 0.0% 7.2%6-7 0.9% 2.7% 2.7% 0.0% 0.9% 7.2%7-8 0.0% 0.9% 1.8% 3.6% 1.8% 8.1%8-9 0.9% 2.7% 0.9% 3.6% 0.9% 9.0%9-10 0.9% 2.7% 1.8% 2.7% 1.8% 9.9%10-11 0.9% 0.0% 0.0% 3.6% 0.9% 5.4%11-12 0.0% 0.9% 0.0% 0.9% 2.7% 4.5%12-13 0.0% 0.0% 0.9% 1.8% 0.0% 2.7%14-15 0.0% 0.0% 0.9% 0.0% 0.0% 0.9%15-16 0.0% 0.0% 0.9% 0.0% 0.0% 0.9%Grand Total 11.7% 37.8

%18.9

%21.6

%9.9

%100.0%

Percent of Row TotalColumn Labels

Row Labels 0-10 10-20

20-30 30-40

40-50

Grand Total

0-1 33.3% 53.3%

13.3% 0.0% 0.0% 100.0%

1-2 7.7% 69.2%

7.7% 15.4%

0.0% 100.0%

2-3 16.7% 33.3%

0.0% 50.0%

0.0% 100.0%

3-4 0.0% 75.0%

25.0% 0.0% 0.0% 100.0%

4-5 0.0% 28.6%

42.9% 14.3%

14.3%

100.0%

5-6 25.0% 50.0%

25.0% 0.0% 0.0% 100.0%

6-7 12.5% 37.5%

37.5% 0.0% 12.5%

100.0%

7-8 0.0% 11.1%

22.2% 44.4%

22.2%

100.0%

8-9 10.0% 30.0%

10.0% 40.0%

10.0%

100.0%

9-10 9.1% 27.3%

18.2% 27.3%

18.2%

100.0%

10-11 16.7% 0.0% 0.0% 66.7%

16.7%

100.0%

11-12 0.0% 20.0%

0.0% 20.0%

60.0%

100.0%

12-13 0.0% 0.0% 33.3% 66.7%

0.0% 100.0%

14-15 0.0% 0.0% 100.0%

0.0% 0.0% 100.0%

15-16 0.0% 0.0% 100.0%

0.0% 0.0% 100.0%

Grand Total

11.7% 37.8%

18.9% 21.6%

9.9% 100.0%

Percent of Column Total% of Taxes Of GDP

Alcohol Consumption

0-10 10-20 20-30 30-40 40-50 Grand Total

0-1 38.5% 19.0% 9.5% 0.0% 0.0% 13.5%1-2 7.7% 21.4% 4.8% 8.3% 0.0% 11.7%2-3 7.7% 4.8% 0.0% 12.5% 0.0% 5.4%3-4 0.0% 14.3% 9.5% 0.0% 0.0% 7.2%4-5 0.0% 4.8% 14.3% 4.2% 9.1% 6.3%5-6 15.4% 9.5% 9.5% 0.0% 0.0% 7.2%6-7 7.7% 7.1% 14.3% 0.0% 9.1% 7.2%

7-8 0.0% 2.4% 9.5% 16.7% 18.2% 8.1%8-9 7.7% 7.1% 4.8% 16.7% 9.1% 9.0%9-10 7.7% 7.1% 9.5% 12.5% 18.2% 9.9%10-11 7.7% 0.0% 0.0% 16.7% 9.1% 5.4%11-12 0.0% 2.4% 0.0% 4.2% 27.3% 4.5%12-13 0.0% 0.0% 4.8% 8.3% 0.0% 2.7%14-15 0.0% 0.0% 4.8% 0.0% 0.0% 0.9%15-16 0.0% 0.0% 4.8% 0.0% 0.0% 0.9%Grand Total 100.0% 100.0

%100.0

%100.0

%100.0

%100.0%

Graph 1 “Frequency of Alcohol Consumption in 2013”

0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10-11

11-12

12-13

14-15

15-16

0

2

4

6

8

10

12

14

16

Total

Graph #2 “Relative Frequency of Alcohol Consumption in 2013”

0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10-11 11-12 12-13 14-15 15-160.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

Total

Graph 3 “Percent Frequency of Alcohol Consumption in 2013”

13.51%

11.71%

5.41%

7.21%

6.31%7.21%7.21%8.11%

9.01%

9.91%

5.41%

4.50% 2.70% 0.90% 0.90%

0-11-22-33-44-55-66-77-88-99-1010-1111-1212-1314-1515-16

Graph #4 “Percent Cumulative Frequency of Alcohol Consumption in 2013, Ogive”

0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10-11

11-12

12-13

14-15

15-16

0.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

Total

Liters of Alcohol Consumed

Coun

t of C

umilt

ative

Ele

men

ts

Graph #5 “The Box and Whisker”

-30 -20 -10 0 10 20 30 40

Graph #6 “The Box Plot”

0 2 4 6 8 10 12 14 16

Box Plots

Data Values

Type 1

Type 2

Type 3

Type 4

Graph #7 “The Dot Scatter”

-10 -5 0 5 10 15 20 250

1

2

3

4

5

Dot Plots

Data Values

Type 3

Type 2

Type 1

Type 4

Graph #8 “Scatter plot of the relationship between Alcohol Consumption 2013 and GNI in 2009”

0 10000 20000 30000 40000 50000 60000 70000 80000 90000 1000000

2

4

6

8

10

12

14

16

f(x) = 9.1722164974524E-05 x + 4.34346034083308R² = 0.192888943065956

GNI 2009

Alco

hol C

onsu

mpti

on 2

013

Graph #9 “Scatter plot of the relationship between Alcohol Consumption 2013 and GNI in 2013”

0 20000 40000 60000 80000 100000 1200000

2

4

6

8

10

12

14

16

f(x) = 7.94928134116221E-05 x + 4.36230742413835R² = 0.183501616179471

GNI 2013

Alco

hol C

onsu

mpti

on 2

013

Graph #10 “Scatter plot of the relationship between Alcohol Consumption 2013 and % of Taxes of GDP in 2013”

0 10 20 30 40 50 600

2

4

6

8

10

12

14

16

f(x) = 0.150228298830105 x + 2.28449675918872R² = 0.228145152216919

Graph #11 “Frequency of Alcohol Consumption in 2009”

0-1 1-2 2-3 3-4 4-5 5-6 6-7 7-8 8-9 9-10 10-11

11-12

12-13

13-14

14-15

0

2

4

6

8

10

12

14

16

18

Total

Frequency

liter

s of

alc

ohol

con

sum

ed

References

Boyle P., Boffetta P., Lowenfels A.B., et.al. (2013) Alcohol: Science, Policy, and Public

Health

Retrieved from:

http://www.oxfordscholarship.com/view/10.1093/acprof:oso/9780199655786.001.0001/

acprof-9780199655786-chapter-13

Droomers M., Schrijvers C.T., & Stronks K., (1999). Educational differences in excessive

alcohol consumption: the role of psychosocial and material stressors.

Retrieved from http://europepmc.org/abstract/MED/10419792

Strand B.H., Steiro A. (2000). Alcohol consumption, income and education in Norway, 1993-

2000.

Retrieved from http://europepmc.org/abstract/med/14600708

http://europepmc.org/abstract/med/14600708

http://europepmc.org/abstract/MED/10419792

ECON 311 Project 1

Documents

Transcript of ECON 311 Project 1