In: Statistics and Probability
The topic for this week is Inferential Statistics including the Chi-Square, Correlation and Regression as well as Time Series Analysis. Correlation and Regression are used in basic modeling where we forecast the value of a dependent variable based on the value of an independent variable. You may want to review the lecture entitled Correlation and Regression posted in this week’s discussion stream.
Be sure to use the Excel charting to construct a Scatterplot of two of the variables shown in the attached dataset. Once you have the Scatterplot, add the Trendline, Regression Equation and R2 following the directions discussed in the lecture. It may be instructive to identify (country) the outlier data points displayed on the Scatterplot. Discuss the meaning of the Regression Equation in terms of the independent and dependent variables. Discuss the strength of the Correlation between the Variables and the proportion of Variation Explained by the Regression Equation. Does your Linear Regression model help to understand the trend in the data? Pick any two variables and please include the chart
Worldwide | 9,003,042 | 469,220 |
United States | 2,324,956 | 121,766 |
Brazil | 1,086,990 | 50,659 |
Russia | 592,280 | 8,206 |
India | 425,282 | 13,699 |
United Kingdom | 305,289 | 42,647 |
Peru | 254,936 | 8,045 |
Chile | 246,963 | 4,502 |
Spain | 246,272 | 28,322 |
Italy | 238,499 | 34,634 |
Iran | 207,525 | 9,742 |
Germany | 191,576 | 8,961 |