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" ... Correlation between economic freedom and income inequality from above table. Lower Gini coefficient ... [+] shows more equality of income. ... "
" ... Correlation is commonly expressed as a coefficient with values ranging between -1.0 and 1.0. A correlation of -1.0 shows a perfect negative correlation, while a correlation of 1.0 indicates a perfect positive correlation. A correlation of 0.0 shows no linear relationship between the movement of the two variables. They are best illustrated on a scatter plot: ... "
" ... From a financial perspective, the very low or negative correlation between cryptocurrencies and traditional asset classes such as equities, commodities, real estate, or bonds is interesting. No asset class shares similar characteristics with your average cryptocurrency. The closer the correlation coefficient (-1 perfectly negatively correlated, 0 uncorrelated, 1 perfectly positively correlated) to 0 or negative, the more interesting it becomes when building an efficient portfolio. All cryptocurrencies have a correlation coefficient around 0 (+ – 0.2) compared to the established asset classes. ... "
" ... Stability of earnings is an important factor to consider along with the absolute level of earnings growth. The R-squared, or the coefficient of determination (R2) over the last seven years was calculated for both earnings and sales. The R-squared is a measure of the degree to which plotted data falls on or close to the trendline for the data used to calculate the least-squares growth rate. If all of the plotted points fall precisely on the line, the coefficient of determination would be 100%. If none of the points bears any relationship to the trendline (which can still be mathematically calculated), the value would be zero. Thus, a higher value for R-squared indicates a higher degree of stability or predictability for the plotted points. ... "
" ... There is a concept called the “Gini Coefficient” which measures income inequality. The higher the Gini Coefficient, the more skewed the income shares are to the higher earners. The chart below graphs the Gini Coefficient and M2 since 2000. As easy money has come to dominate the scene, as indicated by rapidly rising M2, so has income inequality. The correlation coefficient between M2 and Gini is a whopping .86. This shouldn’t be a surprise, as we have seen that M2 and the S&P 500 are also highly correlated. Easy money and a rising money supply cause asset inflation which benefits the higher income classes. ... "