diff --git a/pyerrors/obs.py b/pyerrors/obs.py
index 762f2b06..c009d765 100644
--- a/pyerrors/obs.py
+++ b/pyerrors/obs.py
@@ -63,13 +63,13 @@ class Obs:
                  'idl', 'tag', '_covobs', '__dict__']
 
     S_global = 2.0
-    S_dict = {}
+    S_dict: dict[str, float] = {}
     tau_exp_global = 0.0
-    tau_exp_dict = {}
+    tau_exp_dict: dict[str, float] = {}
     N_sigma_global = 1.0
-    N_sigma_dict = {}
+    N_sigma_dict: dict[str, int] = {}
 
-    def __init__(self, samples: Union[List[List[int]], List[ndarray], ndarray, List[List[float64]], List[List[float]]], names: List[Union[int, Any, str]], idl: Optional[Any]=None, **kwargs):
+    def __init__(self, samples: Union[List[List[int]], List[ndarray], ndarray, List[List[float64]], List[List[float]]], names: List[str], idl: Optional[list[Union[list[int], range]]]=None, **kwargs):
         """ Initialize Obs object.
 
         Parameters
@@ -82,7 +82,8 @@ class Obs:
             list of ranges or lists on which the samples are defined
         """
 
-        if kwargs.get("means") is None and len(samples):
+        means: Optional[list[float]] = kwargs.get("means")
+        if means is None and len(samples):
             if len(samples) != len(names):
                 raise ValueError('Length of samples and names incompatible.')
             if idl is not None:
@@ -100,17 +101,17 @@ class Obs:
             if min(len(x) for x in samples) <= 4:
                 raise ValueError('Samples have to have at least 5 entries.')
 
-        self.names = sorted(names)
+        self.names: list[str] = sorted(names)
         self.shape = {}
         self.r_values = {}
         self.deltas = {}
-        self._covobs = {}
+        self._covobs: dict[str, Covobs] = {}
 
-        self._value = 0
-        self.N = 0
-        self.idl = {}
+        self._value: float = 0.0
+        self.N: int = 0
+        self.idl: dict[str, Union[list[int], range]] = {}
         if idl is not None:
-            for name, idx in sorted(zip(names, idl)):
+            for name, idx in sorted(zip(names, idl, strict=True)):
                 if isinstance(idx, range):
                     self.idl[name] = idx
                 elif isinstance(idx, (list, np.ndarray)):
@@ -124,19 +125,19 @@ class Obs:
                     else:
                         self.idl[name] = list(idx)
                 else:
-                    raise TypeError('incompatible type for idl[%s].' % (name))
+                    raise TypeError('incompatible type for idl[%s].' % name)
         else:
-            for name, sample in sorted(zip(names, samples)):
+            for name, sample in sorted(zip(names, samples, strict=True)):
                 self.idl[name] = range(1, len(sample) + 1)
 
-        if kwargs.get("means") is not None:
-            for name, sample, mean in sorted(zip(names, samples, kwargs.get("means"))):
+        if means is not None:
+            for name, sample, mean in sorted(zip(names, samples, means, strict=True)):
                 self.shape[name] = len(self.idl[name])
                 self.N += self.shape[name]
                 self.r_values[name] = mean
                 self.deltas[name] = sample
         else:
-            for name, sample in sorted(zip(names, samples)):
+            for name, sample in sorted(zip(names, samples, strict=True)):
                 self.shape[name] = len(self.idl[name])
                 self.N += self.shape[name]
                 if len(sample) != self.shape[name]:
@@ -642,7 +643,7 @@ class Obs:
         if save:
             fig1.savefig(save)
 
-        return dict(zip(labels, sizes))
+        return dict(zip(labels, sizes, strict=True))
 
     def dump(self, filename: str, datatype: str="json.gz", description: str="", **kwargs):
         """Dump the Obs to a file 'name' of chosen format.