update text

app.py

@@ -12,7 +12,7 @@ def roll_die():
 # Roll the die and check if the result is even
 def test_event():
     result = roll_die()
-    return result, "Yes" if result % 2 == 0 else "No"
+    return result, "Yes!" if result % 2 == 0 else "No.."
 
 # Compute the probability of an event
 def compute_event_probability(favorable_outcomes, possible_outcomes):
@@ -74,12 +74,13 @@ with gr.Blocks(css=css) as demo:
         ## Sample Spaces and Outcomes
         The `sample space` is the **set of all possible `outcomes`** of a random experiment or random process.
 
-        For example, if you roll a `six-sided die`, the sample space would be `{1, 2, 3, 4, 5, 6}`, as these are all outcomes that can occur.
+        For example, if you roll a `six-sided die` 🎲, the sample space is all the possible configurations the die could end up in.
+        <br>These are either with the side facing up showing the value 1, or 2 or... We can summarize this as: `{1, 2, 3, 4, 5, 6}`
         """
     )
     with gr.Row():
         die_roll = gr.Button(value="Roll the Die! 🎲🎲")
-        die_roll_output = gr.Textbox(label="You have rolled a..", placeholder="", interactive=False)
+        die_roll_output = gr.Textbox(label="You side facing up shows a..", placeholder="", interactive=False)
     die_roll.click(roll_die, [], [die_roll_output])
 
     gr.Markdown(
@@ -88,7 +89,7 @@ with gr.Blocks(css=css) as demo:
 
         An `event` is any **subset of the `sample space`**, representing a specific outcome or a combination of outcomes.
         <br>
-        Events are events of interest or events we want to analyze in terms of their probability.
+        This often corresponds to some event of interest (e.g. whether if will rain tomorrow) but may be sometimes an interemediary step when dealing with more complex probability problems.
 
         Continuing with our example, an event like `rolling an even number` would correspond to the subset: `{2, 4, 6}`
         
@@ -110,11 +111,11 @@ with gr.Blocks(css=css) as demo:
         $$ P(\text{Event}) = \frac{\text{Number of (Favorable Outcomes)}}{\text{Number of (Possible Outcomes)}} $$
         
         - `Favorable outcomes` are those that satisfy the condition of the `event`.
-        - `Possible outcomes` are all outcomes, regardless of whether they are part of the event or not.
+        - `Possible outcomes` are all the outcomes, regardless of whether they satisfy the event or not.
 
         You can use the space below to calculate the probability of an event.
         <br>
-        Play around with different sets of favorable and possible outcomes to see how the probability changes.
+        Play around with different sets of favorable and possible outcomes to see how the probability changes!
         """
     )