1. To develop an understanding of various statistical techniques in terms of their assumptions, applications and limitations. 2. To acquire competencies to organize data for computer analysis. 3. To acquire elementary competencies in using computer packages of statistical analyses. 4. This course deals with research methods that are employed in field settings. Correlational analysis techniques with numerical examples will be discussed.
Introduction : Definition and types of statistics; Levels of measurement; Construction of Frequency Distribution, Graphical Representation : Histogram, Frequency Polygon.
Descriptive Statistics : Measures of central tendency, measure of variability; correlation : concept; product movement correlation for ungrouped data.
Inferential Statistics : Normal probability curve : Sampling; Standard Error Formula – Mean, SD.
Hypothesis Testing : Null and Alternative hypothesis, Type I and II errors, ‘t’ Test : Mean for large and small independent samples, ANOVA (one way analysis : independent samples).
Non Parametric Statistics : Assumption, Chi Square, (Null Hypothesis, contingency tables); Rank order correlation.
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