App Profile: Line-Fit
Android / Games / Puzzles
Line-Fit
Installs:
Rating:
0.00
Total Reviews:
0
Top Countries:
GR, US, TH
< $5k
/mo
< 5k
/mo
Reviews: What People Think About Line-Fit
very sad student
Rating: 1/5
I got this app because my school calculator broke and this is absolutely horrendous every time you enter the app it starts off with a new randomly generated line which wouldn’t be that bad if there was an option to clear but there isn’t so you either have to edit it and delete each individual coordinate before writing in a new one or just delete all the coordinates you can then try to work with their system and even after typing in all the correct coordinates it doesn’t show the coordinates in the correct place
About Line-Fit
The Line-Fit app uses linear regression to model the relationship between two variables (x and y) by fitting a linear equation to observed data. One variable is considered to be an explanatory (independent) variable, and the other is considered to be a response (dependent) variable.
A linear regression line has an equation of the form Y = a + bX, where X is the explanatory variable and Y is the dependent variable. The slope of the line is b, and the intercept is a (the value of y when x = 0).
To measure the association between the two variables the correlation coefficient is used, which is a value between -1 and 1 indicating the strength of the association of the observed data for the two variables.
The coefficient of determination, R2, measures how close the data are to the fitted regression line. In general, higher values of R2 indicate a better fit of the model to the given data. R2 is always positive and equal to 1.0 for a perfect fit.
A linear regression line has an equation of the form Y = a + bX, where X is the explanatory variable and Y is the dependent variable. The slope of the line is b, and the intercept is a (the value of y when x = 0).
To measure the association between the two variables the correlation coefficient is used, which is a value between -1 and 1 indicating the strength of the association of the observed data for the two variables.
The coefficient of determination, R2, measures how close the data are to the fitted regression line. In general, higher values of R2 indicate a better fit of the model to the given data. R2 is always positive and equal to 1.0 for a perfect fit.
File size: 686080
Launched countries: USAUCACNFRDEGBITJPKRRUDZAOARATAZBBBYBEBMBRBGCLCOCRHRCZDKDOECEGSVFIGHGRGTHKHUINIDIEILKZKEKWLBLTLUMOMGMYMXNLNZNGNOOMPKPAPEPHPLPTQAROSASGSKSIZAESLKSECHTWTHTNTRUAAEUYUZVEVNBOKHEELVNIPYMZYEBHCYMTBJBFCGJOLAMLSNTZUGZW
Minimum OS version: 12.3
Release Date: 1560610213000
Published by Bjarne Berge
Website url: http://www.oilgasapp.com
Publisher country:
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