Correct typos

Author: bcopy

content/titanic/CaseStudy_Titanic-Solution.ipynb

@@ -45,7 +45,7 @@
     "#### Objective\n",
     "In this challenge, we will complete the analysis of what sorts of people were likely to survive. \n",
     "\n",
-    "In addition, we will build a regression model to predict ticket price(Fare).\n",
+    "In addition, we will build a regression model to predict ticket price (Fare).\n",
     "\n"
    ]
   },
@@ -1727,7 +1727,7 @@
     "### Feature Engineering\n",
     "We'll create a new column FamilySize. There are 2 columns related to family size, parch indicates parent or children number, Sibsp indicates sibling and spouse number.\n",
     "\n",
-    "Take one name 'Asplund' as example, we can see that total family size is 7(Parch + SibSp + 1), and each family member has same Fare, which means the Fare is for the whole group. So family size will be an important feature to predict Fare. There're only 4 Asplunds out of 7 in the dataset becasue the dataset is only a subset of all passengers."
+    "Take one name 'Asplund' as example, we can see that total family size is 7(Parch + SibSp + 1), and each family member has same Fare, which means the Fare is for the whole group. So family size will be an important feature to predict Fare. There're only 4 Asplunds out of 7 in the dataset because the dataset is only a subset of all passengers."
    ]
   },
   {
@@ -2054,7 +2054,7 @@
     "\n",
     "## Step 4: Modeling\n",
     "\n",
-    "Now we have a relatively clean dataset(Except for Cabin column which has many missing values). We can do a classification on Survived to predict whether a passenger could survive the desaster or a regression on Fare to predict ticket fare. This dataset is not a good dataset for regression. But since we don't talk about classification in this workshop we will construct a linear regression on Fare in this exercise."
+    "Now we have a relatively clean dataset (except for the Cabin column which has many missing values). We can do a classification on Survived to predict whether a passenger could survive the desaster or a regression on Fare to predict ticket fare. This dataset is not a good dataset for regression. But since we don't talk about classification in this workshop we will construct a linear regression on Fare in this exercise."
    ]
   },
   {