docs: fix 'Bad Value' in cases where it should be 'Bad value'

fix some of the urls that are pointing at invalid locations

Author: georgeRobertson

docs/user_guidance/business_rules.md

@@ -50,7 +50,7 @@ For the simplest rules, you can write them in the filters section. For example,
                     "failure_type": "record",
                     "error_code": "MOVIE_TOO_LONG",
                     "failure_message": "Movie must be less than 4 hours long.",
-                    "category": "Bad Value"
+                    "category": "Bad value"
                 }
             ]
         }
@@ -81,7 +81,7 @@ For the simplest rules, you can write them in the filters section. For example,
                     "failure_type": "submission",
                     "error_code": "MOVIE_TOO_LONG",
                     "failure_message": "Movie must be less than 4 hours long.",
-                    "category": "Bad Value"
+                    "category": "Bad value"
                 }
             ]
         }
@@ -113,7 +113,7 @@ For the simplest rules, you can write them in the filters section. For example,
                     "is_informational": true,
                     "error_code": "MOVIE_TOO_LONG",
                     "failure_message": "Movie must be less than 4 hours long.",
-                    "category": "Bad Value",
+                    "category": "Bad value",
                 }
             ]
         }

docs/user_guidance/data_contract.md

@@ -417,13 +417,13 @@ When a [Feedback Message](./feedback_messages.md) is produced during the contrac
                 "error_message": "File Rejected - movie_uuid is blank.",
                 "error_level": "submission"
             },
-            "Bad Value": {
+            "Bad value": {
                 "error_code": "MOVIE_UUID_02",
                 "error_message": "Record Rejected - movie_uuid has an incorrect data format. movie_uuid={{ movie_uuid }}.",
             }
         },
         "movie_name": {
-            "Bad Value": {
+            "Bad value": {
                 "error_code": "MOVIE_NAME_01",
                 "error_message": "Warning - movie_name has an incorrect data format. movie_name={{ movie_name }}.",
                 "is_informational": true

docs/user_guidance/install.md

@@ -79,7 +79,7 @@ You can install the DVE package through python package managers such as [pip](ht
 
 Python dependencies are listed in the [`pyproject.toml`](https://github.com/NHSDigital/data-validation-engine/blob/main/pyproject.toml). Many of the dependencies are locked to quite restrictive versions due to complexity of this package. Core packages such as Pydantic, Pyspark and DuckDB are unlikely to receive flexible version constraints as changes in those packages could cause the DVE to malfunction. For less important dependencies, we have tried to make the contraints more flexible. Therefore, we would advise you to install the DVE into a seperate environment rather than trying to integrate it into an existing Python environment.
 
-Once you have installed the DVE you are almost ready to use it. To be able to run the DVE, you will need to choose one of the supported pipeline runners (see Backend implementations here - [DuckDB](user_guidance/implementations/duckdb.md) *or* [Spark](user_guidance/implementations/spark.md)) and you will need to create your own dischema document to configure how the DVE should validate incoming data. You can read more about this in the [Getting Started](getting_started.md) page.
+Once you have installed the DVE you are almost ready to use it. To be able to run the DVE, you will need to choose one of the supported pipeline runners (see Backend implementations here - [DuckDB](implementations/duckdb.md) *or* [Spark](implementations/spark.md)) and you will need to create your own dischema document to configure how the DVE should validate incoming data. You can read more about this in the [Getting Started](getting_started.md) page.
 
 
 ## DVE Version Compatability Matrix