As one would probably expect, the standard normal distribution is standardized. When working with distributions, one usually looks for intervals within which a value lies. E.g., One is asking: With which probability a value y lies between y1 <y < y2 ? Standard normal distribution is the best way to calculate such a probability. First, you standardize your y values […]
Quantitative Easing refers to an expansionary monetary policy of the European Central Bank – ECB (or another Central Bank). Usually, the ECB buys bonds. Therefore, the amount of money in the economy gets larger, and bond prices rise. As the amount of money becomes higher, the interest rates get lower. The lower interest rates (in theory) lead to greater consumption […]
Formula Portfolio return: the return of asset 1 * weights of asset 1 + the return of asset 2 * weight of asset 2 …. and so on
Correlation The correlation coefficient shows you the linear relationship (and also the strength of this relationship) between two variables (eg. observations). It can take a value within the range of -1 and +1. Therefore correlation is standardized. + 1 suggests a strong positive relationship and -1 suggests a strong negative relationship. So if it is +1 one it means if […]
Mostly when you talk about the average you actually talk about the arithmetic mean. The arithmetic mean is useful if one wants to look at independent variables. Eg. for the average income of 2 different lawyers. 2000 Euro + 4000 Euro / 2 Lawyers = Lawyers average =3000 Euro The geometric mean ensures that the ratio of each number towards […]
If you want to represent a lot of data in one table you could use ways such as a histogram. A histogram separates your data points into groups and shows you how many data points are in each group. Therefore a histogram shows you the relative frequency of data values. Additionally, a histogram is a great tool to look at […]
Variance is a measurement of distribution. Variance measures the dispersion of observations from their mean value (mü). The higher the variance, the more dispersed the observations are from their mean. Formula in case you have 3 observations : ((observation point 1 – mean) + (observation point 2 – mean) + (observation point 3 – mean))^2 / n (n means number […]
Normal distributions.) Are unimodal – they have one “high” peak.) Symmetrical shaped – mean mode median are the same An example for normal distribution would be the size of male students. To calculate the expected value, you calculate the weighted mean. -> probability * value (eg size) Eg. 0,1 * 1 + 0,2 * 2 … The expected value is […]
Mean, Median, Mode -> these are measures of central tendency Variance, Standard Deviation, Range, Minimum, Maximum, Kurtosis, Skewness -> these are dispersion measures
Nominal: A ranking/order of the variables is not possible and ther is no standardized difference between th variables. Eg. colours (blue, red etc.) Ordinal: A ranking/order of the variables is possible, but there is no standardized difference between th variables. Eg. schoolgrades from 1-5. Like the difference between 1 and 2 isnt exactly the same as the difference between 3 […]