correlation coefficient measures how related 2 variables are measures how related 2 variables are...
TRANSCRIPT
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!
Scatter Plots
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
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
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.
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
*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
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)
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??
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
Stage One = “High stationary”What is happening with CBR and CDR?
Stage Two = “Early Expansion”
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
Stage Four = Low Stationary
What does it mean to be overpopulated?
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
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