for ( v=0 ; v < n_vars ; ++v )
{
double T;
- double stderr;
+ double std_error;
struct hsh_iterator g;
tab_float (t, 4, row + count, 0, gs->std_dev,8,2);
- stderr = gs->std_dev/sqrt(gs->n) ;
+ std_error = gs->std_dev/sqrt(gs->n) ;
tab_float (t, 5, row + count, 0,
- stderr, 8,2);
+ std_error, 8,2);
/* Now the confidence interval */
T = gsl_cdf_tdist_Qinv(q,gs->n - 1);
tab_float(t, 6, row + count, 0,
- gs->mean - T * stderr, 8, 2);
+ gs->mean - T * std_error, 8, 2);
tab_float(t, 7, row + count, 0,
- gs->mean + T * stderr, 8, 2);
+ gs->mean + T * std_error, 8, 2);
/* Min and Max */
tab_float (t, 4, row + count, 0, totals->std_dev,8,2);
- stderr = totals->std_dev/sqrt(totals->n) ;
+ std_error = totals->std_dev/sqrt(totals->n) ;
- tab_float (t, 5, row + count, 0, stderr, 8,2);
+ tab_float (t, 5, row + count, 0, std_error, 8,2);
/* Now the confidence interval */
T = gsl_cdf_tdist_Qinv(q,totals->n - 1);
tab_float(t, 6, row + count, 0,
- totals->mean - T * stderr, 8, 2);
+ totals->mean - T * std_error, 8, 2);
tab_float(t, 7, row + count, 0,
- totals->mean + T * stderr, 8, 2);
+ totals->mean + T * std_error, 8, 2);
/* Min and Max */
struct group_statistics *gs;
double T;
- double stderr_contrast ;
+ double std_error_contrast ;
double df;
TAB_RIGHT, contrast_value, 8,2);
- stderr_contrast = sqrt(vars[v]->p.ww.mse * coef_msq);
+ std_error_contrast = sqrt(vars[v]->p.ww.mse * coef_msq);
/* Std. Error */
tab_float (t, 4, (v * lines_per_variable) + i + 1,
- TAB_RIGHT, stderr_contrast,
+ TAB_RIGHT, std_error_contrast,
8,3);
- T = fabs(contrast_value / stderr_contrast) ;
+ T = fabs(contrast_value / std_error_contrast) ;
/* T Statistic */