Investigation on the effects Investigation on the effects of data manipulationof data manipulation

Part 1: Research on Gun DeathsPart 1: Research on Gun Deaths

Part 2: Graphing and data manipulation Part 2: Graphing and data manipulation

Researchers: Matt Johns, Will Parkinson Researchers: Matt Johns, Will Parkinson and James Pye for Mr. Lieff, Carleton and James Pye for Mr. Lieff, Carleton Place High SchoolPlace High School

Part 1: Gun death ResearchPart 1: Gun death Research

Initially we attempted to obtain data on Initially we attempted to obtain data on the relations between gun deaths and the relations between gun deaths and various trends in Canada.various trends in Canada.

We will show a portion of the data we We will show a portion of the data we collected.collected.

The research will investigate trends and The research will investigate trends and influences that certain government bills influences that certain government bills have had on gun deaths in Canada.have had on gun deaths in Canada.

Cause of Deaths in Canada Unknown 1.4

Other¹ 0.9

Vehicle 0.9

Poisoning 1.4

Fire (burns/smokeinhalation) 1.4

Shaken Baby Syndrome1.4

Strangulation/suffocation8.5

Beating 22.2

Stabbing 30.9

Shooting 30.9

Firearm Homicides

0

50

100

150

200

250

300

Year

Nu

mb

er

of

de

ath

s

Total gun deaths*** Handgun Rifle other

Bill - C51Bill - C150 Bill - C17 Bill - C68

Bill C-150Bill C-150 The passage The passage

of Bill C-150 of Bill C-150 was May was May 1414thth, 1969 , 1969

The Bill The Bill deals with deals with abortion abortion rights.rights.

The moral The moral and political and political content was content was downplayed. downplayed.

It legalized It legalized contraception and contraception and therapeutic abortion, therapeutic abortion, but it assigned doctors but it assigned doctors control over women's control over women's reproductive decisions.reproductive decisions.

Bill C-51Bill C-51 Enforced since Enforced since

1977 1977 This Act requires This Act requires

acquisition acquisition certification for all certification for all firearms, restricts firearms, restricts the availability of the availability of some types of some types of firearms to certain firearms to certain types of types of individuals.individuals.

It establishes It establishes procedures for procedures for handling and handling and storing firearms, storing firearms, requires permits requires permits for those selling for those selling firearms, and firearms, and increases the increases the sentences for sentences for firearm offences.firearm offences.

Bill C-17Bill C-17

The overarching goal of both the previous The overarching goal of both the previous bill and this bill created in 1991 named bill and this bill created in 1991 named “Firearms Control Initiative” was meant to “Firearms Control Initiative” was meant to enhance public safety from firearms enhance public safety from firearms accidents and suicides as well as reducing accidents and suicides as well as reducing criminal firearms misuse thereby making criminal firearms misuse thereby making Canada a safer society. Canada a safer society.

Bill C-68Bill C-68 The bill imposes a The bill imposes a

mandatory mandatory minimum sentence minimum sentence of four years in of four years in prison, in addition prison, in addition to a lifetime to a lifetime prohibition against prohibition against possession of a possession of a firearm upon firearm upon conviction of any conviction of any of ten specific of ten specific violent offences violent offences with a firearm.with a firearm.

Proclaimed into Proclaimed into law on January 1, law on January 1,

1996.1996.

The offences affected are: The offences affected are: manslaughter, attempted manslaughter, attempted murder, sexual assault with a murder, sexual assault with a weapon, robbery and criminal weapon, robbery and criminal negligence causing death, negligence causing death, causing bodily harm with intent, causing bodily harm with intent, aggravated sexual assault, aggravated sexual assault, kidnapping, hostage taking, kidnapping, hostage taking, extortion.extortion.

Part 2: An Investigation Part 2: An Investigation on Data Manipulation.on Data Manipulation.

We will show how anybody can We will show how anybody can manipulate data to display any trend they manipulate data to display any trend they wish.wish.

We will use different graphing techniques We will use different graphing techniques and mathematical functions to display the and mathematical functions to display the data.data.

Changing the ScaleChanging the Scale

Total Income y = 1000x - 2E+06

R2 = 1

10000

15000

20000

25000

30000

35000

40000

45000

50000

55000

1959 1964 1969 1974 1979 1984 1989 1994 1999

Year

Am

ou

nt

in $

By Changing the scale on a graph we are able By Changing the scale on a graph we are able to change the appearance of a relation.to change the appearance of a relation.

As seen the previous graph the was a line with As seen the previous graph the was a line with a R^2 of 1.0 and slope of 1000.a R^2 of 1.0 and slope of 1000.

In the next graph observe how the slope and In the next graph observe how the slope and equation remain the same although the graph equation remain the same although the graph looks much different.looks much different.

