I. Data analysis

Data analysis

I.1. Normal distribution

Most processes are described fairly accurately by the normal distribution. The normal distribution is used in chemistry, physics, and many other fields of science

I.2. Poisson distribution

When we operate with the value of the number of events in a time interval, for example, three sandwiches a day, then we use the Poisson distribution

I.3. The law of distribution of a random variable

How can we mathematically describe that on average we drink two cups of tea a day? What is likely to be +20 in June? That the gasoline consumption will be 8L/100km? The distribution law is a mathematical model of events

I.4. Parameters of the discrete distribution law

The main parameters of the distribution law: mean, quantile, deviation, confidence interval

I.5. Binomial distribution

I.6. Statistical hypothesis

With a probability of 30%, the milk will sour until tomorrow. And tomorrow we need to sell three cups of milk. Should I buy a new bottle? What if I don't buy it, and the milk turns sour? The statistical hypothesis will give the answer in numbers

I.7. Normality of the distribution

Some statements are based on the premise that the distribution is normal, but how do you know how normal the real distribution is?

I.8. Analysis of variance

It happens that we conduct a number of experiments, but we cannot find a pattern. Why is the tea delicious, then not? ANOVA is a method for finding the reason for changing the result. Is it the quality of the tea or my mood?

I.9. Correlation analysis

Is there a connection between the changes in values? Two numbers change, but in order to draw a conclusion about the linear dependence of the change, it is necessary to resort to correlation analysis