By Chris Gallant Updated April 19, — There are numerous ways to measure portfolio performance and determine if the investment strategy is successful. Among all of these metrics, investment professionals most often use means to estimate growth rates and returns on their portfolios.

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The mean value of life satisfaction for male is about 7. From this pair of figures it is obvious that the life satisfaction for female is more flexible than male.

The mean value of satisfaction for those who is not alone is about 7. 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. The average life satisfaction for people with income level 1 is 7.

Furthermore, the sample variance for income 1 is 4. 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.

And 0 represents male while 1 means female. Thus when other factors are the same, life satisfaction of female is slightly less than man. The result is not exactly what I have supposed. My prior assumption is? As people grow old, they tend to be more satisfied with their life. I reckon that as people grow old they might be easy to feel satisfied about life.

For young people they are more likely to be ambitious and do not feel enough about what they have. The result is in accordance with what I expected. The more people earned the more satisfied they feel about their life. The result is correspondent with what I expected.

Estimated sample regression function: In my opinion, when other variables remains stable people with religion compared with people without religion are more satisfied with their lives, since people with religion have spiritual sustenance.

Hours spend on sleep every week can also be set as another independent variable 0? I suppose that people who spent more time on sleep will be happier than those got less time on sleep.

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Coefficients as calculated in part c: As I change the portfolio of coefficient, the new sum of squared residuals ever lower than the original SSE. The coefficients we got by applying the OLS model contributes to the most minor sum of squared residuals.

Hence, all the six variables together have significant effect on sales. In other words, the set of explanatory variables in the model can significantly explain the dependent variable life satisfaction.So the evidence suggests that income and life satisfaction tend to go together (which still doesn’t mean they are one and the same).

Important life events such as marriage or divorce do affect our happiness, but have surprisingly little long-term impact. Happiness and life satisfaction, as well as many other social and cultural.

HUMAN MOVEMENT Physical activity and life satisfaction in blind and visually im Paired individuals Jakub Łabudzki 1, 2, tomasz tasiemski 1 * 1 University School of Physical Education, Poznań, Poland 2 Osteo-Reh Physiotherpay Clinic, Pniewy, Poland AbSTRACT Purpose.

Physical activity (PA) is known to have a positive influence on many physical and psychological aspects of human. Health status is one of the basic factors of a high quality of life and the problem of the acceptance of illness is important for adaptation to the limitations imposed by it.

The purpose of the study was the evaluation of the quality of life, satisfaction with life and the acceptance of illness by. In the research, the arithmetic mean, level and standard deviations were calculated to determine the perception levels of the teachers about life satisfaction.

The “t” test and the one-way analysis of variance were used to test whether there was a significant difference between the perceptions of the groups. The “average” or “arithmetic mean” of a set of numbers means you add the numbers and divide it by the number of terms. average = sum of terms.

Mobility was found to be positively correlated with quality of life (r = , p.

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