By changing the scale on the Y axis you can By changing the scale on the Y axis you can change the appearance of the slope of a change the appearance of the slope of a graph.graph.

y = 1000x - 2E+06

R2 = 1

-100000

-50000

0

50000

100000

150000

1958 1963 1968 1973 1978 1983 1988 1993 1998

Year

Inco

me

in $

Total Income

Small Sample SizeSmall Sample Size

Total Immagrant Population Vs. Gun Deaths

y = -4E-10x2 + 0.001x - 472.62R 2 = 0.9696

0

50

100

150

200

250

300

0 500000 1000000 1500000 2000000

Too Few Data PointsToo Few Data Points Here it shows that a large Here it shows that a large

immigration population leads immigration population leads to a large amount of gun deaths to a large amount of gun deaths but once the immigrant but once the immigrant population reaches 1.4 million population reaches 1.4 million the gun deaths begin to the gun deaths begin to decrease.decrease.

There is obvious problem with There is obvious problem with the data in the way in which it the data in the way in which it is presented because this is presented because this relation is improbable.relation is improbable.

As you can see there are only 4 As you can see there are only 4 data points on this graph that data points on this graph that the curve is fitting to which the curve is fitting to which makes the curve easily fit the makes the curve easily fit the data.data.

This explains why this curve This explains why this curve only has as R^2 of 0.96only has as R^2 of 0.96

Total Immagrant Population Vs. Gun Deaths

y = -4E-10x2 + 0.001x - 472.62

R2 = 0.9696

0

50

100

150

200

250

300

0 200000 400000 600000 800000 1000000 1200000 1400000 1600000 1800000 2000000

The Log FunctionThe Log Function

U.S. Government Debty = -1.4478x2 + 5.0287x - 114.35R 2 = 0.9968

-14000

-12000

-10000

-8000

-6000

-4000

-2000

0

-2 8 18 28 38 48 58 68 78 88 98

time(quarterly)

To

tal $

, in

mill

ion

s

Y = 1/Log(x)Y = 1/Log(x)

By using the logarithmic function on x we can By using the logarithmic function on x we can change the appearance of the graph.change the appearance of the graph.

Although the equation changes the data that is Although the equation changes the data that is used remains the same, it is just placed into used remains the same, it is just placed into the equation y = 1/log(x)the equation y = 1/log(x)

This is used to show how the U.S. Government This is used to show how the U.S. Government debt does not appear to be increasing at a debt does not appear to be increasing at a exponential rate like it actually is.exponential rate like it actually is.

US Government Debty = 0.6596Ln(x) + 0.9747R 2 = 0.9517

1 .5

2

2 .5

3

3 .5

4

4 .5

0 10 20 30 40 50 60 70 80 90

Time(quarterly)

Logarithmic ScaleLogarithmic Scale

R2 = 1

-20000

-15000

-10000

-5000

0

5000

10000

15000

20000

25000

30000

0 5 10 15 20 25 30 35 40 45

R2 = 1

-20000

-15000

-10000

-5000

0

5000

10000

15000

20000

25000

30000

1 10 100

As you have noticed the scale on the x-axis of As you have noticed the scale on the x-axis of the graph has a very weird structure.the graph has a very weird structure.

This is called a logarithmic scale or a semi-log This is called a logarithmic scale or a semi-log graph.graph.

1 to 10 takes up the same amount of space as 1 to 10 takes up the same amount of space as 10 to 100. Similarly 10 to 100 takes up the 10 to 100. Similarly 10 to 100 takes up the same space as 100 to 1000.same space as 100 to 1000.

Doing this changes a linear equation into a Doing this changes a linear equation into a equation with a curve.equation with a curve.

In this case it makes the data look like it is In this case it makes the data look like it is decreasing at a faster rate than it really is.decreasing at a faster rate than it really is.

CoincidencesCoincidences

Population vs. Bacon PricesPopulation vs. Bacon Prices

0

1

2

3

4

5

1995 1996 1997 1998 1999 2000 2001 2002 2003

Year

Bacon Prices(per pound)

Population of Canada X 10 000 000

You can use a coincidence to find a You can use a coincidence to find a relation that shouldn’t exist. relation that shouldn’t exist.

Using this people can draw false Using this people can draw false conclusions on the data.conclusions on the data.

Conclusion:Conclusion:

We have shown that data can be manipulated We have shown that data can be manipulated to show any relation needed to be expressed.to show any relation needed to be expressed.

All that needs to be done is footnote what has All that needs to be done is footnote what has actually happenedactually happened

By doing this most people wont pick up on the By doing this most people wont pick up on the footnote and the people who made the graph footnote and the people who made the graph cannot get in trouble for ‘falsified data’cannot get in trouble for ‘falsified data’

You should always look for stars that lead to You should always look for stars that lead to footnotes to truly understand thefootnotes to truly understand the data. data.