diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/random/_common.pyx | 4 | ||||
| -rw-r--r-- | numpy/random/_generator.pyx | 2 | ||||
| -rw-r--r-- | numpy/random/mtrand.pyx | 2 |
3 files changed, 4 insertions, 4 deletions
diff --git a/numpy/random/_common.pyx b/numpy/random/_common.pyx index 19fb34d4d..719647c3e 100644 --- a/numpy/random/_common.pyx +++ b/numpy/random/_common.pyx @@ -219,8 +219,8 @@ cdef np.ndarray int_to_array(object value, object name, object bits, object uint cdef validate_output_shape(iter_shape, np.ndarray output): - cdef np.npy_intp *shape - cdef ndim, i + cdef np.npy_intp *dims + cdef np.npy_intp ndim, i cdef bint error dims = np.PyArray_DIMS(output) ndim = np.PyArray_NDIM(output) diff --git a/numpy/random/_generator.pyx b/numpy/random/_generator.pyx index bf83c4a0c..17a52a8d5 100644 --- a/numpy/random/_generator.pyx +++ b/numpy/random/_generator.pyx @@ -1745,7 +1745,7 @@ cdef class Generator: either positive or negative, hence making our test 2-tailed. Because we are estimating the mean and we have N=11 values in our sample, - we have N-1=10 degrees of freedom. We set our signifance level to 95% and + we have N-1=10 degrees of freedom. We set our significance level to 95% and compute the t statistic using the empirical mean and empirical standard deviation of our intake. We use a ddof of 1 to base the computation of our empirical standard deviation on an unbiased estimate of the variance (note: diff --git a/numpy/random/mtrand.pyx b/numpy/random/mtrand.pyx index e5083bdf1..23cb5ea31 100644 --- a/numpy/random/mtrand.pyx +++ b/numpy/random/mtrand.pyx @@ -2156,7 +2156,7 @@ cdef class RandomState: either positive or negative, hence making our test 2-tailed. Because we are estimating the mean and we have N=11 values in our sample, - we have N-1=10 degrees of freedom. We set our signifance level to 95% and + we have N-1=10 degrees of freedom. We set our significance level to 95% and compute the t statistic using the empirical mean and empirical standard deviation of our intake. We use a ddof of 1 to base the computation of our empirical standard deviation on an unbiased estimate of the variance (note: |