The Human Development Index ( Hdi ) And The Gdp Per Capita

Cross-tabulation and chi square will be use to organize the data do that determining the counts or percentages for combinations of categories across two or more categorical variables and investigate the relationship between variables will be easy. Questions like:

The Gross Domestic Product (GDP) per capita is the standard measure of average income used by the mainstream economics. We all know it measures the total value of goods and services produced in this country in a given year. This can help us learn by how poor and rich the people are in the country so to say. The GDP Per Capita is not telling the truth because most people don’t get the average income they put out, most get less then it. The GDP also doesn’t show the goods that are made from farmers for their own family or

17 In regression analysis, the coefficient of determination R2 measures the amount of variation in y

scores; (b) describe in words the general pattern of correlation, if any; (c) figure the correlation coefficient; (d) figure whether the correlation is statistically significant (use the .05 significance level, two-tailed); (e) explain the logic of what you have done, writing as if you are speaking to someone who has never heard of correlation (but who does understand the mean, deviation scores, and hypothesis

1. Prepare a graph of the data. On this same graph, plot a 12-month moving average forecast. Discuss any apparent trend and seasonal patterns.

What is the r-value? Does the r-value suggest a positive or negative correlation? Is the correlation weak or strong? Looking at the significance value, is the correlation significant?

Feedback: A strong correlation exists when the plotted ordered pair points are close to the line of best fit. If the points line up exactly on the line of best fit, there is a perfect correlation. The

the correlation is 0.668; the equation of regression is CREDITS=11.7475*AGE-174.356; the slope is 11.7475 which is positive; when the predictor variable AGE increase, the response variable CREDITS also strongly increase; for instance, when AGE increase by 1, the CREDITS will increase 11.7475. There are some outliers may affect the correlation. Based on the graphs and data above, we can find out a student who is older with a litter lower GPA, but has very higher credits; the student with higher credits also has high GPA.

"There are several different kinds of relationships between variables. Before drawing a conclusion, you should first understand how one variable changes with the other. This means you need to establish how the variables are related - is the relationship linear or quadratic or inverse or logarithmic or something else" ("Relationship Between Variables ", n.d)

The R2 value is a statistical measurement of how close the data is from the linear regression line and indicates the variation in the values from the relationship of two variables. In graph 1, the R2 value is 0.60497, which indicates a moderate positive correlation. This suggests that around 60% of the variation in the mean age among different football teams can be predicted from the relationship between the number of wins and the mean age of the team. Contrarily, 40% of the variation in mean team ages cannot be

[pic] [pic] Regression Analysis: CRIMES versus URBAN The regression equation is CRIMES = 737.0 + 57.18 URBAN S = 917.074 R-Sq = 45.7% R-Sq(adj) = 44.6% Analysis of Variance Source DF

    I am going to compare these two variables by doing a scatter plot and finding the line of best fit. I am also comparing the two variables in two histograms and a chi-squared test.

3 After collecting all the data, I constructed a graph with two lines of best fit and determined where they intersect.

This is due in part because of the unequal wealth distribution. The top one percent of the richest people own forty six percent of the global wealth. This wealth being held by the rich would not be a problem if they were not so selfish with their earnings. The distribution of wealth leads to the subsequent unequal distribution of resources. Some issues this raises are human settlement and population distribution, economic activities, trade and quality of life. Certain indicators can be expended in order to measure a nation’s wealth and they include: Gross Domestic Product (GDP), Gross National Income (GNI) and Human Development Index (HDI). The Gross Domestic Product is the total value of all goods and services. This is a good indicator of what the country is like in relation to their products being sold. The GNI is the GDP plus the income from foreign investors minus the money paid out to foreign investors. The GNI and GDP are not always equal between or within countries. The HDI captures the health, education and income of any given area. It is often a more accurate depiction of what the people are like.

Scatter diagram purpose is to show how much one variable is affected by another. These charts will be used to gather the data; determine the high and low values for each factor. Decide which factor will be plotted on which axis. Theorizing a cause and effect relationship put the suspected cause on the horizontal axis and the alleged effect on the vertical axis. Draw and label the axes clearly. Make the axes roughly the same length, creating a square plotting area. Label each axis with increasing values from left to right, and from bottom to top. Label each axis to match the full range of values for that factor. In other words, make the lowest numerical label slightly less than the lowest data value, and the highest name slightly greater than the highest value. The data should fill the whole plotting