X and y relationship calculator

Correlation Coefficient (ρ) Formula, Example, Calculator

x and y relationship calculator

A Pearson correlation coefficient calculator (offers scatter diagram, full details of the calculations performed, etc). Pearson, Spearman, Kendall correlation calculators with significance test. It tells you what kind of relationship exists between the two variables, and also the If you draw a diagram with the two values (on axes X and Y), then the stronger . Linear regression calculator. 1. Enter data. Label: X. Y. 1. 2. 3. 4. 5. 6. 7. 8. 9.

Online calculator: Relation between two numbers

After entering the datapairs, a scatterplot diagram immediately appears where you can visually check how the values move together and you can also see the strength of the correlation coefficientand the sureness p-value of the result is also shown. Pearson or Spearman or Kendall? Pearson correlation coefficient is the most commonly used method, although it is very sensitive to outliers.

  • Correlation Coefficient Calculator
  • Relation between two numbers
  • Correlation Test Online Calculator

Spearman and Kendall correlation coefficients are not sensitive to outliers but their explanatory power is lower. Read our correlation coefficient demistified blogpost. Why you can't be absolutely sure? Because the experienced correlation between X and Y columns may come from the work of coincidence.

Your data comes from an experiment or observation that is not exactly repeatable, they are not accurate, there is a fluke in them.


If you would measure again, you would get different values. This distribution causes that you can be sure about the relationship between the things only if you have several data and if the correlation is strong.

x and y relationship calculator

The more data you have and the more strong the relationship between values, the bigger the certainty. If you have a small 12 rows chart, in which you have the seasons and their average temperatures and the number of computers sold in that season, then if there is a weak correlation between the values, this may be the work of coincidence, so you cannot say it with complete certainty that computer sales are in connection with the temperature. However if you have lines of datapairs about the temperature of each days and the number of ice creams sold then - because of the many data and strong correlation - it is already sure that there is a relationship.

What does the p-value tell you? This certainty value shows, how likely it is, that the observed correlation coefficient came out only by coincidence.

A low p-value below 0. A high p-value above 0.

x and y relationship calculator

What does low sureness mean? It means that from these numbers it cannot be known whether there is a correlation between the two values or not. In business, a well-dressed man is thought to be financially successful. A mother knows that more sugar in her children's diet results in higher energy levels.

Dependence or Statistical Relationship Calculator

The ease of waking up in the morning often depends on how late you went to bed the night before. Quantitative regression adds precision by developing a mathematical formula that can be used for predictive purposes. For example, a medical researcher might want to use body weight independent variable to predict the most appropriate dose for a new drug dependent variable.

The purpose of running the regression is to find a formula that fits the relationship between the two variables.

x and y relationship calculator

Then you can use that formula to predict values for the dependent variable when only the independent variable is known. A doctor could prescribe the proper dose based on a person's body weight.

Linear Functions

The regression line known as the least squares line is a plot of the expected value of the dependent variable for all values of the independent variable. Technically, it is the line that "minimizes the squared residuals".

x and y relationship calculator

The regression line is the one that best fits the data on a scatterplot.