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1.3 The Power of Visualizing Data - Trends

1.3 The Power of Visualizing Data - Trends

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1.3 The Power of Visualizing Data - Trends. a) Create a scatter plot. Example 1. Source: Statistics Canada, CANSIM table 252-0051. b) Add a line of best fit and describe the correlation. Approximate the equation of the line. - PowerPoint PPT Presentation

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Page 1: 1.3 The Power of Visualizing Data - Trends

1.3 The Power of Visualizing Data - Trends

Page 2: 1.3 The Power of Visualizing Data - Trends

Example 1

a) Create a scatter plot.

YearNumber of Homicides

1998 558

1999 538

2000 546

2001 553

2002 582

2003 549

2004 624

2005 663

2006 606

2007 594

2008 611

Source: Statistics Canada, CANSIM table 252-0051

500

540

580

620

660

700

1998 2000 2002 2004 2006 2008

Number of Canadian Homicides 1998 - 2008

500

540

580

620

660

700

1998 2000 2002 2004 2006 2008

Year

Number of Canadian Homicides 1998 - 2008

500

540

580

620

660

700

1998 2000 2002 2004 2006 2008

Year

Page 3: 1.3 The Power of Visualizing Data - Trends

b) Add a line of best fit and describe the correlation. Approximate the equation of the line.

Number of Canadian Homicides 1998 - 2008

500

540

580

620

660

700

1998 2000 2002 2004 2006 2008

Year

Number of Canadian Homicides 1998 - 2008

500

540

580

620

660

700

1998 2000 2002 2004 2006 2008

Year

Graph slopes upwards to the right. Positive correlation.

Most points (but not all) are close to the line. Moderately strong correlation.

y-intercept is approximately 540.line rose approximately 90 units in approximately 10 years. Slope = 9

y =9x + 540 (x = 0 corresponds to the year 1998)

Page 4: 1.3 The Power of Visualizing Data - Trends

c) Another (more accurate) line of best fit is know as a median-median line. Determine its equation.

YearNumber of Homicides

1998 558

1999 538

2000 546

2001 553

2002 582

2003 549

2004 624

2005 663

2006 606

2007 594

2008 611

Source: Statistics Canada, CANSIM table 252-0051

Step 1: Split data into 3 equal sized groups. (middle can be different by 1)

Step 2: Find median of each group

1st Group

x: {1998, 1999, 2000, 2001} Median = (1999+2000)/2 = 1999.5

y: {538, 546, 553, 558} Median = (546+553)/2 = 549.5

2nd Group

x: {2002, 2003, 2004} Median = 2003

y: {549, 582, 624} Median = 582

3rd Group

x: {2005, 2006, 2007, 2008} Median = (2006+2007)/2 = 2006.5

y: {594, 606, 611, 663} Median = (606+611)/2 = 608.5

Page 5: 1.3 The Power of Visualizing Data - Trends

1995 x = -3

y = 8.43x + 540 (x = 0 corresponds to the year 1998)

d) Use the equation to predict the number of homicides in 1995 and 2010.

y = 8.43(-3) + 540

y = 514.71

515 homicides in 1995.

2010 x = 12

y = 8.43(12) + 540

y = 641.16

641 homicides in 2010.

e) What year will the homicide rate be approximately 700

y = 8.43x + 540

700 = 8.43x + 540

160 = 8.43x

x = 19

In 2017 there will be 700 homicides.

Page 6: 1.3 The Power of Visualizing Data - Trends

Example 2Create a scatter plot corresponding to each set of data. Describe the trends.

Gold Owned

# of Pirate Ships

150 650 2100 5250 9200 8

0

2

4

6

8

10

0 50 100 150 200 250

There is a strong positive correlation between the wealth of a pirate and the number of ships they own. For every additional 25 gold pieces they are able to own 1 additional ship.

# of Pirate Ships

Vacations days (Last 2 years)

6 1501 3504 45010 509 250

There is a weak negative correlation between the number of ships they own and how much vacation time they take. For every additional ship they own they take approximately 40 fewer days off in a 2 year period.

0

100

200

300

400

500

0 2 4 6 8 10