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A total of 1 courses have been found.
Analysis, interpretation of research data; descriptive statistics; introduction to probability, sampling theory, statistical inference (binomial, normal distribution, t-distribution models); linear correlation, regression.

Many fields of graduate study involve data whose meaning and trustworthiness are not obvious. Analytical techniques must be applied to bring out the implications of the data and to verify that apparent trends are not the result of chance. This course introduces such methods. It is the basic course which serves as a prerequisite for further work in statistical methods. The primary emphasis is on techniques used in the behavioral sciences--education, psychology, sociology, human factors in industrial settings, and business.

Student evaluation is based on computer assignments and two types of tests: those which cover the minimum competencies expected of all students and tests which cover levels of achievement above the minimum level.

Discussion sections, led by TAs, provide opportunities for questioning and consideration of homework exercises.

Software: Microsoft Excel.