Help.
Chat with our AI personalities
Two variables are said to be positively correlated if an increase in one is accompanied by an increase in the other. There need not be any causal link between these changes.
Correlation between two variables implies a linear relationship between them. The existence of correlation implies no causal relationship: the two could be causally related to a third variable. For example, my age is correlated with the number of TV sets in the UK but obviously there is no causal link between them - they are both linked to time.
The normal distribution is a statistical distribution. Many naturally occurring variables follow the normal distribution: examples are peoples' height, weights. The sum of independent, identically distributed variables - whatever their own underlying distribution - will tend towards the normal distribution as the number in the sum increases. This means that the mean of repeated measures of ANY variable will approach the normal distribution. Furthermore, some distributions that are not normal to start with, can be converted to normality through simple transformations of the variable. These characteristics make the normal distribution very important in statistics. See attached link for more.
Box plots are box-and-whiskers plot. Basically, it represents a set of data by marking its five number summary: lowest, quartile 1, median, quartile 3, and highest. Moreover, it also shows a dotted connection to outliers. See the link in the related links section below for an example of what it looks like.
This link gives you an excellent multiplication table and some tips.Please see related link below.