Arithmetic Mean and Life Satisfaction
PART A:
i) Male:
Female:
The mean value of life satisfaction for male is about 7.7459 while for female is 7.7101, which proves there is no significant different life satisfaction between male and female, thus gender does not affect life satisfaction a lot. But when it comes to sample variance, for male is 2.5684 while for female is 3.0081. From this pair of figures it is obvious that the life satisfaction for female is more flexible than male. Man’s life satisfactions are easy to be affected by other variables. I assume “GENDER” does not affect life satisfaction.
ii) Not alone:
Alone:
The mean value of satisfaction for those who is not alone is about 7.8055 meanwhile the figure for those who live alone is 7.32584. There is a big gap between these two data, which implies that “ALONE” have a significant impact on people life satisfaction. Additionally, sample variance for alone is much higher than for not alone, which implies other variables affect people who live alone severely and affect people not alone a little. I assume “ALONE” affects “LIFESAT” vitally, since people feel happier when they are accompanied by others but for those who are alone are easy to feel lonely and sad.
iii) Income 1:
Income 6:
The average life satisfaction for people with income level 1 is 7.4426 while for people with income level 6 is 8.2069, which means people with high income are more satisfy with their life than those with low income. Furthermore, the sample variance for income 1 is 4.37941 while for level 6 is only 0.74138, which tells that people with relatively high income enjoys a relatively stable high life satisfaction. Personally, I reckon that people with high income are happier than those with low income, as they are more capable to purchase what they like which makes people satisfy with their lives.
PART B:
i)
Y=7.746-0.036X (gender)
For gender, the ß2 is -0.036 which means gender has negative relationship with
i) Male:
Female:
The mean value of life satisfaction for male is about 7.7459 while for female is 7.7101, which proves there is no significant different life satisfaction between male and female, thus gender does not affect life satisfaction a lot. But when it comes to sample variance, for male is 2.5684 while for female is 3.0081. From this pair of figures it is obvious that the life satisfaction for female is more flexible than male. Man’s life satisfactions are easy to be affected by other variables. I assume “GENDER” does not affect life satisfaction.
ii) Not alone:
Alone:
The mean value of satisfaction for those who is not alone is about 7.8055 meanwhile the figure for those who live alone is 7.32584. There is a big gap between these two data, which implies that “ALONE” have a significant impact on people life satisfaction. Additionally, sample variance for alone is much higher than for not alone, which implies other variables affect people who live alone severely and affect people not alone a little. I assume “ALONE” affects “LIFESAT” vitally, since people feel happier when they are accompanied by others but for those who are alone are easy to feel lonely and sad.
iii) Income 1:
Income 6:
The average life satisfaction for people with income level 1 is 7.4426 while for people with income level 6 is 8.2069, which means people with high income are more satisfy with their life than those with low income. Furthermore, the sample variance for income 1 is 4.37941 while for level 6 is only 0.74138, which tells that people with relatively high income enjoys a relatively stable high life satisfaction. Personally, I reckon that people with high income are happier than those with low income, as they are more capable to purchase what they like which makes people satisfy with their lives.
PART B:
i)
Y=7.746-0.036X (gender)
For gender, the ß2 is -0.036 which means gender has negative relationship with