Updated readme

Author: JAnns98

README.md

@@ -23,20 +23,23 @@ performance improvements. It’s a big one!
 2.  **Horizontal Plots**: Users can now create horizontal layout plots,
     providing compact data visualization. This can be achieved by
     setting `horizontal=True` in the `.plot()` method. See the
-    [Horizontal Plots tutorial](tutorials/08-horizontal_plot.ipynb) for
-    more details.
+    [Horizontal Plots
+    tutorial](https://acclab.github.io/DABEST-python/tutorials/08-horizontal_plot.html)
+    for more details.
 
 3.  **Forest Plots**: Forest plots provide a simple and intuitive way to
     visualize many delta-delta (or delta *g*), mini-meta, or regular
     delta effect sizes at once from multiple different dabest objects
     without presenting the raw data. See the [Forest Plots
-    tutorial](tutorials/07-forest_plot.ipynb) for more details.
+    tutorial](https://acclab.github.io/DABEST-python/tutorials/07-forest_plot.html)
+    for more details.
 
 4.  **Gridkey**: Users can now represent experimental labels in a
     ‘gridkey’ table. This can be accessed with the `gridkey` parameter
     in the `.plot()` method. See the gridkey section in the [Plot
-    Aesthetics tutorial](tutorials/09-plot_aesthetics.ipynb) for more
-    details.
+    Aesthetics
+    tutorial](https://acclab.github.io/DABEST-python/tutorials/09-plot_aesthetics.html)
+    for more details.
 
 5.  **Other Visualization Improvements**:
 
@@ -65,7 +68,7 @@ performance improvements. It’s a big one!
         Raw and contrast bars are shown by default. Users can customize
         these bars and add summary bands as needed. For detailed
         customization instructions, please refer to the [Plot Aesthetics
-        tutorial](tutorials/09-plot_aesthetics.ipynb).
+        tutorial](https://acclab.github.io/DABEST-python/tutorials/09-plot_aesthetics.html).
 
     - **Tighter spacing in delta-delta and mini-meta plots**: We have
       adjusted the spacing of delta-delta and mini-meta plots to reduce

nbs/read_me.ipynb

@@ -33,19 +33,19 @@
     "\n",
     "1. **Python 3.13 Support**: DABEST now supports Python 3.10—3.13.\n",
     "\n",
-    "2. **Horizontal Plots**: Users can now create horizontal layout plots, providing compact data visualization. This can be achieved by setting `horizontal=True` in the `.plot()` method. See the [Horizontal Plots tutorial](tutorials/08-horizontal_plot.ipynb) for more details.\n",
+    "2. **Horizontal Plots**: Users can now create horizontal layout plots, providing compact data visualization. This can be achieved by setting `horizontal=True` in the `.plot()` method. See the [Horizontal Plots tutorial](https://acclab.github.io/DABEST-python/tutorials/08-horizontal_plot.html) for more details.\n",
     "\n",
-    "3. **Forest Plots**: Forest plots provide a simple and intuitive way to visualize many delta-delta (or delta *g*), mini-meta, or regular delta effect sizes at once from multiple different dabest objects without presenting the raw data. See the [Forest Plots tutorial](tutorials/07-forest_plot.ipynb) for more details.\n",
+    "3. **Forest Plots**: Forest plots provide a simple and intuitive way to visualize many delta-delta (or delta *g*), mini-meta, or regular delta effect sizes at once from multiple different dabest objects without presenting the raw data. See the [Forest Plots tutorial](https://acclab.github.io/DABEST-python/tutorials/07-forest_plot.html) for more details.\n",
     "\n",
-    "4. **Gridkey**: Users can now represent experimental labels in a ‘gridkey’ table. This can be accessed with the `gridkey` parameter in the `.plot()` method. See the gridkey section in the [Plot Aesthetics tutorial](tutorials/09-plot_aesthetics.ipynb) for more details.\n",
+    "4. **Gridkey**: Users can now represent experimental labels in a ‘gridkey’ table. This can be accessed with the `gridkey` parameter in the `.plot()` method. See the gridkey section in the [Plot Aesthetics tutorial](https://acclab.github.io/DABEST-python/tutorials/09-plot_aesthetics.html) for more details.\n",
     "\n",
     "5. **Other Visualization Improvements**:\n",
     "   - **Comparing means and effect sizes**: The estimation plots now include three types of customizable visual features to enhance contextualization and comparison of means and effect sizes:\n",
     "     - **Bars for the mean of the observed values (`raw_bars`)**: Colored rectangles that extend from the zero line to the mean of each group's raw data. These bars visually highlight the central tendency of the raw data.\n",
     "     - **Bars for effect size/s (`contrast_bars`)**: Similar to raw bars, these highlight the effect-size difference between two groups (typically test and control) in the contrast axis. They provide a visual representation of the differences between groups.\n",
     "     - **Summary bands (`reference_band`)**: An optional band or ribbon that can be added to emphasize a specific effect size’s confidence interval that is used as a reference range across the entire contrast axis. Unlike raw and contrast bars, these span horizontally (or vertically if `horizontal=True`) and are not displayed by default.\n",
     "\n",
-    "          Raw and contrast bars are shown by default. Users can customize these bars and add summary bands as needed. For detailed customization instructions, please refer to the [Plot Aesthetics tutorial](tutorials/09-plot_aesthetics.ipynb).\n",
+    "          Raw and contrast bars are shown by default. Users can customize these bars and add summary bands as needed. For detailed customization instructions, please refer to the [Plot Aesthetics tutorial](https://acclab.github.io/DABEST-python/tutorials/09-plot_aesthetics.html).\n",
     "\n",
     "   - **Tighter spacing in delta-delta and mini-meta plots**: We have adjusted the spacing of delta-delta and mini-meta plots to reduce whitespace. The new format brings the overall effect size closer to the two-groups effect sizes. In addition, delta-delta plots now have a gap in the zero line to separate the delta-delta from the ∆ effect sizes.\n",
     "\n",