How to show the regression plot in a figure?

Plot x vs y, with y plotted as the independent variable. need to find out the slope, y-intercept,t-statistic for the regression plot, p-value for the regression plot and the r^2 value.

x=[1 2 3 4 5 6 7 8 9 10]

y=[4 5 2 7 2 8 10 2 1 5]

[Hildo]

You can use the Curve Fitting toolbox and plot its object

plot(curvefitted)

or use in code the functions of this toolbox.

[KSSV]

Home work...

Answer 1

[Soumya Saxena]

I understand that you would like to plot a regression plot for the x and y values specified. If y is independent variable and x is dependent variable, you may specify them as follows:

x=[1 2 3 4 5 6 7 8 9 10]

y=[4 5 2 7 2 8 10 2 1 5]

You can define a table containing y as the independant variable and x as the response variable. The "fitlm" function takes the last variable in the table as the response variable by default.

tbl = table(y' , x')

You can then create a linear model as:

mdl = fitlm(tbl,'linear')

You can plot it as:

plot(mdl)

The model generated will have the intercept values along with the t-statistic, p value, degrees of freedom and r squared values.

The documentation of the "fitlm" function can be found at:

https://www.mathworks.com/help/stats/fitlm.html

The output should be similar to:

mdl = 

Linear regression model:
    Var2 ~ 1 + Var1

Estimated Coefficients:
                   Estimate       SE         tStat       pValue 
                   _________    _______    _________    ________

      (Intercept)       5.6144     1.9347        2.902    0.019832
      Var1           -0.024876    0.35803    -0.069479     0.94631

Number of observations: 10, Error degrees of freedom: 8
Root Mean Squared Error: 3.21
R-squared: 0.000603,  Adjusted R-Squared -0.124
F-statistic vs. constant model: 0.00483, p-value = 0.946