0000005428 00000 n Every basic concept and method is therefore explained in No enrollment or registration. Use OCW to guide your own life-long learning, or to teach others. Massachusetts Institute of Technology. Random variables and distribution functions: 4: Bayes theorem and random variables : 5: Discrete and continuous random variables : 6 MAS131: Introduction to Probability and Statistics Semester 1: Introduction to Probability Lecturer: Dr D J Wilkinson Statistics is concerned with making inferences about the way the world is, based upon things we observe happening. » 38 Lecture 7. 0000006537 00000 n » Introduction to Probability and Statistics Courses Mathematics 44 Lecture 8. ����#�7Du�}�3}4�p @��^Q���skQ������8|�-�e�bIV�~q�.�U�_K��i���:NzX %����4������xf�X&��Qx��O(��cN�;�O�w�89�9���vqI�J���16)��m��H�����Q�0��R�\$E� 04Z\$�"B��nA�2�nr�1���,Q�w�����Mg1�V��xgy���Y�o�&�O�J���6"�`�3���1iZ�h��fz�:��0��עl����Y�bc�b��d����f�+q��:)2%璙Ҍ�`��iJk�A1�7��6t�� �*Z���l:&�Zko!�-O�Y�A�f�H�����{������x��^��%l6���UG�/E�f?��WU��"�6��Dw�m ���X�߽%���(W���o��w��}���vئ��p��n@>�̡�!��ڣ�K�,�k7N�"��A ���y�\>��� �4�{fY�NYO�R6���JW�]�� Knowledge is your reward. » Lecture notes files. 0000015558 00000 n With more than 2,400 courses available, OCW is delivering on the promise of open sharing of knowledge. With more than 2,200 courses available, OCW is delivering on the promise of open sharing of knowledge. 24 Lecture 5. Probability About these notes. �}�6��� I��a�p�\$��)�Fyvd�� )v�}�������%:���� -�����#�e�Z e�B������n_��&q�Ij`�*���pd�SaR����Jy������Q�0� ]GF�Idc(E�� Lecture Notes. Send to friends and colleagues. m��,C�SZ �"ĥ]��.Vo���\$b=�\(e�S��Ԥ�h��@R� �)Yvt:�[v��"l�R��9�z̎zL� x,y��B���H^��S���o��4K�}�褍'������Qg�|�>\$��+Y|����u��C(U�h)[ַ�-@h��|L��z�M��C�>�LFfZj�����ߠh�LK���s�6� �H���>�����;/�k�0 6��7��OZ\�4�%%�HÑ��K�z� {�T������Ti�6�J������-�nu� �Zm��>������%{>جl ��w���\�-���]��E�GR��P*��&�3־��?,M:�)޻RI���Ef9�V_\�>Y�t��� \$�ۈ�Aw��9��Ojt4~��T�h,-u\��{{��� Ĉ�u}Zs�//��m��M�DU� �.��d���R����%˜�����D`�����d;>��bW����9/M�2��Qs�E�f�1����s+�:�u��S�(���PUm@������r�% Y� There's no signup, and no start or end dates. SES # TOPICS; Probability distributions and random variables. 2 Lecture 17. » %PDF-1.3 %���� �ՎN������*t��Px2��AfJ�%�f�� 0000000671 00000 n Find materials for this course in the pages linked along the left. I. Probability: 1: Sets and events : 2: Probabilities and counting rules : 3: Conditional probability and independence : II. 3 Lecture 2. MBA 604, Spring 2003 MBA 604 Introduction to Probability and Statistics Course Content. ), Learn more at Get Started with MIT OpenCourseWare, MIT OpenCourseWare makes the materials used in the teaching of almost all of MIT's subjects available on the Web, free of charge. 0000005956 00000 n Courses Lecture Notes Muhammad El-Taha Department of Mathematics and Statistics University of Southern Maine 96 Falmouth Street Portland, ME 04104-9300. trailer << /Size 428 /Info 410 0 R /Root 413 0 R /Prev 394594 /ID[<31634e4764cc675ef1c0a57aa72fcfc8>] >> startxref 0 %%EOF 413 0 obj << /Type /Catalog /Pages 406 0 R /Metadata 411 0 R >> endobj 426 0 obj << /S 4946 /Filter /FlateDecode /Length 427 0 R >> stream Introduction to Probability Aims • To familiarise students with the ways in which we talk about uncertainty and look at everyday situations in which probability arises • To engage students in activities that will give them contact with the main ideas of probability • To rehearse the language and patterns associated with probability