Estimate/Predict the y value for a specified x value. If the specified x is within the original data's domain then this process is called estimating; if the specified x exceeds the original data's domain then this process is called predicting.

### Estimate/Predict

Model name | Formula expression | Parameters | Square sum of fitting errors | x | y |
---|---|---|---|---|---|

{0} | {1} | {2} | {3} | {4} | {5} |

## About

This app allows you to plot the scatter of your data easily as well as to work out the stats (mean sample/population standard deviation variance and correlation co-efficient etc.) of your data. Moreover it can find out the linear regression quadratic regression cubic regression and exponential regressions for your data also known as the least square fittings. According to the relation between two variables it finds the linear function quadratic function cubic function and exponential function that best fit a given set of data points.

**Copy & Paste: **

You can copy and paste data directly from a spreadsheet a tabulated data file or a comma separated values (.csv) file in the box underneath the graph area. Any character that cannot be part of a number - space comma semicolon tabulation... - is considered a column separator. The exponent can be indicated by preceding it by the character E or e for example 5.1E-1 1.78e+3 are valid numbers. Remember data must consist of two columns x and y to get the scatter graph and its regression functions.

### Stats for x

Stats | Value | Name of Stats |
---|---|---|

n | {0} | Count |

{2} | Mean | |

Sx | {4} | Sample standard deviation |

S^{2}x | {6} | Sample variance |

σx | {8} | Population standard deviation |

σ^{2}x | {10} | Population variance |

Σx | {12} | Sum |

Σx^{2} | {14} | Sum of squares |

Σxy | {1} | Sum of product |

r | {16} | Correlation co-efficient with y |

### Stats for y

Stats | Value | Name of Stats |
---|---|---|

n | {0} | Count |

{3} | Mean | |

Sy | {5} | Sample standard deviation |

S^{2}y | {7} | Sample variance |

σy | {9} | Population standard deviation |

σ^{2}y | {11} | Population variance |

Σy | {13} | Sum |

Σy^{2} | {15} | Sum of squares |

Σyx | {1} | Sum of product |

r | {16} | Correlation co-efficient with x |