Use probability trees as a tool for finding probabilities. In the Probability and Statistics course the unit is a classical treatment of probability and includes basic probability principles, conditional probability, discrete random variables (including the Binomial distribution) and continuous random variables (with emphasis on the normal distribution). an operating system that supports the latest browser update, the latest browser update (Chrome recommended; Firefox, Safari supported; Edge and Internet Explorer are supported but not recommended). Determine the likelihood of making type I and type II errors, and explain how to reduce them, in context. Identify and distinguish among cases where use of calculations specific to independent samples, matched pairs, and ANOVA are appropriate. Recognize the distinction between association and causation, and identify potential lurking variables for explaining an observed relationship. Course description. Let E and F be events of a sample space S of an experiment, then; Property 2: If A and B are two events in a sample space S and F is an event of S, such that P(F)≠0, then; P((A ∪ B)|F) = P(A|F) + P(B|F) – P((A ∩ B)|F). develop strong learning strategies for Probability & Statistics, as well as other online courses. In the special case of linear relationship, use the least squares regression line as a summary of the overall pattern, and use it to make predictions. * : By Dr. ANEESH KUMAR. Probability and Statistics (IT302) Class No. (i) P (A ∩ B), Solution: Given, P (A) = 0.8, P (B) = 0.5 and P (B|A) = 0.4, P (A ∩ B) = P(B|A).P(A) = 0.4 x 0.8 = 0.32, Your email address will not be published. The unit covers inferential methods for the population mean and population proportion, Inferential methods for comparing the means of two groups and of more than two groups (ANOVA), the Chi-Square test for independence and linear regression. Specify the and alternative hypotheses for comparing groups. ]�W'x����"�p��E:�j(��� ��w$ٿ��]J�Α����S�ʢ�"��P��so�-��BI}�[GMf��Ӛs�M3�9n���-�C�&J�S�.��ӥ9��C�yu^)�O�1�S��v��b-'��h�L�Z�� ��9q�=Y�n�Y9MS���(S��6��[��N�.T�/̫%��?i��Q|���|�F���$�fH���q]� E\ņ�=�)�1.V17p.q�f.h�+O�*ϻ�x|�C���"p���_Ke.��mF�ֱ,����'�����b�4$��y��P$�a�&8��i�%�CN'F�L�� � ��}ʆ�i�$��Cs��^�J�L8�p(m������Q�4�M��B_W4&��]h�[KKDm�uxl+��$�mH P��X��6�L*4�g�SiL��eVe-͍�9��j�ڧ��}�#ؕ`\��Y����\;x�5�%. Produce a two-way table, and interpret the information stored in it about the association between two categorical variables by comparing conditional percentages. Both probability units culminate in a discussion of sampling distributions that is grounded in simulation. Probability and Statistics includes the classical treatment of probability as it is in the earlier versions of the OLI Statistics course, while Statistical Reasoning gives a more abbreviated treatment of probability, using it primarily to set up the inference unit that follows it. Choose the appropriate inferential method for examining the relationship between two variables and justify the choice. We offer two versions of statistics, each with a different emphasis: Probability and Statistics and Statistical Reasoning. When you've finished the section, you can review everything you've learned by working through the bonus workbook. OLI system requirements, regardless of course: Some courses include exercises with exceptions to these requirements, such as technology that cannot be used on mobile devices. Relate measures of center and spread to the shape of the distribution, and choose the appropriate measures in different contexts. Use the normal distribution as an approximation of the binomial distribution, when appropriate. Designed for students with no prior knowledge in statistics, its only prerequisite is basic algebra. If not, you can review the videos and notes again or ask for help in the Q&A section. Explain what a confidence interval represents and determine how changes in sample size and confidence level affect the precision of the confidence interval. Probability & Statistics includes data files and software instructions, but not the statistical analysis software itself. Compare and contrast distributions (of quantitative data) from two or more groups, and produce a brief summary, interpreting your findings in context. Classify a data analysis situation (involving two variables) according to the “role-type classification,” and state the appropriate display and/or numerical measures that should be used in order to summarize the data. These include: simulations, “walk-throughs” that integrate voice and graphics to explain an example of a procedure or a difficult concept, and, most prominently, computer tutors in which students practice problem solving, with hints and immediate and targeted feedback. The workbooks include tons of extra practice problems, so they're a great way to solidify what you just learned in that section. Includes a classical treatment of probability. In particular, explain what the p-value is and how it is used to draw conclusions. The probability will be 0 for something that is impossible to happen. Introductory-level course teaches students the basic concepts of statistics and the logic of statistical reasoning. ]�h�׉� ���ױ���v2�e�h�%��-�u�8�m?�.iM�����׌��U)p�w����u����5��X�v�_����b�a�5��3�G=��u&!�z���$��⹖z�����Qw��~h. In addition, the course helps students gain an appreciation for the diverse applications of statistics and its relevance to their lives and fields of study. Learn about Open & Free OLI courses by visiting the “Open & Free features” tab below. Explain the logic behind and the process of hypotheses testing. Explain how a density function is used to find probabilities involving continuous random variables.