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Correlation Coefficient Measures how related 2 variables are Shown as #s b/t +1 and -1 Determines: STRENGTH Closer to 1/-1 = strong correlation Closer to 0 = weak/no correlation DIRECTION (positive or negative) Determined through statistical magic!

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Page 1: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

Correlation Coefficient• Measures how related 2 variables are• Shown as #s b/t +1 and -1• Determines:

– STRENGTH• Closer to 1/-1 = strong correlation• Closer to 0 = weak/no correlation

– DIRECTION (positive or negative)

• Determined through statistical magic!

Page 2: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

Scatter Plots

Page 3: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

1. Birth Rate (CBR)• Calculated how?• High =40+ Low = <15• Wealth and CBR

– Positive/negative correlation?– Exceptions: China (12) E. Europe (12)Low wealth and

low CBR. Otherwise, high wealth, low CBR.• Highest: Chad (51) and Niger (50)• Lowest: Germany/Bosnia/Japan @ 8• U.S.: 13• World average = 20• MDCs = 11, Dev = 22, w/o China = 25, LDCs = 34

Page 4: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

2. Death Rate (CDR)• Calculated?• High = 18 Low = <10• Stat can change dramatically

– War, pandemic, famine, etc. – W. Hem in 16th Century was 900/1,000

• Correlation Wealth and CDR?– NOT Really?

• Highest: Sierra Leone (18) & E. Europe ~15• Lowest: U.A.E (1) and Qatar & Oman (2)• U.S.: 8

Page 5: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

3. Natural Rate of Increase (NRI) or (RNI)

• Calculated how?• Ex: CBR 20 CDR 5 THEN NIR = 15/1000 = 1.5%• High = 2-3% Low = Less than 1%• USA formula CBR 13.8 minus CDR 8.4 = 5.4/1,000

= .54%• Europe: Denmark, Finland, Iceland, Ireland, Norway, Sweden,

U.K., Belgium, France, Luxembourg, Netherlands, Switzerland, Albania, Kosovo, Spain have slightly pos, NRI. A number of others have a 0 or negative NRI. Why? Highest in world = Niger.

Page 6: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

4. Population growth rates (PGR)

• Calculated how?• High = 2+% Low = <1% or negative• U.S.: 13.8 (CBR) – 8.4 (CDR) + Net migration

4.3 (per 1000) = 9.7/1000 = .97%• Population Growth trends

– Negative/Positive Correlations?• Women’s rights Impact of immigration?• Economic growth• Literacy rate

Page 7: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

*Why would a country want a pro-natalist policy ?

• replaces those lost in war and civil unrest

• build up the military

• replace retiring folks in the workforce

• support the increasing number of seniors

• occupy parts of a country that are virtually empty

• help develop the resources of a state

• lead to economic growth

• increase majority/minority percentages

• gain more influence internationally

Page 8: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

Why would a country want an anti-natalist policy ?

• cannot afford to provide for them

• overpopulation concerns - limited available resources local, national, international SCALE

• allow more women in the workforce and boost economy

• repress a group of people separate policy for certain groups or different applications of the policy (see 2nd last slide)

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6. Doubling Time• Def.?• Assumption?? Constant PGR• World’s doubling time is 64 years

– As TFR increases, doubling time ___________.– At 1% growth rate it takes 70 years to double– At 2% growth rate takes 35 years to double

• U.S. = 70/.9% = 78• What is Eastern Europe’s doubling time?• Japan’s??

Page 10: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

7. Dependency ratio• Calculated:

(Pop. <15) + (65+) divided byworking-age population (those aged 15-64)

• Dependency ratio tells us how strained working pop. is– Ex. Dependency ratio of 0.9 means there are 9

dependants for every 10 working-age people• Keep in mind:

– Negative correlation b/t dependency ratio and the ability to take care of dependents

Page 11: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1
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Stage One = “High stationary”What is happening with CBR and CDR?

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Stage Two = “Early Expansion”

Page 14: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

Stage Three = “Late Expanding”• Declines in birth rate WHY?

– Drop in IMR– Urban life too expensive/not enough space– Gains for women

• Increase in literacy rate• More access to education

– Postponing marriage– (Contraceptives were not widely available in the first

half 20th)• MDCs moved into Stage 3 during early 20th • If LDCs are in Stage 3, they did so in the last 20

years

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Stage Four = Low Stationary

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What does it mean to be overpopulated?

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II. Population Theories

Thomas Malthus published his essay in 1798

• Malthus’ three assumptions (This was before the Industrial Revolution)– food grows __________– pop grows __________– Britain was a closed sys.

• = People will eventually run out of food

Page 18: Correlation Coefficient Measures how related 2 variables are Measures how related 2 variables are Shown as #s b/t +1 and -1 Shown as #s b/t +1 and -1

Our text says there are 3 types of Push & Pull factors

Political Economic Environmental

• Net migration– Immigrants – emigrants (# out of 1000)– Net in-migration– Net out-migration

Ravenstein’s 12 laws of migration